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 12 October 2026 to 6 November 2026: 4,992 arXiv preprints and 8 OpenAlex records.
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Newest papers, page 249
GUIDE: Computationally Augmented Consensus for Trustworthy Clinical Practice Guidelines
Maintaining up-to-date clinical practice guidelines (CPGs) is essential for evidence-based medicine, but rapid evidence growth and complex expert consensus formation limit timely updates.Constructed regional photovoltaic generation fields improve ultra-short-term distributed solar forecasting
Ultra-short-term forecasting of densely distributed photovoltaic (PV) systems remains challenging because external meteorological and satellite products may not adequately resolve rapid local…Beyond Perfect Teammates: Multi-Agent Collaboration with Unreliable Colleagues
LLM-based multi-agent collaboration is increasingly used to solve complex tasks by dividing work among specialized agents and integrating complementary expertise.Imitation Holds a Key to Evolution: Localized Repair and Verified Skill Acquisition for Adaptive Agents
An agent can retain successful trajectories without learning which part of an experience should repair a new discrepancy.Towards a Benchmark for Fire Safety Code Interpretation in the Hong Kong AEC Industry
Large Language Models (LLMs) are increasingly explored in the Architecture, Engineering, and Construction (AEC) domain, yet their reliability in regulatory compliance remains uncertain.PID-Gated Continual Prompt Adaptation Under Noisy Feedback
Deploying LLM agents in non-stationary environments requires continually revising their instructions as the task drifts, yet rewriting after every reported mistake can turn noisy feedback into…Query Your Way Out: Benchmarking Multi-Turn Knowledge Reasoning through Generalized Puzzle Solving
Puzzles offer a natural testbed for Large Language Models (LLMs) reasoning because they pose verifiable goals under partial information and require multi-step decisions to reach a solution.Omni-Modal LLMs Know More Than They Say
Omni-modal large language models (Omni-LLMs) extend LLMs to process heterogeneous modalities (e.g., vision, audio, and IMU signals) alongside language, enabling a broader range of multimodal tasks.Large Language Model Assisted Transportation Planning through a Differentiable User Equilibrium Layer
Transportation planning has traditionally required substantial expertise in network modeling, traffic assignment, and optimization.Phantom Merge: When Your Large Language Model Agents Pick One but Tell You About Another
LLM agents increasingly operate over multiple entities, where reliable response generation requires not only retrieving relevant evidence but also preserving its association with the correct entity.Pollard: Governed Semantic Execution Trees for Framework-Independent AI Agent Control and Replay
Agent frameworks can persist checkpoints, trace tool calls, and limit resource use, but these facilities often assign different identities to execution, governance, and replay.Unravel: Recovering an Interactive 3D Scene from a Single Image
We present Unravel, a training-free framework that turns a single image into an interactive 3D scene, where every object is an independent and movable asset.WildTrace: Evaluating Training Data Detection in Realistic Large-Scale LLM Post-Training
This drives growing interest in training data detection for post-trained models.Uncovering Robustness Weaknesses in LLM Agents via Persona Evolution with Task-Integrity Constraints
Interactive-agent evaluations commonly rely on standardized LLM-based user simulators that exhibit broadly cooperative behavior, potentially overlooking failures that arise under diverse but…Fisher information and the geometry of memorization in neural networks
A fruitful approach towards understanding generalization in machine learning involves characterizing how models separate generalizable structure from idiosyncratic or even corrupted features of…Interactive 4D Volumetric Liquid Forecasting under Moving-Solid Interaction
We propose the task of Interactive 4D Volumetric Liquid Forecasting: predicting the spatiotemporal evolution of a future dense 3D liquid velocity field conditioned on how a solid object moves…EventLens: Event-Structure Reinforcement Learning for Video Understanding
Recent multimodal large language models (MLLMs) achieve strong results on video question answering, yet often fail to recover the temporal structure that makes a video coherent.ProCARE: Real-World Study Automation via Profile-Grounded Evidence Contracts
Real-world studies (RWS) analyze routinely collected healthcare data, such as electronic health records and insurance claims, to estimate treatment effects, monitor safety, and identify risk factors…Label-Centric Knowledge Retrieval for Zero-Shot Text Classification
Flagship large language models (LLMs) offer rich general knowledge and strong reasoning capabilities, but their high inference cost and latency limit their use for large-scale data labeling.Correct Choices, Failed Sequences: Choice2Seq Benchmarks Correctness Retention Across Output Interfaces
A model may select the correct answer yet fail to construct it through a sequence of local decisions.