7 citations · 7 across the 7 of their papers we have counts for
7 papers
Uncovering and Mitigating Aggregation-Induced Reward Hacking in Multi-Reward Reinforcement Learning
Yu Yuan, Yaoyou Fan, Lili Zhao +5
Reinforcement learning fine-tuning of large language models increasingly adopts multiple reward dimensions, including verifiable rules, task-specific evaluators, and learned reward…
Beyond Retrieval: Modeling Confidence Decay and Deterministic Agentic Platforms in Generative Engine Optimization
XinYu Zhao, ChengYou Li, XiangBao Meng +2
Generative Engine Optimization (GEO) is rapidly reshaping digital marketing paradigms in the era of Large Language Models (LLMs). However, current GEO strategies predominantly rely…
CeProAgents: A Hierarchical Agents System for Automated Chemical Process Development
Yuhang Yang, Ruikang Li, Jifei Ma +8
The development of chemical processes, a cornerstone of chemical engineering, presents formidable challenges due to its multi-faceted nature, integrating specialized knowledge, con…
Simulating Human-Like Learning Dynamics with LLM-Empowered Agents
Yu Yuan, Lili Zhao, Wei Chen +4
Capturing human learning behavior based on deep learning methods has become a major research focus in both psychology and intelligent systems. Recent approaches rely on controlled…
Self-Reflective Planning with Knowledge Graphs: Enhancing LLM Reasoning Reliability for Question Answering
Jiajun Zhu, Ye Liu, Meikai Bao +3
Recently, large language models (LLMs) have demonstrated remarkable capabilities in natural language processing tasks, yet they remain prone to hallucinations when reasoning with i…
Know3-RAG: A Knowledge-aware RAG Framework with Adaptive Retrieval, Generation, and Filtering
Xukai Liu, Ye Liu, Shiwen Wu +4
Recent advances in large language models (LLMs) have led to impressive progress in natural language generation, yet their tendency to produce hallucinated or unsubstantiated conten…
Retrieval Augmented Generation Evaluation in the Era of Large Language Models: A Comprehensive Survey
Aoran Gan, Hao Yu, Kai Zhang +5
Recent advancements in Retrieval-Augmented Generation (RAG) have revolutionized natural language processing by integrating Large Language Models (LLMs) with external information re…