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Artificial Intelligence
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The newest 5,000 papers, from 12 October 2026 to 6 November 2026: 4,992 arXiv preprints and 8 OpenAlex records.
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Newest papers, page 233
LatentRiskBench: Measuring State-Dependent Risks in Enterprise Agents
Enterprise agents face safety risks that cannot be determined from individual actions alone.Stable Token-level Scheduling for Serverless LLM Inference
Serverless inference is emerging as an efficient deployment model for Large Language Models (LLMs) due to its ability to elastically scale resources, improve GPU utilization through resource…MedEvo: Medical Reasoning Evolution through Knowledge Navigation
Medical multimodal reasoning models are typically trained on teacher-generated rationales, discarding the valid reasoning in students' own failed trajectories, while general-domain correction…HelpMeOut: A Neuropsychology-Grounded Benchmark for Error-Aware Monitoring of Household Task Execution
We introduce HelpMeOut, an embodied AI benchmark for error-aware monitoring of household task execution.zPocket: Better Pocket Finding with Frozen Co-Folding Features
Identifying protein-ligand binding sites (pockets) is important for understanding protein function and developing drugs.LeanPRM: Lean-Grounded Process Supervision for Natural Language Proof Verification
AI systems now write long and difficult mathematical proofs, and checking their step-by-step validity is becoming a bottleneck.Understanding Gene Expression-to-Image Learning: Spatial Structure and Information Fidelity
Single-cell RNA sequencing (scRNA-seq) enables cell-level analysis of biological heterogeneity, but learning effective representations from high-dimensional, unordered gene expression profiles…A Node Embedding Framework for Model-Centric Conformance Checking in Process Mining
Evaluating the quality of process models discovered from event logs is a fundamental challenge in process mining.From Token Correction to Claim Admission: Training-Free Hallucination Mitigation for Large Vision-Language Models
Large vision-language models often exhibit object hallucination, generating claims that are not supported by the input image.Where Small Mistakes Matter: Quantifying State Criticality for Imitation Learning
Imitation learning typically treats every demonstration state as equally important, optimizing a behavior-cloning objective uniformly across the dataset.Adaptive-Group Process Rewards for GUI Agents
Training graphical user interface (GUI) agents with reinforcement learning suffers from sparse outcome rewards, leading to inefficient learning.ECG-RSI: Recursive Self-Improvement through Targeted Electrocardiogram Waveform Evolution
Electrocardiogram (ECG) models need supervision that targets evolving weaknesses and remains faithful to waveform evidence.Keep Your Receipts: Trustworthy Cleanup of Agent-Built Knowledge Graphs
Agents build knowledge graphs as memory, and building them has become easy.Upstream Influence, Downstream Re-Anchoring in LLM Agent Chains
People act on evaluative judgments produced by LLM agents, and in multi-agent systems those judgments pass through several agents before reaching a person.Evidence-First Agentic Verification
Long-horizon, semi-verifiable agentic tasks often rely on rubric-based evaluation, but the evidence needed to assess these tasks can be spread across the environment state and the execution trace.TSRL: Trigger-based Supervised Reinforcement Learning for Continual Agent Training
Large language model (LLM) agents excel at complex, multi-step tasks but suffer from catastrophic forgetting during continual learning--acquiring new skills often degrades previously mastered…SkillScreen: High-Recall Screening of Malicious Agent Skills with Decision Models
Agent skills turn natural-language instructions into actions, creating a security challenge: legitimate automation and malicious behaviour can look deceptively similar.Safety for Whom? Benchmarking Understanding Beyond Refusal in Egocentric Multimodal Assistants
Egocentric multimodal assistants see through the user's eyes and guide what the user does next, so their outputs directly shape physical actions, including those that affect bystanders.CoCA: Criterion-Aware Credit Assignment for Rubric-Based Reinforcement Learning
Rubric-based reinforcement learning (RL) evaluates responses against explicit criteria to construct rewards, offering a viable way to train large language models on open-ended tasks.Explore with Memory, Learn without It: In-Context Exploration and Self-Distillation for LLM Reasoning
Exploration bounds learning efficiency in reinforcement learning with verifiable rewards (RLVR).