Tracked topic
Large language models are machine learning models trained to predict and generate text and other language-based outputs.
…Steering LLM Logical Reasoning via Alignment of Natural-Language and Symbolic Views (2026) Where Reasoning Breaks: Logic-Aware Path Selection by Controlling Logical Connectives in LLMs Reasoning Chains (2026) When Chain-of…
Papers arxiv:2605.09252 LLM Agents Already Know When to Call Tools -- Even Without Reasoning Published on May 10 Submitted by Chung-En, Sun on May 13 Authors: Chung-En Sun , , , , Abstract…
…First, a BEV representation consolidates multi-view spatial information into a structure compatible with LLMs. Second, we introduce LLM-enhanced world queries to facilitate knowledge transfer from the understanding branch. Third, a…
…Generated by Qwen/Qwen2.5-Coder-32B-Instruct Reinforcement learning (RL) post-training has shown to improve reasoning in large language models (LLMs). However, there has been little exploration on the problem…
Papers arxiv:2604.26326 Addressing Performance Saturation for LLM RL via Precise Entropy Curve Control Published on May 10 Submitted by Bolian Li on May 12 Purdue University Authors: Bolian Li , Yifan…
…Benchmarking LLM Agents on Real-World Personal Applications via Environment Simulation Published on Jun 1 Submitted by WENHAO WANG on Jun 2 Authors: , , , , , , , , , , , Abstract MCP-Persona benchmark evaluates agent performance on personalized…
…Disentangling Evolution Capabilities in Self-Evolving LLM Agents Published on May 28 Submitted by Minhua Lin on Jun 1 Authors: Minhua Lin , Juncheng Wu , , , , , , , , , , , , , , , Abstract Research reveals that harness self-evolution capabilities…
…A Dataset and LLM Pipeline for Extracting Empirical Relation Graphs from Psychology Abstracts Published on Jun 6 Submitted by Xingwei Tan on Jun 9 Authors: , , Xingwei Tan , Abstract Variable-centered empirical graph…
…Multi-Agent Self-Evolution for LLM Reasoning (2026) Experience is the Best Teacher: Motivating Effective Exploration in Reinforcement Learning for LLMs (2026) $\pi$-Play: Multi-Agent Self-Play via Privileged Self-Distillation…
…By transforming graph topology and node information into graph tokens , GLMs allow LLMs to jointly process structured graph inputs and textual instructions. Yet, it remains unclear how LLMs internally interpret these graph…