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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 133
METTA: Memory-Enhanced Test-Time Adaptation for Meta-Reinforcement Learning
Meta-reinforcement learning aims to train agents that adapt quickly to unseen tasks from limited interaction, but this requires representing task evidence over long interaction histories.Cost-Aware Abstention for LLM-Based IT Ticket Classification
Wrong automatic routing of an IT support ticket can cost more than human triage.Direct Pass@$k$ Optimization for Thought Pruning: Balancing Quality and Diversity in Test-Time Reasoning
Test-time scaling has emerged as a key inference strategy for reasoning models, where a model generates a large number of candidate solutions in the hope of finding at least one correct solution.Mining the Design Space of Multi-Agent Workflows
Designing large language model (LLM) multi-agent systems (MAS) still relies on trial and error and informal "folk wisdom.Compact-Bench: Measuring What Context Compaction Costs Long-Horizon Coding Agents
Context compaction lets long-horizon coding agents continue beyond their context windows, but can erase the state needed to finish a task.MBABench-2.0: Evaluating AI Agents on Constructing Financial Spreadsheets Beyond Simple Verifiability
Spreadsheets are the lingua franca of modern finance, driving valuation, forecast, audit, and many other core workflows of the industry.Reuse, Rewrite, or Reject: Evidence-Constrained Trace Reuse for Repeated Mobile GUI Control
Mobile GUI agents frequently perform repetitive tasks with similar interaction procedures.What Open-Source Projects Tell Their Coding Agents: A Census of AGENTS.md and CLAUDE.md
Coding agents can be guided with instruction files in a repository.End-to-End Differentiable Diffusion Conditioning for Physics-Informed Optimization
Optimizing high-dimensional physical systems under expensive evaluations and complex constraints is a central challenge in science and engineering.Autoregressive Multimodal Anomaly Detection with Large Language Models for Microservice Systems
Microservice systems have become a dominant architecture for large-scale cloud applications, enabling rapid deployment and elastic scaling.Learning to Be Monitored: Causal Bounds and Intervention-Aware Post-Training Recipes for Chain-of-Thought Monitorability
Chain-of-thought (CoT) monitoring aims to detect potentially harmful behaviors in large language models (LLMs) from their CoTs.Generalized green and red concepts for artificial intelligence, big data, and information and communication technologies: Multidimensional framework and countermeasures
The rapid expansions of artificial intelligence (AI), big data (BD), and information and communication technologies (ICT) are driving substantial growth in electricity, water, and material demands…Benchmarks Are Surprisingly Compaction-Friendly
Long horizon agentic tasks are now pushing LLM agents past their context window.Phronix: The Capability-Centric Learning Paradigm for Agents
Scientific computing increasingly relies on large language model-based agents for performance engineering tasks such as instrumentation, analysis, and workflow porting.Patronizing and Condescending Language Detection in English and Mandarin
Patronizing and condescending language (PCL) is a form of harmful language that belittles and assumes pity for vulnerable groups, reinforcing negative societal stereotypes.PaperFormalizer: Author-in-the-Loop Autoformalization of Research Papers in Lean
Even a carefully proofread paper can leave small gaps in its proofs or its stated assumptions.PrefO2O: Zero-Shot Preference-Based Reinforcement Learning via Offline-to-Online Latent Preference Transfer
Preference-based reinforcement learning (PbRL) has emerged as a promising paradigm for learning robot behaviors aligned with human intent.What the Query Remembers: Query Abstraction Governs Lexical and Dense Retrieval of Classical Arabic Poetry
How well a poetry archive can be searched depends on what the user still remembers, not only on what the model understands.SEVI: Safe Evidential Real-World Reinforcement Learning
Real-world reinforcement learning has enabled contact-rich manipulation tasks to be trained directly on physical robots, but unsafe interactions during online learning remain a key barrier to…Don't Forget What You Just Learned: Self-Directed Repair Turns Agent Mistakes Into Lasting Lessons
Intelligent agents should learn from their mistakes so that experience leads to continuous improvement.