AI news archive.
10,659 articles filed under Research, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchReward-Guided RRT* for Budgeted Task and Motion Planning
arXiv:2610.35289v1 Announce Type: cross Abstract: Robotic missions involving spatially distributed tasks often require jointly selecting rewarding locations and planning feasible motions under limited travel budgets. Thi…
- arXiv cs.AIresearchDid the Model Use That? Counterfactual Training Boosts Self-Attribution in Language Models
arXiv:2610.35295v1 Announce Type: cross Abstract: A fundamental challenge for explainable and accountable language models is revealing how external information influences their answers. This paper examines whether models…
- arXiv cs.AIresearchConstrained Decoding: Harmful or Beneficial? Revisiting Its Impact on LLM Performance
arXiv:2610.35328v1 Announce Type: cross Abstract: Constrained decoding guarantees that Large Language Models (LLMs) produce outputs conforming to predefined formats, but is often assumed to inherently degrade reasoning.…
- arXiv cs.AIresearchGeometric Consistency Based Label-Free Validation for Checkpoint Selection in Audio Active Learning
arXiv:2610.35329v1 Announce Type: cross Abstract: Audio active learning (AL) trains a classifier at low annotation cost by labeling only an informative fraction of an unlabeled collection over successive rounds. Each rou…
- arXiv cs.AIresearchShould Pseudo-Labels Share Mini-Batches with Labeled Examples? Semi-Supervised Continual Active Learning with Limited Training Cost
arXiv:2610.35345v1 Announce Type: cross Abstract: Active learning (AL) reduces annotation by querying informative examples. Continual active learning (CAL) also cuts the training cost, the total number of gradient steps,…
- arXiv cs.AIresearchShared-Factor-Conditioned Diffusion for Low-Rank Tensor Recovery
arXiv:2610.35368v1 Announce Type: cross Abstract: Tensor recovery spans heterogeneous data structures and observation processes, calling for a representation that can adapt across modalities and tasks. We propose DiffTR,…
- arXiv cs.AIresearchACSAN: All-Convolutional Self-Attention Network Integrating Convolutional Operations with Vision Transformer
arXiv:2610.35375v1 Announce Type: cross Abstract: In the past few years, Vision Transformer (ViT) has achieved excellent performance in the field of computer vision. However, there still some problems remain. For instanc…
- arXiv cs.AIresearchAn Interactive Evolutionary Multiobjective Optimization Algorithm Based on Interpretable Active Preference Learning
arXiv:2610.35470v1 Announce Type: cross Abstract: Many decision-making tasks are inherently multi-objective. Interactive evolutionary multi-objective optimization algorithms (iEMOAs) are particularly well-suited to help…
- arXiv cs.AIresearchBeyond Words Alone: Disentangling Distributed Evidence for Visually Grounded Cultural Translation
arXiv:2610.35482v1 Announce Type: cross Abstract: Social media enables cross-lingual communication, yet the meaning of user-generated content (UGC) is often distributed across text, images, and cultural knowledge, making…
- arXiv cs.AIresearchGoverning Enterprise AI Traffic at Scale: Design and Operation of a Policy-Driven, Multi-Vendor LLM Gateway on Envoy
arXiv:2610.35509v1 Announce Type: cross Abstract: Large organizations consume large language models (LLMs) from several vendors at once, each with its own API dialect, credential model, streaming protocol and pricing. In…
- arXiv cs.AIresearchGenerative Structure from Motion with Native 3D Diffusion
arXiv:2610.35522v1 Announce Type: cross Abstract: Recovering an object's 3D structure and camera motion from a few uncalibrated views is a fundamental problem in computer vision. Classical structure from motion methods r…
- arXiv cs.AIresearchRanking Function Generation with LLMs for Termination
arXiv:2610.35523v1 Announce Type: cross Abstract: Ranking functions are a fundamental technique for proving loop termination, but constructing them manually is challenging and requires substantial expertise. We propose R…
- arXiv cs.AIresearchJANUS: Synthesizing Cross-Layer Defenses Against Web Deserialization Attacks
arXiv:2610.35532v2 Announce Type: replace-cross Abstract: Unsafe deserialization turns untrusted data into attacker-controlled execution, and a single vulnerability can admit diverse exploit variants that evade defenses…
- arXiv cs.AIresearchCross-Domain Sequential Recommendation with Representation-Level User Transfer
arXiv:2610.35550v1 Announce Type: cross Abstract: Cross-domain sequential recommendation aims to improve next-item prediction in a target domain by leveraging user behavior from auxiliary source domains. However, real-wo…
- arXiv cs.AIresearchMulti-Fidelity Training Reshapes Uncertainty Decomposition in Atomistic Models
arXiv:2610.35560v2 Announce Type: replace-cross Abstract: Multi-fidelity training, which combines abundant low-fidelity data with scarce high-fidelity labels, is increasingly common in atomistic modeling, but its effect…
- arXiv cs.AIresearchExCal: Optimization-Free Multivariate Time Series Anomaly Detection via Excess Calibration
arXiv:2610.35568v1 Announce Type: cross Abstract: We introduce ExCal, a normal-only multivariate time series anomaly detector that combines raw state retrieval, a signal/derivative subspace, and robust statistics across…
- arXiv cs.AIresearchMaking Reasoning Visible: Configuration-Aware Diagnostic Modeling for Adaptive Scaffolding in Structured Reasoning Tasks
arXiv:2610.35609v1 Announce Type: cross Abstract: Modeling the latent, multi-step reasoning processes of learners is a core challenge for adaptive tutoring systems, which often rely on simple right/wrong answers rather t…
- arXiv cs.AIresearchAdapt for Planning, Not just Prediction: Optimistic Test-Time World Model Adaptation
arXiv:2610.35636v1 Announce Type: cross Abstract: Latent world models are typically pre-trained offline and kept frozen at test time, so planning with them can degrade under distribution shift. Test-time adaptation (TTA)…
- arXiv cs.AIresearchProvably Efficient Q-learning for Robust Reinforcement Learning
arXiv:2610.35656v1 Announce Type: cross Abstract: Standard reinforcement learning (RL) algorithms based on Markov Decision Processes (MDPs) are vulnerable to sim-to-real gaps. To address this issue, distributionally robu…
- arXiv cs.AIresearchCounterFlow: Target-Conditioned Flow Matching for Visual Counterfactuals
arXiv:2610.35679v1 Announce Type: cross Abstract: In eXplainable AI, counterfactual explanations have gained significant traction by offering users direct, intuitive, and actionable insights into model decisions. We intr…
- arXiv cs.AIresearchOmniShowcase: Omnidirectional Subject-Consistent Video Generation from Multi-View Images
arXiv:2610.35684v1 Announce Type: cross Abstract: Generating videos of a specific subject from a few reference images remains challenging when the camera reveals surfaces that are not visible in the input. Early subject-…
- arXiv cs.AIresearchAdapting LLM-SC to Living Sacred Heritage: Domain-Specific Extraction, Semantic Networks and Human Evaluation on Pashupatinath Temple Reviews
arXiv:2610.35685v2 Announce Type: replace-cross Abstract: Large language model (LLM) pipelines can turn visitor reviews into structured data, but generic schemes may miss rituals, sacred spaces, cultural restrictions and…
- arXiv cs.AIresearchTrySee: Modular Perception-Enhanced VLM Grounding for Closed-Loop Robot Task Planning in Specialized Domains
arXiv:2610.35687v1 Announce Type: cross Abstract: Vision Language Models (VLMs) have shown impressive capabilities in high-level reasoning and task planning for robots. However, specialized domains remain a challenge for…
- arXiv cs.AIresearchTowards a Unified Framework of Optimal Input-Side Dimensional Configuration for Deep CTR Prediction
arXiv:2610.35695v1 Announce Type: cross Abstract: Deep click-through rate (CTR) prediction has achieved substantial success through increasingly expressive feature interaction architectures. However, predictive performan…
- arXiv cs.AIresearchQuantitative Generalization Bounds for Multi-Layer Transformers: A Few Long Strings can Beat Many Short Ones
arXiv:2610.35715v2 Announce Type: replace-cross Abstract: Transformer-based language models exhibit an astonishing capacity to generalize to longer and more difficult problem instances than those seen in training. Howeve…
- arXiv cs.AIresearchAudit Where Hacks Pay: Budgeted Strong-Verifier Audits Against Reward Hacking in GRPO
arXiv:2610.35716v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards trains on cheap checks, such as unit tests, that a policy can learn to game, while a stronger check is too expensive to run…
- arXiv cs.AIresearchCan JEV Support Clinical Trial Criteria Assessment?
arXiv:2610.35721v1 Announce Type: cross Abstract: Clinical trial prescreening requires distinguishing unmet conditions from insufficient evidence in patient records. Given patient records, criterion questions, and predef…
- arXiv cs.AIresearchThe Watchtower Imperative: Lifespan-Calibrated Evaluation for Frontier AI
arXiv:2610.35725v1 Announce Type: cross Abstract: The gap between AI capability deployment and safety assurance is structural and cannot be closed through internal evaluations alone. Analyzing documented harms (2017-2026…
- arXiv cs.AIresearchMulti-Objective Reinforcement Learning Using Routed Ensembles and Trajectory Attribution
arXiv:2610.35733v1 Announce Type: cross Abstract: Multi-objective reinforcement learning is a fundamental problem for modern AI, with applications spanning post-training, reasoning models, and robotic control. A central…
- arXiv cs.AIresearchEEGaze: Multimodal Attention Prediction in Visual Search via EEG-Based Saliency Refinement
arXiv:2610.35757v1 Announce Type: cross Abstract: Visual search is ubiquitous in daily life, from locating keys in a messy apartment to finding a tool in a cluttered workshop or an application icon on a desktop screen. W…
- arXiv cs.AIresearchDo Similarity Measures Measure Similarity? How User Activity Creates Phantom Correlation in Recommender Systems
arXiv:2610.35765v1 Announce Type: cross Abstract: Item-item similarity is one of the oldest and most foundational signals in recommender systems: two items are assumed to be similar when the same users consume them. Desp…
- arXiv cs.AIresearchLearning When to Commit: Schedule Distillation for Fast Diffusion Language Models
arXiv:2610.35804v1 Announce Type: cross Abstract: Diffusion large language models (dLLMs) can generate multiple tokens in parallel, but often require many decoding rounds to complete a response. Efficient generation depe…
- arXiv cs.AIresearchLearning Force-Reactive Humanoid Loco-Manipulation
arXiv:2610.35862v1 Announce Type: cross Abstract: Many everyday tasks require controlling contact force as well as motion. On a humanoid, this force must often be coordinated across both hands and the whole body, and can…
- arXiv cs.AIresearchEvaluating Harmful Memorization in LLM Code Generation
arXiv:2503.02296v3 Announce Type: replace Abstract: Assessing memorization in LLM code generation is challenging because code reuse is not inherently harmful. Correct programs often share APIs, templates, and algorithmic…
- arXiv cs.AIresearchExploring the Limits of Large Language Models as a Reflection of Human Cognition: An Illustration in the Context of Moral Judgement
arXiv:2508.06950v4 Announce Type: replace Abstract: Large Language Models (LLMs), such as ChatGPT, are increasingly used in research, ranging from simple writing assistance to complex data annotation tasks. Recently, som…
- arXiv cs.AIresearchHealth-SCORE: Towards Scalable Rubrics for Improving Health-LLMs
arXiv:2601.18706v2 Announce Type: replace Abstract: Rubrics are essential for evaluating open-ended LLM responses, especially in safety-critical domains such as healthcare. However, creating high-quality and domain-speci…
- arXiv cs.AIresearchDo MLLMs Really See It: Reinforcing Visual Attention in Multimodal LLMs
arXiv:2602.08241v2 Announce Type: replace Abstract: While chain-of-thought (CoT) reasoning has substantially improved multimodal large language models (MLLMs) on complex reasoning tasks, existing approaches largely rely…
- arXiv cs.AIresearchBeyond 0-100: How Confidence Scale Design Shapes Verbalized Confidence and LLM Metacognition
arXiv:2603.09309v4 Announce Type: replace Abstract: Verbalized confidence, in which LLMs report a numerical certainty score, is widely used to estimate uncertainty in black-box settings, yet the confidence scale itself (…
- arXiv cs.AIresearchGPT4o-Receipt: A Dataset and Human Study for AI-Generated Document Forensics
arXiv:2603.11442v3 Announce Type: replace Abstract: Can humans detect AI-generated financial documents better than machines? We present GPT4o-Receipt, a benchmark of 1,235 receipt images pairing GPT-4o-generated receipts…
- arXiv cs.AIresearchEpiPersona: Persona Projection and Episode Coupling for Pluralistic Preference Modeling
arXiv:2603.28197v2 Announce Type: replace Abstract: Pluralistic alignment is essential for adapting large language models (LLMs) to the diverse preferences of individuals and minority groups. However, existing personaliz…
- arXiv cs.AIresearchAlphaCNOT: Learning CNOT Minimization with Model-Based Planning
arXiv:2604.13812v2 Announce Type: replace Abstract: Quantum circuit optimization is a central task in quantum computing, as current NISQ devices suffer from error propagation that often scales with the number of operatio…
- arXiv cs.AIresearchA systematic evaluation of vision-language models for observational astronomical reasoning tasks
arXiv:2604.24589v2 Announce Type: replace Abstract: Vision-language models (VLMs) are increasingly proposed as general-purpose tools for scientific data interpretation, yet their reliability on real astronomical observat…
- arXiv cs.AIresearchPREFER: Personalized Review Summarization with Online Preference Learning
arXiv:2605.05911v2 Announce Type: replace Abstract: Product reviews significantly influence purchasing decisions on e-commerce platforms. However, the sheer volume of reviews can overwhelm users, obscuring information mo…
- arXiv cs.AIresearchFrom Pixels to Prompts: Vision-Language Models
arXiv:2605.07544v4 Announce Type: replace Abstract: When you read a paper about a new Vision-Language Model today, it can be easy to forget how strange this idea would have sounded not so long ago. Teaching machines to s…
- arXiv cs.AIresearchDiagnosticIQ: A Benchmark for LLM-Based Industrial Maintenance Action Recommendation from Symbolic Rules
arXiv:2605.08614v2 Announce Type: replace Abstract: Monitoring complex industrial assets relies on engineer-authored symbolic rules that trigger on sensor conditions and prompt technicians to perform corrective actions.…
- arXiv cs.AIresearchLearning Scenario Reduction for Two-Stage Robust Optimization with Discrete Uncertainty
arXiv:2605.14494v2 Announce Type: replace Abstract: Two-Stage Robust Optimization (2RO) with discrete uncertainty is challenging, often rendering exact solutions prohibitive. Scenario reduction alleviates this issue by s…
- arXiv cs.AIresearchNGM: A Plug-and-Play Training-Free Memory Module for LLMs
arXiv:2605.16893v2 Announce Type: replace Abstract: Recent studies have introduced memory-augmented architectures that decouple knowledge storage from neural computation, enabling more direct access to stored representat…
- arXiv cs.AIresearchMeasuring Cross-Modal Synergy: A Benchmark for VLM Explainability
arXiv:2605.22168v2 Announce Type: replace Abstract: Vision-Language Models (VLMs) map complex visual inputs to semantic spaces, but interpreting the cross-modal reasoning of VLMs currently relies on post-hoc explainers e…
- arXiv cs.AIresearchICCU: In-Context Continual Unlearning via Pattern-Induced Refusal Rules
arXiv:2605.27138v2 Announce Type: replace Abstract: Machine unlearning aims to remove the influence of specific data from trained language models. In real-world deployments, unlearning requests often arrive sequentially,…
- arXiv cs.AIresearchRhythm of the Deep: Two-tier acoustic organization of sperm-whale codas from click waveforms to coda sequences
arXiv:2606.16084v4 Announce Type: replace Abstract: Sperm-whale codas are usually described by the number and timing of their clicks. These measures have revealed patterns in whale communication, but leave open how click…