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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 182
DialogMem: Evaluating Dialogue-Grounded Embodied Memory in 3D Environments
Embodied agents in human-centered environments require memory that integrates what they observe with what humans tell them over time.Evidence Field: Adaptive Covering Programs for Medical Imaging
Medical image classifiers typically return predictions without a native contract for independently reconstructing their spatial decision computation.AI Rights with an Off-Switch: Rights-Balancing and Due Process Harmonize AI Rights with AI Safety
Several prominent voices in AI safety have recently opposed rights for AI on the grounds that such rights would make it harder for us to justify a mandatory off-switch for potentially dangerous…LLM Trojans that Increase Response Lengths and Cost
Management of the token-based costs of using LLMs has emerged as a significant problem.IndustrialCAD-1400: Benchmarking Detailed Industrial Assemblies from Text
Industrial assemblies require more than a recognizable shape: functional parts, interfaces, dimensions and service features must satisfy a detailed request together.When LLM-Generated Refactorings Ripple: An Empirical Study of Repository Adoption Readiness
Large Language Models (LLMs) are increasingly used to refactor source files, but file-local evaluations do not reveal changes to contracts, dependencies, or caller assumptions affecting repository…Cooperation Without Shared Rewards via Reciprocal Q-Augmentation
General-sum games are more challenging than fully cooperative or adversarial settings because agents may deceive or exploit one another.Aptamers as a sandbox for lab-in-the-loop agentic molecular discovery
Despite breakthroughs in AI-driven molecular generation, existing discovery pipelines operate largely in silico, with wet-lab feedback reserved for validation rather than iterative improvement.Medical Fine-Tuning Reshapes, Not Reduces, Patient-Facing AI Risk: A Rubric-Based, LLM-Judge Evaluation Framework
Patient-facing medical question answering with large language models (LLMs) is moving from research demonstrations to production deployments, yet evaluation remains anchored on factual correctness.First-Order LoRA Training with Phone NPUs
On-device fine-tuning lets a large language model (LLM) learn from its user's private data without uploading it.Pair-Aware Optimization: Coordinating Exploration and Refinement for Jailbreaking LLM Agents
Large Language Model (LLM) agents are vulnerable to adversarial inputs that induce attacker-specified malicious behaviors, commonly referred to as jailbreaking.Teaching Code Agents to Ask Without Leaking Private Code
Local coding agents can extend their reach by consulting a stronger cloud model.Measuring Consensus in AI Agent Networks
As AI agents become increasingly connected through networks and take on tasks that require negotiation and joint decision-making, a systematic approach is needed to assess how their views converge…Pattern-Driven Evaluation of LLM Code Optimization: Isolating Compiler-Transcendent Semantic Reasoning
Existing evaluations of LLM-based code optimization primarily measure end-to-end speedup, obscuring whether a model actually performs the intended optimization.SpriteStage: Long Horizon Animation Generation via Progressive Scene Programming and Replay
Video generation models synthesize visual sequences from text and image inputs.Bellman Language Models: Solving the Recurring Decisions of LLM Agents
A general observation in agentic workflows, especially bounded ones, is that the decision space of the LLM, when we separate a decision from generation, starts approaching saturation: the agent…The One-Pixel of Reasoning: One Truthful Relation Is Enough to Mislead LLM Agents
Can one sentence manipulate an agent's belief by targeting a single implicit warrant linking evidence to a conclusion?RAFT: Redundancy-Aware Input Filtering for Temporal Graph Neural Network Training
Temporal graph neural networks (TGNNs) have shown strong performance on dynamic graph learning tasks by continuously updating node memories from evolving interactions (i.e., events) and leveraging…HybridResearcher: Bridging the Structured-Unstructured Boundary for Deep Research Agents
While LLM agents are increasingly capable of gathering and synthesizing evidence from a single homogeneous source, such as structured tables or unstructured data, real-world analytical questions…Leveraging Mental Models for Human-Centered Explanations: A Systematic Design Approach Illustrated by Explainable Fake Review Identification
Explainable AI (XAI) often prioritizes model fidelity over user intelligibility, yielding explanations that satisfy technical transparency yet fail to support human sense-making.