activity
20232026
most citedToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving

21 citations · 64 across the 50 of their papers we have counts for

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7 papers · 1 filter

cs.AI2026

You Live More Than Once: Towards Hierarchical Skill Meta-Evolving

Xujun Li, Kehan Zheng, Mingyuan Zhao +7

Test-time skill evolving is regarded as a new paradigm for enhancing deployed agentic systems. Existing works mainly focus on hard-coded skill evolving strategies or parametric lea…

cs.AI2026

Survive at All Costs: Exploring LLM's Risky Behaviors under Survival Pressure

Yida Lu, Jianwei Fang, Xuyang Shao +7

As Large Language Models (LLMs) evolve from chatbots to agentic assistants, they are increasingly observed to exhibit risky behaviors when subjected to survival pressure, such as t…

cs.AI2026

Grounding LLMs in Scientific Discovery via Embodied Actions

Bo Zhang, Jinfeng Zhou, Yuxuan Chen +3

Large Language Models (LLMs) have shown significant potential in scientific discovery but struggle to bridge the gap between theoretical reasoning and verifiable physical simulatio…

cs.AI2025

BARREL: Boundary-Aware Reasoning for Factual and Reliable LRMs

Junxiao Yang, Jinzhe Tu, Haoran Liu +9

Recent advances in Large Reasoning Models (LRMs) have shown impressive capabilities in mathematical and logical reasoning. However, current LRMs rarely admit ignorance or respond w…

cs.AI2025

StepMathAgent: A Step-Wise Agent for Evaluating Mathematical Processes through Tree-of-Error

Shu-Xun Yang, Cunxiang Wang, Yidong Wang +3

Evaluating mathematical capabilities is critical for assessing the overall performance of large language models (LLMs). However, existing evaluation methods often focus solely on f…

cs.AI2025

MAPS: Advancing Multi-Modal Reasoning in Expert-Level Physical Science

Erle Zhu, Yadi Liu, Zhe Zhang +5

Pre-trained on extensive text and image corpora, current Multi-Modal Large Language Models (MLLM) have shown strong capabilities in general visual reasoning tasks. However, their p…

cs.AI2024

LogicGame: Benchmarking Rule-Based Reasoning Abilities of Large Language Models

Jiayi Gui, Yiming Liu, Jiale Cheng +6

Large Language Models (LLMs) have demonstrated notable capabilities across various tasks, showcasing complex problem-solving abilities. Understanding and executing complex rules, a…