AI & Machine Learning · Computer Science & AI
Artificial Intelligence
The newest papers in Artificial Intelligence that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
The newest 5,000 papers, from 11 October 2026 to 5 November 2026: 4,998 arXiv preprints and 2 OpenAlex records.
Get the few papers worth your time in Artificial Intelligence every morning.
Follow Artificial Intelligence and ReadSearch reads its new papers each day, then brings you the few worth reading, each with its key finding in a sentence.
Newest papers, page 79
Governance-Aware Federated Learning for Multi-Agent AI Systems: A Policy-Driven Framework for Trustworthy Collaborative AI
Federated Learning (FL) enables collaborative model training without exchanging raw data, but conventional FL provides limited runtime governance, evidence verification, fairness assessment…The Code Behind the Layout: AI Agents for Analog Layout Generators
Analog layout remains largely manual and hard to automate.DecisionUnlearn-Bench: Unlearning Probabilistic Decisions under Changing Schemas
Machine unlearning aims to reproduce the behavior of a model trained without designated data.RoleFUZZER: User-Behaviour Fuzzing for Role-Specification Adherence in Large Language Models
Large language models (LLMs) are often conditioned into specific roles such as tutors, interviewers, or agents acting for an organisation, through system prompts that specify how they should behave.Predict the Reward, Not the World: World Reward Models for ML Agents
Search-based machine-learning (ML) agents improve a solution by writing candidate programs, executing them, and keeping the best.DES-JEPA: Learning a Shared Vocabulary for High-Dimensional Discrete Event Sequences
Temporal foundation models such as Chronos and TimesFM generalize across domains through a shared numerical observation space.Benchmarking decision models against generative large language models on medical multiple-choice questions
Medical workflows often require selecting among predefined options.Tracekit Box: Running AI Agents in Micro-VMs Where Every Way Out Is Decided and Signed
AI agents now install packages, call model APIs with their operators' keys and change code in repositories that deploy to production.Accelerating Nonlinear MPC by Behavior Cloning with Separated Timescales: Application to Nuclear Reactor Load-Following
Behavior Cloning (BC) of expert controllers for multiscale dynamical systems is challenging: state variables evolving at widely separated timescales induce highly nonlinear couplings that a shared…SaiVLA-JEPA: Evaluating Future Latent Prediction in JEPA-Conditioned VLA Control
Joint-embedding predictive architectures (JEPAs) learn to predict representations rather than pixels, offering a compact way to model how visual scenes evolve.AtomSteer: Test-Time Constraint Steering for Atomistic Generative Models
Diffusion and flow matching models offer scalable approaches to generating crystalline materials, molecular conformers, and protein-ligand complexes.Value Probes: Learned Value Functions for Beam-Search Red Teaming
Automated red-team auditing of language models is an important way to evaluate safety-relevant behaviors.From Leniency to Suspicion: How an Open Post-Training Recipe Changes Whom LLM Fact-Checkers Believe
LLMs increasingly fact-check online content with the poster's identity in view.An Alignment Benchmark for Enterprise Agents on Era by Eon
AI agents are widely used in enterprises to access business systems and act on them in pursuit of a goal.PT$^3$: Prototype-Guided Self-Supervised Pretraining for Generalizable mmWave Human Point Cloud Representation
Multi-source millimeter-wave (mmWave) observations offer an opportunity to learn human representations reusable across sensing tasks.Persona Learning from Feedback for Personalized AI Assistants
Personalizing AI assistants requires adapting their behavior to users' preferences and task contexts.Co-Evolving Policy and Rubric via Capability Awareness for Open-Ended Generation
Rubric-based reinforcement learning (RL) offers interpretable, fine-grained supervision for aligning large language models (LLMs) on open-ended generation tasks.A-RSI: Adaptive Task Refresh for Zero-Data Multimodal Self-Improvement
Recursive self-improvement requires models not only to acquire useful training experience, but also to decide when their current experience has ceased to be useful.Do Audio LLMs HEAR Pain? Tracing Acoustic Evidence from Speech to Language Reasoning
Large audio language models (LALMs) can process speech directly, but it remains unclear how well they use the non-lexical acoustic information that speech carries.CALM: Conflict-Aware Lifecycle Memory Governance for Long-Horizon Language Agents
A memory can be outdated for present-day reasoning yet indispensable for reconstructing the past.