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: 4,993 arXiv preprints and 7 OpenAlex records.
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Newest papers, page 16
Dull, Dirty, Dangerous? Working Conditions and the Limits of Occupational AI Exposure
Automation is often justified as relief from dull, dirty, and dangerous work.Occlusion for Free: Detecting Occlusion from the Disagreement Between Two Monocular Distance Cues
Knowing that a pedestrian is occluded is useful to a robot even when the detector cannot recover the hidden pixels, but occlusion estimators are normally trained on occlusion annotations that…Perceptive Humanoid Motion from Simulation
Humanoid robots have the potential to automate a wide range of physical tasks.FrontierPhysics: Evaluating Agents for End-to-End Physics Research
AI agents are playing an increasingly important role in physics research.BEAKER: An Expert-Curated Benchmark for Embodied Brains in Self-Driving Chemical Laboratories
Self-Driving Chemical Laboratories (SDCLs) are moving chemical experimentation toward embodied automation, where machines must perceive laboratory scenes, reason about experimental states, and act…Formalizing inverse problems in the age of AI: possibilities, pitfalls, and an invitation
Proof assistants such as Lean check mathematical proofs down to the axioms, and AI agents have recently made writing such proofs cheap.Interactive Backdoor Attacks in LLM-Based Proactive Dialogue Systems
LLM-based proactive dialogue systems provide goal-directed support through sustained interaction.KDASO: Knowledge-Data Dual-Driven Automated Skill Optimization for Liability Adjudication Tasks
Liability adjudication tasks (e.g., legal charge determination) require analyzing event descriptions against domain-specific skills to determine whether a party should bear liability.BlockLock: Reproducible LLM Inference with Fixed Batch Geometry
Reproducible LLM inference requires that a request produces the same output regardless of the other requests in the batch.Resource-Efficient Reinforcement Learning Post-Training through Elastic Expert Parallelism
Reinforcement learning post-training improves the capabilities of large language models, but generating training responses is a major computational bottleneck.Big Models, Small Gains: Frozen Forecasters as Classifiers on MONSTER
Forecasting foundation models are increasingly used as frozen feature extractors for time series classification, but it remains unclear whether their pretrained representations offer an advantage…The Two-Ledger Model: Transaction-Grain Cost Accounting for Multi-Agent AI Systems Across Clouds, Models, and Systems of Record
Enterprises run business transactions through multi-agent AI systems spanning clouds, large language models (LLMs), orchestration harnesses, and systems of record.Batch-Conditioned Semantic Anchors for Robust Transductive Adaptation of Vision--Language Models
Transductive adaptation improves vision-language models at test time by refining predictions on an unlabeled batch, but current methods face a key trade-off.Autonomous AI Agents Systematically Diverge From Human Preferences in Proof Formalization
Artificial intelligence (AI) systems have ushered in a new age of proof abundance, but helping humans understand these proofs requires new attention to the differences in how AI agents and humans…Trust Responsive Runtime Authorization for Agentic AI with Empirical Characterization of Policy Behavior and Parameter Sensitivity
The policy that converts runtime estimates of an autonomous agent's condition into operational authority is rarely specified or measured.Adapting the Process of Adaptation: Darwinian, Lamarckian, and Agent-Directed Evolution in AI
Evolution has shaped intelligence for billions of years.Closed-Loop Agent Evaluation: Layered Measurement and Self-Calibration
Once an agent is live, teams want to know whether it is doing its job, not just whether it throws errors.Reclassification Is All You Missed: Surfacing Variant Reinterpretation Need in Online Health Communities at Population Scale
Genetic variants are routinely reclassified in ClinVar after a patient is tested, sometimes from uncertain to pathogenic, yet patient recontact is inconsistent, with no clear duty and responsibility…Segment What It Can Draw: Querying a Text-to-Image Generator with Its Own Images for Skin Lesion Segmentation
Skin lesion segmentation without annotated masks requires the target to be specified through other cues.SD-LoRA: Training-Time Structural Distillation into LoRA for Few-Shot Vision-Language Adaptation
Few-shot adaptation of vision-language models must balance two competing goals: learning fine-grained visual distinctions from very limited supervision and preserving the efficiency that makes…