venue stringclasses 1
value | year int64 2.03k 2.03k | title stringlengths 17 189 | snippet stringlengths 289 3.84k | url stringlengths 54 54 |
|---|---|---|---|---|
AAAI | 2,026 | 10 Open Challenges Steering the Future of Vision-Language-Action Models | Due to their ability of follow natural language
instructions,
vision-language-action (VLA) models are increasingly preva-
lent in the embodied AI arena, following the widespread suc-
cess of their precursors—LLMs and VLMs. In this paper,
we discuss 10 principal milestones in the ongoing develop-
ment of VLA models—mult... | https://ojs.aaai.org/index.php/AAAI/article/view/41333 |
AAAI | 2,026 | 2-ASP(Q) Solving Based on CEGAR | The ASP(Q) language extends Answer Set Programming (ASP) with Quantifiers that operate over answer sets.
Thus, ASP(Q) facilitates a more natural encoding of problems whose complexity exceeds NP within the ASP framework.
In this paper we focus on ASP(Q) programs with two quantifiers, i.e., 2-ASP(Q) programs, which can b... | https://ojs.aaai.org/index.php/AAAI/article/view/38975 |
AAAI | 2,026 | 2D Gaussians Spatial Transport for Point-supervised Density Regression | This paper introduces Gaussian Spatial Transport (GST), a novel framework that leverages Gaussian splatting to facilitate transport from the probability measure in the image coordinate space to the annotation map. We propose a Gaussian splatting-based method to estimate pixel-annotation correspondence, which is then us... | https://ojs.aaai.org/index.php/AAAI/article/view/37836 |
AAAI | 2,026 | 2D-CrossScan Mamba: Enhancing State Space Models with Spatially Consistent Multi-Path 2D Information Propagation | Despite recent progress in adapting State Space Models such as Mamba to vision tasks, their intrinsic 1D scanning mechanism imposes limitations when applied to inherently 2D-structured data like images. Existing adaptations, including VMamba and 2DMamba, either suffer from inconsistency between scanning order and spati... | https://ojs.aaai.org/index.php/AAAI/article/view/38855 |
AAAI | 2,026 | 360Explorer: Exploring 4D Controllable World in Panoramic Videos | We present 360Explorer, a novel approach for generating 4D controllable panoramic videos conditioned on user-provided 3D instructions for exploring and manipulating dynamic worlds. Compared to existing perspective-based methods struggle to address spatial consistency during camera rotation in place, we introduce the pa... | https://ojs.aaai.org/index.php/AAAI/article/view/37325 |
AAAI | 2,026 | 3D Gaussian Splatting for Reconstructing Large Sparse Environments (Student Abstract) | 3D Gaussian splatting (3DGS) has recently demonstrated significant potential in computer vision, enabling high-fidelity 3D scene reconstruction with real-time rendering and fast training times. However, existing methods struggle in large, visually sparse, geometric self-similarity environments due to heavy reliance on ... | https://ojs.aaai.org/index.php/AAAI/article/view/42189 |
AAAI | 2,026 | 3D-ANC: Adaptive Neural Collapse for Robust 3D Point Cloud Recognition | Deep neural networks have recently achieved notable progress in 3D point cloud recognition, yet their vulnerability to adversarial perturbations poses critical security challenges in practical deployments. Conventional defense mechanisms struggle to address the evolving landscape of multifaceted attack patterns. Throug... | https://ojs.aaai.org/index.php/AAAI/article/view/37434 |
AAAI | 2,026 | 3D-DRES: Detailed 3D Referring Expression Segmentation | Current 3D visual grounding tasks only process sentence-level detection or segmentation, which critically fails to leverage the rich compositional contextual reasonings within natural language expressions. To address this challenge, we introduce Detailed 3D Referring Expression Segmentation (3D-DRES), a new task that p... | https://ojs.aaai.org/index.php/AAAI/article/view/37288 |
AAAI | 2,026 | 3D4D: An Interactive, Editable, 4D World Model via 3D Video Generation | We introduce DreamLand, an interactive 4D visualization framework that integrates WebGL with Supersplat rendering. It transforms static images and text into coherent 4D scenes through four core modules and employs a foveated rendering strategy for efficient, real-time multi-modal interaction. This framework enables ada... | https://ojs.aaai.org/index.php/AAAI/article/view/42351 |
AAAI | 2,026 | 3DAlign-DAER: Dynamic Attention Policy and Efficient Retrieval Strategy for Fine-grained 3D-Text Alignment at Scale | Despite recent advancements in 3D-text cross-modal alignment, existing state-of-the-art methods still struggle to align fine-grained textual semantics with detailed geometric structures, and their alignment performance degrades significantly when scaling to large-scale 3D databases. To overcome this limitation, we intr... | https://ojs.aaai.org/index.php/AAAI/article/view/36987 |
AAAI | 2,026 | 3DDM: Physically-based Anisotropic 3D Diffusion Model with 3D Gaussian for Point Cloud Completion | A 3D point cloud completion task is to generate completed 3D objects given partial observations. Auto-encoder-based models suffer from poor generalization ability to untrained 3D data. Current diffusion-based models add isotropic noise with the same variance in three x, y, z axes. More importantly, these models ignore ... | https://ojs.aaai.org/index.php/AAAI/article/view/38070 |
AAAI | 2,026 | 3DTeethSAM: Taming SAM2 for 3D Teeth Segmentation | 3D teeth segmentation, involving the localization of tooth instances and their semantic categorization in 3D dental models, is a critical yet challenging task in digital dentistry due to the complexity of real-world dentition. In this paper, we propose 3DTeethSAM, an adaptation of the Segment Anything Model 2 (SAM2) fo... | https://ojs.aaai.org/index.php/AAAI/article/view/37702 |
AAAI | 2,026 | 3One2: One-Step Regression plus One-Step Diffusion for One-Hot Modulation in Dual-Path Video Snapshot Compressive Imaging | Video snapshot compressive imaging (SCI) captures dynamic scene sequences through a two-dimensional (2D) snapshot, fundamentally relying on optical modulation for hardware compression and the corresponding software reconstruction. While mainstream video SCI using random binary modulation has demonstrated success, it in... | https://ojs.aaai.org/index.php/AAAI/article/view/37935 |
AAAI | 2,026 | 4D Point Cloud Segmentation via Active Test-Time Adaptation | 4D point cloud segmentation is crucial for autonomous driving with continuous LiDAR streams. While test-time adaptation (TTA) is the standard approach for handling dynamic environments, current methods suffer from catastrophic error accumulation due to over-reliance on pseudo-labels. Active learning could provide relia... | https://ojs.aaai.org/index.php/AAAI/article/view/39277 |
AAAI | 2,026 | 4D Scaffold Gaussian Splatting with Dynamic-Aware Anchor Growing for Efficient and High-Fidelity Dynamic Scene Reconstruction | Modeling dynamic scenes through 4D Gaussians offers high visual fidelity and fast rendering speeds, but comes with significant storage overhead.
Recent approaches mitigate this cost by aggressively reducing the number of Gaussians.
However, this inevitably removes Gaussians essential for high-quality rendering, leading... | https://ojs.aaai.org/index.php/AAAI/article/view/37332 |
AAAI | 2,026 | 4DSTR: Advancing Generative 4D Gaussians with Spatial-Temporal Rectification for High-Quality and Consistent 4D Generation | Remarkable advances in recent 2D image and 3D shape generation have induced a significant focus on dynamic 4D content generation. However, previous 4D generation methods commonly struggle to maintain spatial-temporal consistency and adapt poorly to rapid temporal variations, due to the lack of effective spatial-tempora... | https://ojs.aaai.org/index.php/AAAI/article/view/37659 |
AAAI | 2,026 | 6DAttack: Backdoor Attacks in the 6DoF Pose Estimation | Recent advances in deep learning have enabled highly accurate six-degree-of-freedom (6DoF) object pose estimation, leading to its widespread use in real-world applications such as robotics, augmented reality, virtual reality, and autonomous systems. However, backdoor attacks pose a major security risk to deep learning ... | https://ojs.aaai.org/index.php/AAAI/article/view/40855 |
AAAI | 2,026 | A Benchmark Dataset for Spatially Aligned Road Damage Assessment in Small Uncrewed Aerial Systems Disaster Imagery | This paper presents the largest known benchmark dataset for road damage assessment and road alignment, and provides 18 baseline models trained on the CRASAR-U-DRIODs dataset's post-disaster small uncrewed aerial systems (sUAS) imagery from 10 federally declared disasters, addressing three challenges within prior post-d... | https://ojs.aaai.org/index.php/AAAI/article/view/41248 |
AAAI | 2,026 | A Better Start: Sensitivity-Aware Warm-Up for Robust and Efficient Fine-Tuning | As an essential component of fine-tuning, warm-up plays a crucial role in promoting stability and generalization. Many studies have examined its underlying mechanisms from different aspects. However, most of the studies focus on incorporating these insights into optimizers to reduce the reliance on warm-up. Little atte... | https://ojs.aaai.org/index.php/AAAI/article/view/40284 |
AAAI | 2,026 | A Boundary Token Graph for Zero-Shot Relation Triplet Extraction Involving Discontinuous Entities | Zero-Shot Relation Triplet Extraction (ZSRTE) aims to extract head-tail entity pairs and their corresponding relations from sentences, where the relations available during inference are not seen during training. Existing methods typically assume that entities are continuous; however, in practice, entities can be discon... | https://ojs.aaai.org/index.php/AAAI/article/view/40515 |
AAAI | 2,026 | A Brain-Inspired Saliency Prediction Framework for Human-AI Cognitive Consistency in AIGC Content via Multi-Region Liquid Neurons | In recent years, human-AI cognitive consistency has emerged as a crucial perspective for evaluating the perceptual quality and interpretability of AIGC (Artificial Intelligence Generated Content). This paper proposes a biologically inspired saliency prediction framework that models six core regions of the human visual ... | https://ojs.aaai.org/index.php/AAAI/article/view/38837 |
AAAI | 2,026 | A Catalyst Framework for the Quantum Linear System Problem via the Proximal Point Algorithm | Solving systems of linear equations is a fundamental problem, but it can be computationally intensive for classical algorithms in high dimensions. Existing quantum algorithms can achieve exponential speedups for the quantum linear system problem (QLSP) in terms of the problem dimension, but the advantage is bottlenecke... | https://ojs.aaai.org/index.php/AAAI/article/view/39418 |
AAAI | 2,026 | A Causal Framework to Measure and Mitigate Non-binary Treatment Discrimination | Fairness studies of algorithmic decision-making systems often simplify complex decision processes, such as bail or lending decisions, into binary classification tasks (e.g., approve or not approve). However, these approaches overlook that such decisions are not inherently binary; they also involve non-binary treatment ... | https://ojs.aaai.org/index.php/AAAI/article/view/41247 |
AAAI | 2,026 | A Causal Target for Learning to Defer Under Hidden Confounding | Learning decision policies from confounded observational data is a challenging task in causal inference, as unobserved confounders can lead to biased or suboptimal actions when relying solely on machine learning models. A synergistic approach is learning to defer, which decides when to act itself and when to defer to a... | https://ojs.aaai.org/index.php/AAAI/article/view/39493 |
AAAI | 2,026 | A Closer Look at Knowledge Distillation in Spiking Neural Network Training | Spiking Neural Networks (SNNs) become popular due to excellent energy efficiency, yet facing challenges for effective model training.
Recent works improve this by introducing knowledge distillation (KD) techniques, with the pre-trained artificial neural networks (ANNs) used as teachers and the target SNNs as students.
... | https://ojs.aaai.org/index.php/AAAI/article/view/37175 |
AAAI | 2,026 | A Compliant Robotic Leg Based on Fibre Jamming (Abstract Reprint) | Humans possess a remarkable ability to react to unpredictable perturbations through immediate mechanical responses, which harness the visco-elastic properties of muscles to maintain balance. Inspired by this behavior, we propose a novel design of a robotic leg utilizing fibre jamming. The research highlights the potent... | https://ojs.aaai.org/index.php/AAAI/article/view/41389 |
AAAI | 2,026 | A Compress-Expand Framework for Automatic Lesson Plan Generation | Creating a well-structured lesson plan is essential for improving classroom efficiency, yet it is often a labor-intensive process. Recently, many studies have leveraged large language models (LLMs) to generate lesson plans automatically. However, existing methods heavily rely on LLMs that are pre-trained on large-scale... | https://ojs.aaai.org/index.php/AAAI/article/view/41202 |
AAAI | 2,026 | A Content-Preserving Secure Linguistic Steganography | Existing linguistic steganography methods primarily rely on content transformations to conceal secret messages. However, they often cause subtle yet looking-innocent deviations between normal and stego texts, posing potential security risks in real-world applications. To address this challenge, we propose a content-pre... | https://ojs.aaai.org/index.php/AAAI/article/view/40903 |
AAAI | 2,026 | A Course Correction in Steerability Evaluation: Revealing Miscalibration and Side Effects in LLMs | Despite advances in large language models (LLMs) on reasoning and instruction-following benchmarks, it is unclear whether they can reliably produce outputs aligned with a variety of user goals, a concept called steerability. We highlight two gaps in current LLM evaluations for assessing steerability. First, many benchm... | https://ojs.aaai.org/index.php/AAAI/article/view/41057 |
AAAI | 2,026 | A Data-Centric Analysis of the Impact of Training Data Quality vs. Quantity on P300 Brain-Computer Interface Performance (Student Abstract) | The current standard for training brain-computer interface (BCI) machine learning models is user-specific. There is a high interest in developing generic models that are trained on data from other users to minimize BCI calibration time; however, this is limited by noisy, non-stationary brain signals and high inter-user... | https://ojs.aaai.org/index.php/AAAI/article/view/42219 |
AAAI | 2,026 | A Deployed Investigative AI Search Engine for Combating Human Trafficking at Web Scale | Online human trafficking investigations generate vast amounts of noisy, heterogeneous, and deliberately obfuscated data, making traditional search and analytics tools ineffective for supporting law enforcement. This paper discusses the deployment of the Domain-Specific Insight Graphs (DIG) system, an AI-powered investi... | https://ojs.aaai.org/index.php/AAAI/article/view/41436 |
AAAI | 2,026 | A Dialogue-Based Learning Analytics Framework for Collaborative Game-Based Learning | In computer-supported collaborative learning environments, analyzing student dialogue is essential for understanding collaborative problem-solving behaviors and supporting effective learning. Prior work often treats all dialogue interactions uniformly, failing to capture how specific dialogue interaction differentially... | https://ojs.aaai.org/index.php/AAAI/article/view/42116 |
AAAI | 2,026 | A Differential Perspective on Distributional Reinforcement Learning | To date, distributional reinforcement learning (distributional RL) methods have exclusively focused on the discounted setting, where an agent aims to optimize a discounted sum of rewards over time. In this work, we extend distributional RL to the average-reward setting, where an agent aims to optimize the reward receiv... | https://ojs.aaai.org/index.php/AAAI/article/view/39706 |
AAAI | 2,026 | A Disease-Aware Dual-Stage Framework for Chest X-ray Report Generation | Radiology report generation from chest X-rays is an important task in artificial intelligence with the potential to greatly reduce radiologists' workload and shorten patient wait times. Despite recent advances, existing approaches often lack sufficient disease-awareness in visual representations and adequate vision-lan... | https://ojs.aaai.org/index.php/AAAI/article/view/40688 |
AAAI | 2,026 | A Domain-specific Heuristic for PDDL+-based Traffic Signal Optimisation | Optimising traffic signals is crucial for mitigating urban congestion, and automated planning, particularly with PDDL+, has shown promise for real-world deployment due to its flexibility and centralised perspective. While existing PDDL+ models guarantee deployability on current infrastructure, they face significant lim... | https://ojs.aaai.org/index.php/AAAI/article/view/40939 |
AAAI | 2,026 | A Fast Heuristic Search Approach for Energy-Optimal Profile Routing for Electric Vehicles | We study the energy-optimal shortest path problem for electric vehicles (EVs) in large-scale road networks, where recuperated energy along downhill segments introduces negative energy costs. While traditional point-to-point pathfinding algorithms for EVs assume a known initial energy level, many real-world scenarios in... | https://ojs.aaai.org/index.php/AAAI/article/view/41005 |
AAAI | 2,026 | A Flat Minima Perspective on Understanding Augmentations and Model Robustness | Model robustness indicates a model’s capability to generalize well on unforeseen distributional shifts, including data corruptions and adversarial attacks. Data augmentation is one of the most prevalent and effective ways to enhance robustness. Despite the great success of the diverse augmentations in different fields,... | https://ojs.aaai.org/index.php/AAAI/article/view/40011 |
AAAI | 2,026 | A Fortiori Case-Based Reasoning: From Theory to Data (Abstract Reprint) | The widespread application of uninterpretable machine learning systems for sensitive purposes has spurred research into elucidating the decision-making process of these systems. These efforts have their background in many different disciplines, one of which is the field of AI & law. In particular, recent works have obs... | https://ojs.aaai.org/index.php/AAAI/article/view/41413 |
AAAI | 2,026 | A Foundation Model for Brain MRI with Dynamic Modality Integration (Student Abstract) | We introduce a single–backbone foundation model for brain MRI that supports dynamic modality integration: it operates with arbitrary, possibly unseen, combinations of MRI sequences at pretrain and transfer. The encoder is conditioned by text-derived modality embeddings via conditional layer normalization, while a varia... | https://ojs.aaai.org/index.php/AAAI/article/view/42245 |
AAAI | 2,026 | A Framework for Belief-based Programs and Their Verification (Abstract Reprint) | Belief-based programming is a probabilistic extension of the GOLOG program family where every action and sensing result can be noisy and every test condition refers to the agent’s subjective beliefs. Inherited from GOLOG programs, the action-centered feature makes belief programs fairly suitable for high-level robot co... | https://ojs.aaai.org/index.php/AAAI/article/view/41390 |
AAAI | 2,026 | A GPU-based Constraint Programming Solver | Machine learning has tremendously benefited from graphics processing units (GPUs) to accelerate training and inference by several orders of magnitude. However, this success has not been replicated in general and exact combinatorial optimization. Our key contribution is to propose a general-purpose discrete constraint p... | https://ojs.aaai.org/index.php/AAAI/article/view/38448 |
AAAI | 2,026 | A General Anchor-Based Framework for Scalable Fair Clustering | Fair clustering is crucial for mitigating bias in unsupervised learning, yet existing algorithms often suffer from quadratic or super-quadratic computational complexity, rendering them impractical for large-scale datasets. To bridge this gap, we introduce the Anchor-based Fair Clustering Framework (AFCF), a novel, gene... | https://ojs.aaai.org/index.php/AAAI/article/view/39894 |
AAAI | 2,026 | A General Highly Accurate Online Planning Method Integrating Large Language Models into Nested Rollout Policy Adaptation for Dialogue Tasks | In goal-oriented dialogue tasks, the main challenge is to steer the interaction towards a given goal within a limited number of turns. Existing approaches either rely on elaborate prompt engineering, whose effectiveness is heavily dependent on human experience, or integrate policy networks and pre-trained policy models... | https://ojs.aaai.org/index.php/AAAI/article/view/40638 |
AAAI | 2,026 | A Geometric Perspective on Optimizing Vector Quantized Latent Diffusion Model for Image Restoration | In this paper, we investigate the limitations of the Vector Quantized Latent Diffusion Model (VQ-LDM) in restoration tasks. We identify a performance gap between the Vector Quantization (VQ) and Diffusion Model components, manifested as a significant discrepancy between the reconstruction quality of ground truth images... | https://ojs.aaai.org/index.php/AAAI/article/view/42462 |
AAAI | 2,026 | A Graph-Theoretical Perspective on Law Design for Multiagent Systems | A law in a multiagent system is a set of constraints imposed on agents' behaviours to avoid undesirable outcomes. The paper considers two types of laws: useful laws that, if followed, completely eliminate the undesirable outcomes and gap-free laws that guarantee that at least one agent can be held responsible each time... | https://ojs.aaai.org/index.php/AAAI/article/view/40211 |
AAAI | 2,026 | A Guardrail Framework for Sensitive Financial Information Protection: A Taxonomy-Driven Approach | The increasing adoption of large language models in the fi-nancial sector introduces significant challenges related to the handling of sensitive financial information (SFI). Existing general-purpose content safety solutions, or guardrails, often fall short in detecting domain-specific risks inherent in finan-cial data ... | https://ojs.aaai.org/index.php/AAAI/article/view/41498 |
AAAI | 2,026 | A Human-AI Collaboration Mechanism Study on AIGC Assisted Image Production for Special Coverage | Artificial Intelligence Generated Content (AIGC) assisting image production triggers controversy in journalism while attracting attention from media agencies. Key issues involve misinformation, authenticity, semantic fidelity, and interpretability. Most AIGC tools are opaque “black boxes,” hindering the dual demands of... | https://ojs.aaai.org/index.php/AAAI/article/view/41304 |
AAAI | 2,026 | A Human-Centric Pipeline for Aligning Large Language Models with Chinese Medical Ethics | Recent advances in large language models (LLMs) have enabled their application to a range of healthcare tasks. However, aligning LLMs with the nuanced demands of medical ethics, especially under complex real-world scenarios, remains underexplored. In this work, we present MedES, a dynamic, scenario-centric benchmark sp... | https://ojs.aaai.org/index.php/AAAI/article/view/41211 |
AAAI | 2,026 | A Hybrid Space Model for Misaligned Multi-modality Image Fusion | Infrared and visible image fusion aims to integrate complementary information, such as thermal saliency from infrared imagery and fine-grained texture details from visible imagery. However, real-world multi-modal misalignment and geometric deformation often introduce severe artifacts. Most existing methods focus on fea... | https://ojs.aaai.org/index.php/AAAI/article/view/38078 |
AAAI | 2,026 | A Knowledge Compilation Map for Quantum Information | Despite their widespread use in quantum computing and physics, the relative strengths and weaknesses of Matrix Product States (MPS), Decision Diagrams (DDs), and Restricted Boltzmann Machines (RBMs) remains poorly understood.
We analytically compare the succinctness of these quantum state representations and analyze t... | https://ojs.aaai.org/index.php/AAAI/article/view/39018 |
AAAI | 2,026 | A Lightweight Safety Helmet Compliance Detection via Multimodal Fusion (Student Abstract) | Ensuring proper use of personal protective equipment (PPE), especially helmets, is essential for workplace safety. Conventional object detectors often fail to distinguish whether a helmet is worn correctly, and existing approaches relying on single-model pipelines are prone to localization errors and false alarms. More... | https://ojs.aaai.org/index.php/AAAI/article/view/42274 |
AAAI | 2,026 | A Logical Analysis of an Information Filtering Architecture Based on Epistemic Trust Inference | In agent theory, epistemic trust is used to infer beliefs, for example by filtering out the information the agent receives from untrustworthy agents. Moreover, trust itself can be inferred from other information. We introduce a simple information filtering architecture that clearly distinguishes the relation between th... | https://ojs.aaai.org/index.php/AAAI/article/view/39001 |
AAAI | 2,026 | A Metacognitive Architecture for Correcting LLM Errors in AI Agents | The ability to correct mistakes and adapt to users' changing needs is critical for AI agents to remain robust and trustworthy. LLM-based agents are inherently prone to errors like hallucinations and misinterpretations. We observed this challenge in SAMI, an AI social agent deployed in Georgia Tech's OMSCS program for t... | https://ojs.aaai.org/index.php/AAAI/article/view/41465 |
AAAI | 2,026 | A More Efficient Reduction from Outlier-Aware to Outlier-Free k-Median | Given a non-negative integer \ell, the k-median with outliers problem extends the standard k-median problem by allowing the removal of up to \ell points and minimizing the clustering cost over the remaining ones. Algorithmic development in this setting remains an active area of research due to its relevance in processi... | https://ojs.aaai.org/index.php/AAAI/article/view/40090 |
AAAI | 2,026 | A Multi-Agent Conversational Bandit Approach to Online Evaluation and Selection of User-Aligned LLM Responses | Prompt-based offline methods are commonly used to optimize large language model (LLM) responses, but evaluating these responses is computationally intensive and often fails to accommodate diverse response styles. This study introduces a novel online evaluation framework that employs a multi-agent conversational bandit ... | https://ojs.aaai.org/index.php/AAAI/article/view/41064 |
AAAI | 2,026 | A Multi-Agent LLM Framework for Multi-Domain Low-Resource In-Context NER via Knowledge Retrieval, Disambiguation and Reflective Analysis | In-context learning (ICL) with large language models (LLMs) has emerged as a promising paradigm for named entity recognition (NER) in low-resource scenarios. However, existing ICL-based NER methods suffer from three key limitations: (1) reliance on dynamic retrieval of annotated examples, which is problematic when anno... | https://ojs.aaai.org/index.php/AAAI/article/view/40529 |
AAAI | 2,026 | A Multi-Objective Optimization Framework for Adaptive Weighting in Physics-Informed Machine Learning | Training physics-informed neural networks (PINNs) can be viewed as a multi-task optimization problem, where data-driven and physics-driven loss functions must be simultaneously minimized, despite the potential competition between them. Manually tuning the weight coefficients for various loss terms in PINNs is often tim... | https://ojs.aaai.org/index.php/AAAI/article/view/39900 |
AAAI | 2,026 | A Multimodal EEG-Eye Movement Model for Automatic Depression Detection | Depression is a prevalent mental health disorder characterized by persistent sadness and a diminished interest in daily activities, early detection of depression facilitates timely intervention, mitigating its adverse effects. Electroencephalography (EEG) signals and eye movements are emerging as promising biomarkers f... | https://ojs.aaai.org/index.php/AAAI/article/view/37205 |
AAAI | 2,026 | A Natural-Gradient Approach for Nonlinear Stochastic Systems with Parameter Uncertainty | Controlling nonlinear stochastic systems with parametric uncertainty is a fundamental challenge in modern control theory. This paper presents a comprehensive theoretical framework for a natural-gradient method applied to polynomial chaos theory. We focus on quadratic regulator problems characterized by both parametric ... | https://ojs.aaai.org/index.php/AAAI/article/view/38877 |
AAAI | 2,026 | A Network of Biologically Inspired Rectified Spectral Units (ReSUs) Learns Hierarchical Features Without Error Backpropagation | We introduce a biologically inspired, multilayer neural architecture composed of Rectified Spectral Units (ReSUs). Each ReSU projects a recent window of its input history onto a canonical direction obtained via canonical correlation analysis (CCA) of previously observed past–future input pairs, and then rectifies eithe... | https://ojs.aaai.org/index.php/AAAI/article/view/37183 |
AAAI | 2,026 | A Novel Approach to Evaluating Evaluation Metrics for Multi-Output Structured Prediction | In multi-output structured prediction tasks, while only one ground truth label may be provided in the training data, multiple equally valid outputs may be possible, making reliable evaluation a persistent challenge. We postulate that human evaluators implicitly use task-specific invariants, e.g., object boundaries in c... | https://ojs.aaai.org/index.php/AAAI/article/view/39808 |
AAAI | 2,026 | A Novel Fine-Tuned CLIP-OOD Detection Method with Double Loss Constraint Through Optimal Transport Semantic Alignment | Detecting Out-Of-Distribution (OOD) samples in image classification is crucial for model reliability. With the rise of Vision-Language Models (VLMs), CLIP-OOD has become a research hotspot. However, we observe the Low Focus Attention phenomenon from the image encoders of CLIP, which means the attention of image encoder... | https://ojs.aaai.org/index.php/AAAI/article/view/38572 |
AAAI | 2,026 | A Novel Retrieve-Read-Group Paradigm for Open Knowledge Base Canonicalization | Noun phrases (NPs) in open knowledge bases (OKBs) are not canonicalized, leading to scattered knowledge that necessitates the exploration of the OKB canonicalization task (i.e., clustering synonymous noun phrases into the same group and assigning them a unique identifier). However, existing OKB canonicalization methods... | https://ojs.aaai.org/index.php/AAAI/article/view/38644 |
AAAI | 2,026 | A Novel Sliced Fused Gromov-Wasserstein Distance | The Gromov–Wasserstein (GW) distance and its fused extension (FGW) are powerful tools for comparing heterogeneous data. Their computation is, however, challenging since both distances are based on non-convex, quadratic optimal transport (OT) problems. Leveraging 1D OT, a sliced version of GW has been proposed to lower ... | https://ojs.aaai.org/index.php/AAAI/article/view/39669 |
AAAI | 2,026 | A Paradigm Shift in High-Resolution Depth Estimation Using SPAD-Based LiDAR Histograms: From Signal Filtering to Lightweight Similarity Learning | Accurate and efficient depth estimation from time-of-flight (ToF) LiDAR is essential for autonomous systems operating in real-world environments. However, traditional histogram-based depth estimation (HBDE) algorithms face fundamental limitations in balancing depth performance and computational cost, and they struggle ... | https://ojs.aaai.org/index.php/AAAI/article/view/37513 |
AAAI | 2,026 | A Parallel CPU-GPU Framework for Batching Heuristic Operations in Depth-First Heuristic Search | The rapid advancement of GPU technology has unlocked powerful parallel processing capabilities, creating new opportunities to enhance classic search algorithms. This hardware has been exploited in best-first search algorithms with neural network-based heuristics by creating batched versions of A* and Weighted A* that d... | https://ojs.aaai.org/index.php/AAAI/article/view/41019 |
AAAI | 2,026 | A Phase Transition for Opinion Dynamics with Competing Biases | We study the nonlinear evolution of binary opinions in a population of agents connected by a directed network, influenced by two competing forces.
On the one hand agents are stubborn, i.e., have a tendency for one of the two opinions; on the other hand there is a disruptive bias that drives the agents toward the oppos... | https://ojs.aaai.org/index.php/AAAI/article/view/40172 |
AAAI | 2,026 | A Principle-Driven Adaptive Policy for Group Cognitive Stimulation Dialogue for Elderly with Cognitive Impairment | Cognitive impairment is becoming a major public health challenge. Cognitive Stimulation Therapy (CST) is an effective intervention for cognitive impairment, but traditional methods are difficult to scale, and existing digital systems struggle with group dialogues and cognitive stimulation principles. While Large Langua... | https://ojs.aaai.org/index.php/AAAI/article/view/40393 |
AAAI | 2,026 | A Pseudo-Label Optimization Method Based on Polar Coordinate Modeling and Prior Constraints | Magnetic Resonance Imaging (MRI) and its automatic segmentation are pivotal in assisting physicians with clinical diagnosis. In recent years, with the scarcity of labeled data, significant advancements have been made in semi-supervised segmentation. However, the prediction of many current methods is affected by the pre... | https://ojs.aaai.org/index.php/AAAI/article/view/37998 |
AAAI | 2,026 | A Reasoning Paradigm for Named Entity Recognition | Generative LLMs typically improve Named Entity Recognition (NER) performance through instruction tuning. They excel at generating entities by semantic pattern matching but lack an explicit, verifiable reasoning mechanism. This "cognitive shortcutting" leads to suboptimal performance and weak generalization, especially... | https://ojs.aaai.org/index.php/AAAI/article/view/40375 |
AAAI | 2,026 | A Retrieval Augmented Spatio-Temporal Framework for Traffic Prediction | Traffic prediction serves as a cornerstone of modern intelligent transportation systems and the critical task of spatio-temporal forecasting.
Although advanced Spatio-temporal Graph Neural Networks (STGNNs) and pre-trained models have made significant progress in traffic prediction, two critical challenges persist: (i... | https://ojs.aaai.org/index.php/AAAI/article/view/41264 |
AAAI | 2,026 | A Robust Unlearning Method with Adaptive Knowledge Guidance and Memory Preservation | Machine unlearning has emerged as a promising approach to remove specific knowledge from large language models (LLMs), especially for safety-critical applications. However, existing representation-based methods lack guidance for selecting representation locations to unlearn (RMU), thus lacking precision in unlearning, ... | https://ojs.aaai.org/index.php/AAAI/article/view/39017 |
AAAI | 2,026 | A Rolling Stone Gathers No Moss: Adaptive Policy Optimization for Stable Self-Evaluation in Large Multimodal Models | Self-evaluation, a model's ability to assess the correctness of its own output, is crucial for Large Multimodal Models (LMMs) to achieve self-improvement in multi-turn conversations, yet largely absent in foundation models. Recent work has employed reinforcement learning (RL) to enhance self-evaluation; however, its fi... | https://ojs.aaai.org/index.php/AAAI/article/view/40656 |
AAAI | 2,026 | A Scalable and Exact Relaxation for Densest k-Subgraph via Error Bounds | Given an undirected graph and a size parameter k, the Densest k-Subgraph (DkS) problem extracts the subgraph on k vertices with the largest number of induced edges. While DkS is NP--hard and difficult to approximate, penalty-based continuous relaxations of the problem have recently enjoyed practical success for real-wo... | https://ojs.aaai.org/index.php/AAAI/article/view/38562 |
AAAI | 2,026 | A Selective Under-Sampling (SUS) Method for Imbalanced Regression (Abstract Reprint) | Many mainstream machine learning approaches, such as neural networks, are not well suited to work with imbalanced data. Yet, this problem is frequently present in many real-world data sets. Collection methods are imperfect, and often not able to capture enough data in a specific range of the target variable. Furthermor... | https://ojs.aaai.org/index.php/AAAI/article/view/41369 |
AAAI | 2,026 | A Simple Proof-Theoretic Characterization of Stable Models: Reduction to Difference Logic and Experiments (Abstract Reprint) | Stable models of logic programs have been studied and characterized in relation with other formalisms by many researchers. As already argued in previous papers, such characterizations are interesting for diverse reasons, including theoretical investigations and the possibility of leading to new algorithms for computing... | https://ojs.aaai.org/index.php/AAAI/article/view/41380 |
AAAI | 2,026 | A Solution Space Transformation-Guided Co-Evolution for Energy-Saving Distributed Heterogeneous Flexible Job Shop Scheduling | Solving energy-saving distributed heterogeneous flexible job shop scheduling problem (ES-DHFJSP) aims to enhance industrial production efficiency while minimizing energy consumption. State-of-the-art co-evolutionary algorithms have emerged as effective approaches for addressing ES-DHFJSP. However, existing methodologie... | https://ojs.aaai.org/index.php/AAAI/article/view/41033 |
AAAI | 2,026 | A Solver-in-the-Loop Framework for Improving LLMs on Answer Set Programming for Logic Puzzle Solving | The rise of large language models (LLMs) has sparked interest in coding assistants.
While general-purpose programming languages are well supported, generating code for domain-specific languages remains a challenging problem for LLMs.
In this paper, we focus on the LLM-based generation of code for Answer Set Programming... | https://ojs.aaai.org/index.php/AAAI/article/view/39714 |
AAAI | 2,026 | A Stage-Aware Mixture of Experts Framework for Neurodegenerative Disease Progression Modelling | The long-term progression of neurodegenerative diseases is commonly conceptualized as a spatiotemporal diffusion process that consists of a graph diffusion process across the structural brain connectome and a localized reaction process within brain regions. However, modeling this progression remains challenging due to ... | https://ojs.aaai.org/index.php/AAAI/article/view/39316 |
AAAI | 2,026 | A Study of Finetuning Video Transformers for Multi-view Geometry Tasks | This paper presents an investigation of vision transformer learning for multi-view geometry tasks, such as optical flow estimation, by fine-tuning video foundation models. Unlike previous methods that involve custom architectural designs and task-specific pretraining, our research finds that general-purpose models pret... | https://ojs.aaai.org/index.php/AAAI/article/view/38038 |
AAAI | 2,026 | A Switching Framework for Online Interval Scheduling with Predictions | We study online interval scheduling in the irrevocable setting, where each interval must be immediately accepted or rejected upon arrival. The objective is to maximize the total length of accepted intervals while ensuring that no two accepted intervals overlap. We consider this problem in a learning-augmented setting, ... | https://ojs.aaai.org/index.php/AAAI/article/view/40930 |
AAAI | 2,026 | A TSP-Based Algorithm for Multi-League Traveling Tournament | In some professional sports leagues, inter-league games are scheduled among multiple divisions or conferences. This inspired us to study the p-partite Traveling Tournament Problem (p-partite TTP), where teams are partitioned into p leagues, and each team plays games against teams from different leagues. Previously, onl... | https://ojs.aaai.org/index.php/AAAI/article/view/40977 |
AAAI | 2,026 | A Tale of Two Identities: An Ethical Audit of AI-Crafted Synthetic Personas | As LLMs (large language models) are increasingly used to generate synthetic personas, particularly in data-limited domains such as health, privacy, and HCI, it becomes necessary to understand how these narratives represent identity, especially that of minority communities. In this paper, we audit synthetic personas gen... | https://ojs.aaai.org/index.php/AAAI/article/view/41112 |
AAAI | 2,026 | A Text-Routed Sparse Mixture-of-Experts Model with Explanation and Temporal Alignment for Multi-Modal Sentiment Analysis | Human-interaction-involved applications underscore the need for Multi-modal Sentiment Analysis (MSA). Although many approaches have been proposed to address the subtle emotions in different modalities, the power of explanations and temporal alignments is still underexplored. Thus, this paper proposes the Text-routed sp... | https://ojs.aaai.org/index.php/AAAI/article/view/40559 |
AAAI | 2,026 | A Theoretical Analysis of Detecting Large Model-Generated Time Series | Motivated by the increasing risks of data misuse and fabrication, we investigate
the problem of identifying synthetic time series generated by Time-Series Large
Models (TSLMs) in this work.
While there are extensive researches on detecting model generated text, we find
that these existing methods are not applicable to ... | https://ojs.aaai.org/index.php/AAAI/article/view/39330 |
AAAI | 2,026 | A Theoretical Model for Grit in Pursuing Ambitious Ends | Ambition and risk-taking have been heralded as important ways for marginalized communities to get out of cycles of poverty. As a result, educational messaging often encourages individuals to strengthen their personal resolve and develop characteristics such as discipline and grit to succeed in ambitious ends. However, ... | https://ojs.aaai.org/index.php/AAAI/article/view/41166 |
AAAI | 2,026 | A Theory of Adaptive Scaffolding for LLM-Based Pedagogical Agents | Large language models (LLMs) present new opportunities for creating pedagogical agents that engage in meaningful dialogue to support student learning. However, current LLM systems used in classrooms often lack the solid theoretical foundations found in earlier intelligent tutoring systems. To bridge this gap, we propos... | https://ojs.aaai.org/index.php/AAAI/article/view/37154 |
AAAI | 2,026 | A Theory-Inspired Framework for Few-Shot Cross-Modal Sketch Person Re-Identification | Sketch-based person re-identification aims to match hand-drawn sketches with RGB surveillance images, but remains challenging due to severe modality gaps and limited labeled data. To address this, we propose KTCAA, a theoretically inspired framework for few-shot cross-modal generalization. Drawing on generalization bou... | https://ojs.aaai.org/index.php/AAAI/article/view/42425 |
AAAI | 2,026 | A Topological Rewriting of Tarski’s Mereogeometry | Qualitative spatial representation approaches which rely on Goodman-style predicative mereological theories and on a pseudo-topology, often causes some problems either for their use as a meta-information for knowledge conceptualization in advanced geometric reasoning, since they lack Euclidean geometry and fully-fledge... | https://ojs.aaai.org/index.php/AAAI/article/view/38976 |
AAAI | 2,026 | A Unified Convergence Analysis for Semi-Decentralized Learning: Sampled-to-Sampled vs. Sampled-to-All Communication | In semi-decentralized federated learning, devices primarily rely on device-to-device communication but occasionally interact with a central server. Periodically, a sampled subset of devices uploads their local models to the server, which computes an aggregate model. The server can then either (i) share this aggregate m... | https://ojs.aaai.org/index.php/AAAI/article/view/39705 |
AAAI | 2,026 | A Unified Geospatial Clustering Framework to Identify Varying Density Clusters in E-Commerce Logistics | In e-commerce logistics, accurate geospatial clustering is essential for optimizing resource allocation, manpower planning, and delivery network design. However, existing density-based clustering approaches, particularly their reliance on heuristic parameter tuning, have been underexplored in datasets with significant ... | https://ojs.aaai.org/index.php/AAAI/article/view/41488 |
AAAI | 2,026 | A Unified Self-Regulating Training Framework for Federated Deep Reinforcement Learning | Federated Deep Reinforcement Learning (FDRL) aims to enable distributed collaborative training of multiple DRL models while preserving privacy. Existing FDRL methods function in static client environments, but real-world scenarios often involve dynamic state transitions, such as noise, which render static model topolog... | https://ojs.aaai.org/index.php/AAAI/article/view/39946 |
AAAI | 2,026 | A Unified Shape-Aware Foundation Model for Time Series Classification | Foundation models pre-trained on large-scale source datasets are reshaping the traditional training paradigm for time series classification. However, existing time series foundation models primarily focus on forecasting tasks and often overlook classification-specific challenges, such as modeling interpretable shapelet... | https://ojs.aaai.org/index.php/AAAI/article/view/39574 |
AAAI | 2,026 | A Visualized Framework for Event Cooperation with Generative Agents | Large Language Models (LLMs) have revolutionized the simulation of agent societies, enabling autonomous planning, memory formation, and social interactions. However, existing frameworks often overlook systematic evaluations for event organization and lack visualized integration with physically grounded environments, li... | https://ojs.aaai.org/index.php/AAAI/article/view/42386 |
AAAI | 2,026 | A-FloPS: Accelerating Diffusion Models via Adaptive Flow Path Sampler | Diffusion models deliver state-of-the-art generative performance across diverse modalities but remain computationally expensive due to their inherently iterative sampling process. Existing training-free acceleration methods typically improve numerical solvers for the reverse-time ODE, yet their effectiveness is fundame... | https://ojs.aaai.org/index.php/AAAI/article/view/39397 |
AAAI | 2,026 | A3D: Adaptive Affordance Assembly with Dual-Arm Manipulation | Furniture assembly is a crucial yet challenging task for robots, requiring precise dual-arm coordination where one arm manipulates parts while the other provides collaborative support and stabilization.
To accomplish this task more effectively, robots need to actively adapt support strategies throughout the long-horiz... | https://ojs.aaai.org/index.php/AAAI/article/view/38907 |
AAAI | 2,026 | ACID Test: A Benchmark for Cultural Safety and Alignment in LALMs | Large Audio Language Models (LALMs) are transforming AI by processing and generating human language directly from audio. As these models proliferate in real-world applications, it becomes critical to evaluate their performance to ensure equitable and safe use across diverse linguistic and cultural contexts. We present ... | https://ojs.aaai.org/index.php/AAAI/article/view/41068 |
AAAI | 2,026 | ACID-Style: An Adaptive Condition Injection Diffusion Model for Arbitrary Style Transfer | Arbitrary style transfer (AST), a popular AI-powered photo editing function, aims to strike an optimal balance between content and style injection from two images in order to generate a novel high-fidelity stylised image. Recently, diffusion models have been applied to AST due to their high generation quality as well a... | https://ojs.aaai.org/index.php/AAAI/article/view/38158 |
AAAI | 2,026 | AD-FM: Multimodal LLMs for Anomaly Detection via Multi-Stage Reasoning and Fine-Grained Reward Optimization | While Multimodal Large Language Models (MLLMs) demonstrate remarkable capabilities across diverse domains, their application to specialized anomaly detection (AD) remains constrained by domain adaptation challenges. Existing Group Relative Policy Optimization (GRPO) based approaches suffer from two critical limitations... | https://ojs.aaai.org/index.php/AAAI/article/view/38548 |
AAAI | 2,026 | ADAPT: Adaptive Decentralized Architecture with Perception-Aligned Training for Structural Generalization in Multi-Agent RL | Multi-agent reinforcement learning (MARL) excels in cooperative and competitive tasks, but most architectures are tied to fixed input-output sizes and require retraining when the number of perceptible or controllable objects changes. While structural generalization techniques mitigate this, they rely on centralized tra... | https://ojs.aaai.org/index.php/AAAI/article/view/40096 |
End of preview. Expand in Data Studio
AI Conference & Journal Papers
Searchable metadata for papers from top AI venues (NeurIPS, ICML, ICLR, CVPR, ICCV, WACV, ACL, EMNLP, NAACL).
papers.parquet: the full dataset (all fields, all venues).- Per-venue browse views: pick a venue in Subset, a year in Split.
Dataset Structure
ClosedUni/papercli-papers(main entrypoint): Contains the full index metadata parquet (papers.parquet) and the per-venue browse parquet views (browse/).ClosedUni/papercli-papers-[venue]: Contains the sharded PDF files of that specific venue (no metadata parquet).
PDF Storage
PDF files are sharded across separate datasets by venue to keep repository sizes optimal:
ClosedUni/papercli-papers-[venue](e.g.ClosedUni/papercli-papers-cvprfor CVPR PDFs)
To download a mirrored PDF:
from huggingface_hub import hf_hub_download
repo_id = f"ClosedUni/papercli-papers-{row['venue'].lower()}"
path = hf_hub_download(
repo_id=repo_id,
filename=row["hf_pdf_path"],
repo_type="dataset",
)
Built with papercli.
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