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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 143
MoEZip: Routing-Aware KV Cache Compression for Sparse Mixture-of-Experts LLMs
Mixture-of-Experts (MoE) language models scale model capacity efficiently by activating a small subset of parameters per token.Prediction Is Not Calibration: Item Parameter Recovery and Representation Coupling in Knowledge Tracing
Knowledge tracing (KT) models can estimate item parameters through an item response decoder trained solely for next-response prediction, yet predictive accuracy does not guarantee parameter recovery.When Reconstruction Is Not Enough: Doubly Robust Counterfactual and Interventional Mediation Analysis with Learned Multimodal Representations
Learned representations of high-dimensional multimodal health records are increasingly used to adjust for confounding, yet they are usually trained to reconstruct the data rather than preserve the…Automated screening of privacy risks in medical AI
Medical artificial intelligence (AI) models are often shared without their training data, assuming this protects the patients who contributed them.Edit, Don't Imitate: Minimal-Edit On-Policy Distillation for Multimodal Reasoning
Visual mathematical reasoning can fail before reasoning begins: when a vision-language model (VLM) misreads a diagram, subsequent reasoning proceeds from false premises.Breaking the high-degree barrier in Lehmer's problem with a human-AI discovery loop
While artificial intelligence has made rapid progress in mathematical reasoning, many open problems depend on structure that is revealed only through large-scale computational exploration and…Astro2Method: Benchmarking LLMs on Machine Learning Method Selection in Astronomy
Machine learning (ML) is increasingly used in astronomy, but choosing a suitable method for a scientific problem often requires expertise in both astronomy and ML.SWE-VERIFIER: Selective Verification for Cost-Efficient Coding Agents
Coding agents spend substantial computation generating actions and processing long interaction histories.Generalizing Metropolis-Hastings for DAG Sampling
A fundamental challenge in Bayesian network structure learning lies in efficiently approximating the posterior distribution of directed acyclic graphs (DAGs).GAV: A scientific experimentation environment for PDE agents
Reliable feedback is essential for coding agents to develop programs for partial differential equations (PDEs).Gender, Sexual Orientation, and the One-Year Refugee Bar: A Computational Study of Bill C-12 and Canadian Refugee Adjudication
In March 2026, Bill C-12 amended the Immigration and Refugee Protection Act to make refugee claims ineligible for referral to the Refugee Protection Division where they are made more than one year…TerraTransfer++: Demonstration-Free End-to-End Planner
End-to-end autonomous driving has achieved state-of-the-art performance on benchmarks and real-world deployments.MPBRS: Multi-Potential-Based Reward Shaping for Unified Reward Configuration in Humanoid Locomotion
Designing and tuning reward functions remains one of the main challenges in building effective reinforcement learning (RL) pipelines for humanoid locomotion.Consistency Is Not Validity: Self-Rewarded Moral Argumentation Makes Language Models Decisive but Pliable
LLMs are increasingly consulted for moral judgment.Route-and-Generate: KL-Regularized Router Improvement for Reasoning Routing in LLMs
Large language models often apply complex reasoning indiscriminately, leading to overthinking on simple tasks and underthinking on harder ones.Probing and Steering for Safety-Relevant Behaviours in Large Language Models
Activation probes are computed directions in a language model's residual stream, used both to detect safety-relevant behaviours and, by adding their direction back into the stream, to steer them.MemPlan: Memory-Conditioned PDDL Planning for Partially Observable Text Environments
LLM agents are flexible in language interaction, but using them as long-horizon planners is costly and prone to hallucinated or invalid actions.Soft Ontology Priors over Latent Concept Posteriors for Weakly Supervised Neuro-Symbolic Learning
Neuro-symbolic (NeSy) predictors that supervise only the task label suffer from reasoning shortcuts: distinct concept mappings achieve the same maximum likelihood, leaving the recovered concepts…AcoustiPrint: Physics-Guided Neural Design of Manufacturable Acoustic Structures
Recent work in additive manufacturing and neural inverse design enables the creation of complex three-dimensional structures to manipulate physical fields, yet these designs must also adhere to…Agent Mosaic: Recognizing Confidentiality Leaks in Agentic LLM Systems
Modern LLM agents can retrieve information from accessible documents, and then disclose a sensitive conclusion assembled from them.