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 5
CORE: Coarse-to-Fine Search with Context Management for Deep Research
Deep research agents answer complex questions through repeated search.FARR: Forecast-Aware Residual Refinement with Matched Endpoint Evidence for Long-Horizon Time-Series Forecasting
Large language models use auxiliary conditioning to incorporate additional information into time-series forecasts.Responsible GenAI Use During Active Armed Conflict: Evidence from Sudan's Emergency Response Rooms
Armed conflict can increase the value of Generative AI (GenAI) while undermining the conditions required for its responsible use.Network Effect Decomposition for Causal Effect Estimation under Network Interference
Estimating causal effects from observational network data requires accounting for both individual treatment and neighborhood exposure.InnerLogic-Surg: An Open Surgical Foundation Model via Continual Pretraining
Vision foundation models are the backbone of modern surgical image analysis, yet most surgical systems still rely on encoders pretrained on natural images or on specialist models trained from…When, Where, How: Active In-Context Learning for Tabular Foundation Models
Tabular Foundation Models (TFMs) adapt to a new task only through the labeled rows in their context.When Bigger Becomes Brittle: Why Compression Hurts More as Language Models Scale
Quantization and pruning reduce the cost of deploying language models, but their effects are usually reported as benchmark scores.DISCERN: Distributional Synthetic Replay for Retain-Free Incremental Machine Unlearning
Machine unlearning aims to remove the influence of specific training data from a trained model without retraining from scratch.Persistent Retrieval for Conversational Agents: A Study of Retrieval Efficiency
Conversational agents can retrieve information directly or delegate retrieval to a subagent.Structure from Collision via Hypothesis-Space Reasoning
Knowledge of the hidden interior structure of an object, including the presence and location of cavities, is essential for predictive simulation, robotic manipulation, and nondestructive inspection.GuidedWAM: Training-Free Energy Guidance for World Action Models in Autonomous Driving
World action models (WAMs) for autonomous driving couple the driving policy and the visual world model in a single generative network whose objectives are fixed post-training.Adaptive Semantic Branching: Disagreement-Localized Cross-Trajectory Regeneration for Reasoning Candidate Expansion
Reasoning trajectories generated for the same problem often arrive at conflicting answers.How Finite Brains Generalize Without Bound: Spatial Memory as a Universal Computer
A child who learns to add small numbers adds numbers of any length.ZeroRAG: Adaptive Semantic Peer Routing for Decentralized Retrieval-Augmented Generation
Retrieval-augmented generation (RAG) is a standard approach to enhance the reliability of large language model (LLM) outputs by retrieving documents relevant to a query and supplying them in the LLM…AttnSR: Attention Step Reward for Long-Horizon Agentic RL
Long-horizon LLM agents make multi-step decisions, yet outcome-reward-only reinforcement learning provides little direct supervision for individual steps.Towards Scalable Diagnostic-Driven Whole-Slide Image Retrieval for Pathology Archives
The growing adoption of digital pathology has rapidly expanded collections of hematoxylin-and-eosin whole-slide images, yet efficient navigation through these archives remains challenging, as…CardioLM: A multilingual suite of small language models for the cardiology domain
Cardiovascular care generates large volumes of clinical free-text documentation in local languages.tok: a textual concrete syntax of BPMN and DMN for humans and AI agents
tok is a plain-text notation for Business Process Model and Notation (BPMN) 2.0.2 process models and Decision Model and Notation (DMN) 1.5 decisions.ChemE-as-Code: An Open-Source Platform for Agentic AI in Chemical Engineering
ChemE-as-Code provides an open-source environment in which AI agents built on large language models (LLMs) can carry out chemical engineering work and engineers can check it.Circe: Training-Free LLM Self-Evaluation via Component Interaction Consistency
As large language models (LLMs) are increasingly deployed in real-world applications, evaluating the correctness of their responses is crucial for reliable use.