1 citations · 3 across the 8 of their papers we have counts for
10 papers
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…
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…
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…
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…
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…
Scaling Flaws of Verifier-Guided Search in Mathematical Reasoning
Fei Yu, Yingru Li, Benyou Wang
Large language models (LLMs) struggle with multi-step reasoning, where inference-time scaling has emerged as a promising strategy for performance improvement. Verifier-guided searc…
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…
PEER: Expertizing Domain-Specific Tasks with a Multi-Agent Framework and Tuning Methods
Yiying Wang, Xiaojing Li, Binzhu Wang +10
In domain-specific applications, GPT-4, augmented with precise prompts or Retrieval-Augmented Generation (RAG), shows notable potential but faces the critical tri-lemma of performa…
MileBench: Benchmarking MLLMs in Long Context
Dingjie Song, Shunian Chen, Guiming Hardy Chen +3
Despite the advancements and impressive performance of Multimodal Large Language Models (MLLMs) on benchmarks, their effectiveness in real-world, long-context, and multi-image task…
OVM, Outcome-supervised Value Models for Planning in Mathematical Reasoning
Fei Yu, Anningzhe Gao, Benyou Wang
Large language models (LLMs) often struggle with maintaining accuracy throughout multiple multiple reasoning steps, especially in mathematical reasoning where an error in earlier s…