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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 146
Projected Distillation: On Learning to Solve Hard Problems from Close, Correct Targets
On-policy learning is central to post-training: training on a model's own generations limits distribution shift and helps preserve existing capabilities.Training-Free Continual Learning for Multimodal Forecasting via Prompt Evolution
Adapting a forecasting system to a changing world classically means retraining.Privacy-Preserving Personalized Federated Learning (PPP-FL) for Medical Imaging
Federated learning (FL) is a distributed machine learning paradigm that reduces transmission costs, mitigates cross-border data sharing restrictions, and enhances privacy by keeping raw data on…Beyond the Prompt: Recovering Hidden Concepts in Text-to-Image Models
Text-to-image models can generate visual concepts that their prompts never mention, and recent work shows that such associations can be implanted so that ordinary prompts trigger them.Runtime Control for AI Agents: Closing the Evaluation--Execution Gap in Operational Workflows
Language-model agents increasingly participate in operational workflows where approvals, binds, and payments create commitments.Securing Agentic Commerce Through Behavior-Aware Fraud Detection and Cybersecurity for Trusted AI-Agent Payment Authorization
The growing use of autonomous artificial intelligence agents in digital commerce creates new security concerns involving agent impersonation, unauthorized payments, compromised agents, and misuse of…The More the Better? A Comparison of Single- and Multi-Agent LLM Setups on a Financial Review Task
Practitioner guidance holds that a large language model reviews a document better when the work is divided among agents.Orthogonal Boundary Unlearning for Dual-Use Concepts in Large Language Models
Mitigating catastrophic risks from large language models requires excising hazardous operational capabilities, such as cyberwarfare exploitation and pathogen enhancement, without degrading benign…Self-Evolving Agents through Privileged Retrospective Distillation
Self-evolving agents aim to improve from their own experience rather than remain fixed after deployment, but naturally collected trajectories often lack ground-truth solutions or verifier-derived…Cross-Visibility-Gap Identity Persistence for 4D Scene Graphs
4D scene graphs require persistent object identity when an object disappears inside an opaque carrier and later reappears as a fresh detection.Structured-Token Attention for Fine-Grained mmWave Liquid Identification
Fine-grained liquid identification requires a classifier to distinguish similar substances from compact millimeter-wave measurements.Progressive Subset Selection and Cascaded Consistency for Unsupervised Vision-Language Model Adaptation
Pretrained Vision-Language Models (PVLMs) achieve strong zero-shot recognition but often suffer performance degradation under target-domain shift.HealBench: A Fine-Grained Benchmark for Evaluating Psychological Comfort in Text-to-Image Generation
Despite advances in photorealism, semantic fidelity, and aesthetics, text-to-image generation and image editing remain understudied in a human-centered dimension: whether their outputs feel…When Health Assistants Agree Too Readily: A Benchmark of Time-Critical Self-Diagnosis
Every day, more than 40 million people ask ChatGPT a health question, such as whether laptop posture explains a stiff neck and days of pounding headache.MemDev-Bench: Does Memory Help Code Agents?Benchmarking Memory Systems over Real Repository Histories
Code agents increasingly work on evolving real repositories, and memory systems aim to help them reuse earlier experience.Automated Multi-Agent Organization Design: From Architecture Search to Organizational Learning
Agentic system design is increasingly shifting from hand-crafted prompts and workflows toward automated search over agentic programs and interaction structures, with multi-agent systems receiving…Adversarial Benchmarks and BenchDoor Attacks: Exploiting Benchmark Incentives for Backdoor Attacks
Machine learning benchmarks act as guideposts for model development and spur the creation of training datasets intended to improve benchmark scores.Less is More: Concise Retrieval and Critic-based Re-ranking for Composed Image Retrieval
Zero-shot composed image retrieval (ZS-CIR) aims to retrieve a target image based on a reference image and modification text.Act on Your Behalf, Beyond Your Authorization: Benchmarking LLM Agent Authorization Alignment
When an LLM agent acts on behalf of a user, it is expected to act within the authorization scope the user grants.Can Native Safety Travel? Reusing Safety Pretraining Across Models via On-Policy Distillation
Safety pretraining has emerged as a promising paradigm for embedding safety deeply into a model during pretraining, yielding robustness to subsequent fine-tuning that conventional safety…