7 papers
Toward Automated Robustness Evaluation of Mathematical Reasoning
Yutao Hou, Zeguan Xiao, Fei Yu +6
Large Language Models (LLMs) have demonstrated remarkable capabilities in various reasoning-intensive tasks. However, these models exhibit unexpected brittleness, often failing on…
AgentBay: A Hybrid Interaction Sandbox for Seamless Human-AI Intervention in Agentic Systems
Yun Piao, Hongbo Min, Hang Su +28
The rapid advancement of Large Language Models (LLMs) is catalyzing a shift towards autonomous AI Agents capable of executing complex, multi-step tasks. However, these agents remai…
Robust Search with Uncertainty-Aware Value Models for Language Model Reasoning
Fei Yu, Yingru Li, Benyou Wang
Value model guided search is effective in steering LLM generation but suffers from a lack of robustness. This is due to verifier failure: imperfect VMs mistakenly prune valid reaso…
Second Language (Arabic) Acquisition of LLMs via Progressive Vocabulary Expansion
Jianqing Zhu, Huang Huang, Zhihang Lin +18
This paper addresses the critical need for democratizing large language models (LLM) in the Arab world, a region that has seen slower progress in developing models comparable to st…
QFFT, Question-Free Fine-Tuning for Adaptive Reasoning
Wanlong Liu, Junxiao Xu, Fei Yu +7
Recent advancements in Long Chain-of-Thought (CoT) reasoning models have improved performance on complex tasks, but they suffer from overthinking, which generates redundant reasoni…
Dual Engines of Thoughts: A Depth-Breadth Integration Framework for Open-Ended Analysis
Fei-Hsuan Yu, Yun-Cheng Chou, Teng-Ruei Chen
We propose the Dual Engines of Thoughts (DEoT), an analytical framework for comprehensive open-ended reasoning. While traditional reasoning frameworks primarily focus on finding "t…