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Artificial Intelligence
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The newest 5,000 papers, from 11 October 2026 to 5 November 2026: 4,998 arXiv preprints and 2 OpenAlex records.
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Newest papers, page 181
Selm: Self-Evolving Library Management for Multi-Skill Agent Optimization
Large language model (LLM) agents increasingly use skills as a lightweight way to acquire task-specific knowledge.Frequency-Domain Membership Inference Does Not Beat Confidence Thresholding: A Band-Resolved Analysis of Why
A widely repeated account of membership inference holds that models lean on fine-grained detail for samples they have memorized, so degrading an input's resolution should expose membership through…Good Judgment, Bad Advice: Decision-Model Controllers Raise Agent Cost Without Improving Success
Agent scaffolds increasingly delegate small decisions (whether to stop, verify, or change approach) to cheaper models.Can AI agents make law? Evaluating AI legal relevance and creativity
Large language models, the artificial intelligence (AI) systems behind modern chatbots, are trained on vast amounts of legal text, but can they build on it to write law for situations that text…From Prediction to Action: Population Health World Model for Digital Medicine
Digital medicine now captures data that traces individual health trajectories and reveals population health dynamics through electronic health records, claims, remote monitoring, wearable devices…MM-LeJEPA: Correlated Gaussian Regularization for Multimodal Joint-Embedding Predictive Architectures
LeJEPA derives an isotropic Gaussian embedding target by minimizing, under its task assumptions, a Fisher information criterion that controls the task-averaged squared prediction bias.Contrastive Adversarial Training for Robust Graph Neural Networks under Label Poisoning
Graph Neural Networks (GNNs) are effective for modeling relational data but are vulnerable to label poisoning, where a small number of corrupted training labels can propagate errors across the graph…Verifying Human-Written Reasoning References
Evaluating the reasoning of AI systems often relies on human-written reasoning chains as references, yet the logical support for their individual steps is rarely verified.Spherical Physics-informed Neural Operator with Multi-scale Coupling for Meteorological Downscaling
Meteorological downscaling is crucial for high-resolution regional climate forecasting and disaster early warning.SQuIREL: A Context-Relative Framework for Measuring Entity Richness in Wikidata
Wikidata is a large, heterogeneous knowledge graph and applying data quality metrics requires context-specific approaches.DiffuPlan: Editable Planning State for Diffusion Language Model Agents
Diffusion language models (dLLMs) are emerging as an alternative to autoregressive (AR) language models, yet dLLM agents largely inherit an interaction protocol designed for AR generation: once…Neuro-Inspired Inhibitory Message Passing for Accurate and Token-Efficient Multi-Agent Reasoning
Multi-agent systems promise to solve problems by bringing together information beyond the reach of any individual agent.Tensor Network Datamodels for Training Data Attribution
Datamodels predict how a model's behavior changes when different parts of its training data are included or removed.Where Natural Language Ends in Agents: Executable Skill Composition with MetaSkill
Agent Skills express open-ended task knowledge in natural language, but composing them requires persistent execution order and upstream-output handoffs.GLOSS-MT: Controllable Low-Resource Machine Translation with an Editable Dictionary
Adapting a pretrained machine translation (MT) model to new terminology usually requires new parallel data and another round of fine-tuning, which is costly for low-resource languages.Can LLM Agents Resolve Service Failures? Simulating Multi-Turn Complaint Handling under Information Asymmetry
LLM agents are widely adopted in service chatbots for rule-guided support and information access, yet emotionally demanding complaint handling still relies heavily on human agents.Toward Collective Model Intelligence: Characterizing and Coordinating Models
Independently developed AI models accumulate diverse and complementary capabilities, but a growing model collection does not automatically realize Collective AI.Are We Evaluating VLM Token Pruning Right? Looking Beyond Accuracy and Token Count
Visual token pruning aims to reduce inference cost while preserving the capabilities of the original VLM.ReTRACE: Feedback-Guided LLM Agent in a Chemistry Harness for Retrosynthesis Planning
Computer-aided retrosynthesis has advanced through single-step prediction, tree search and route scoring, but complex targets still require judgement over the whole route, where stereochemistry…CorrFlow: Self-Correcting Flow Matching
Flow-matching models generate samples through iterative velocity predictions, but typically do not revisit these predictions using the intermediate representations that produced them.