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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.
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Newest papers, page 109
CoLink: Global Compression and Knowledge Linking for Multi-Turn Dialogue Modeling
Extracting salient information from long-horizon dialogue histories remains a significant challenge for Large Language Models (LLMs) due to the restricted context windows and efficient retrieval…Improving the Chain-of-Thought Compressibility of Pruned Reasoning Models via Long--Short Contrastive Pruning
Large reasoning models are costly to serve because they are large and because they generate long chains of thought (CoT).Xing USP: A Cross-Family Semantic Contract for Information Extraction and Intent-Slot Parsing
Structured semantic parsing is typically judged by whether the correct category is assigned, which leaves value recovery and instance-level associations unexamined: a system may recognize an event…SEEK: Skill Extraction with Evolving Knowledge against Frontier Science Agents
Science agents increasingly package domain expertise as reusable skills that plan analyses, select tools, and execute workflows.ComBeautify: Leveraging Code Change Summaries for Conventional Commit Generation
Modern software development relies on version control systems such as Git to track changes and facilitate collaboration.Whether or Where? Tail Calibration Signals Finite-Budget Reward Hacking in Best-of-N Selection
Best-of-N (BoN) inference returns the candidate with the highest proxy reward, so a larger $N$ tests the proxy's extreme tail more than its average ranking quality.AndroidFlux: Evaluating and Reward Modeling Failure Recovery Capabilities in Mobile Use Multimodal Agents
Mobile-use multimodal agents are typically evaluated by task success from a clean initial state, which does not isolate their ability to recover from intermediate errors.Outcome-Aware Agents: When Does Causal Structure Help a Forward Model Foresee the Consequences of Actions?
Agents that act on real systems should predict what their actions will cause before acting.ParetoRSI-Gym: Can AI Agents Improve Language Models Across Multiple Domains?
Recursive self-improvement (RSI) requires an agentic system to design, train, and evaluate its own successor.Dynamic Multi-Step Decoding for Time-Series Foundation Models
Time-series forecasting models typically use a fixed decoding strategy at inference time: either one-shot prediction of the full horizon or autoregressive rollout over atomic chunks.In-Context Adapter Generation for Compositional Generalization in Large Audio Language Models
Large audio language models (LALMs) have achieved strong performance on standard speech and audio understanding tasks, yet their ability to systematically generalize to novel task compositions…Spatial Audio Generation and Editing with Executable Plans and Self-Distilling Transfusion
Spatial audio authoring coordinates source decisions with soundfield synthesis.MulFCoder: Framework-conditioned Multi-agent for MLLM-based Multi-framework Front-end Code Generation
Generating runnable front-end code from UI screenshots is a long-standing goal in automated software engineering.CTXAgent - Self-Controlled Context Management of LLM Agents
Agent harnesses keep long sessions inside the context window by compacting the history when a token threshold is crossed.CyberDual: AI Attackers versus AI Code Reviewers in Real Software Maintenance
Open-source projects now let AI agents review incoming code, but the code under review may itself come from an AI attacker.EvolveMAS: A Unified Self-Evolution Framework for Decentralized Multi-Agent Systems
Decentralized multi-agent systems (MAS) enable large language model agents to interact without centralized control.From Outranking Flow Scores to Linear Programs: Group Decision Making in PROMETHEE II
We study inverse and consensus analysis for PROMETHEE II ranking problems when the performance table is fixed.Efficient Proof Generation for Lean Statements with Multiple Candidate Answers
In formal systems such as Lean 4, efficiently finding answers to mathematical problems and generating verifiable proofs is an important task in automated mathematical reasoning.What Effort Level Should I Choose? On the Economics of Reasoning Effort in LLM Agents
Generative models increasingly expose a reasoning effort setting that lets users scale inference-time compute, trading higher cost for potentially improved performance.Certifying Distributionally Robust Decisions from Projection Observations
A scalar measurement can determine a robust decision without identifying the latent covariance or every decision risk.