8 citations · 14 across the 15 of their papers we have counts for
5 papers · 1 filter
A Survey of Process Reward Models: From Outcome Signals to Process Supervisions for Large Language Models
Congmin Zheng, Jiachen Zhu, Zhuoying Ou +8
Although Large Language Models (LLMs) exhibit advanced reasoning ability, conventional alignment remains largely dominated by outcome reward models (ORMs) that judge only final ans…
Evolutionary Perspectives on the Evaluation of LLM-Based AI Agents: A Comprehensive Survey
Jiachen Zhu, Menghui Zhu, Renting Rui +9
The advent of large language models (LLMs), such as GPT, Gemini, and DeepSeek, has significantly advanced natural language processing, giving rise to sophisticated chatbots capable…
LLM4CD: Leveraging Large Language Models for Open-World Knowledge Augmented Cognitive Diagnosis
Weiming Zhang, Lingyue Fu, Qingyao Li +7
Cognitive diagnosis (CD) plays a crucial role in intelligent education, evaluating students' comprehension of knowledge concepts based on their test histories. However, current CD…
Position: The Real Barrier to LLM Agent Usability is Agentic ROI
Weiwen Liu, Jiarui Qin, Xu Huang +10
Large Language Model (LLM) agents represent a promising shift in human-AI interaction, moving beyond passive prompt-response systems to autonomous agents capable of reasoning, plan…
NL-Debugging: Exploiting Natural Language as an Intermediate Representation for Code Debugging
Weiming Zhang, Qingyao Li, Xinyi Dai +7
Debugging is a critical aspect of LLM's coding ability. Early debugging efforts primarily focused on code-level analysis, which often falls short when addressing complex programmin…