9 citations · 12 across the 9 of their papers we have counts for
9 papers
AgentGroupChat-V2: Divide-and-Conquer Is What LLM-Based Multi-Agent System Need
Zhouhong Gu, Xiaoxuan Zhu, Yin Cai +12
Large language model based multi-agent systems have demonstrated significant potential in social simulation and complex task resolution domains. However, current frameworks face cr…
ToReMi: Topic-Aware Data Reweighting for Dynamic Pre-Training Data Selection
Xiaoxuan Zhu, Zhouhong Gu, Baiqian Wu +5
Pre-training large language models (LLMs) necessitates enormous diverse textual corpora, making effective data selection a key challenge for balancing computational resources and m…
VCEval: Rethinking What is a Good Educational Video and How to Automatically Evaluate It
Xiaoxuan Zhu, Zhouhong Gu, Sihang Jiang +3
Online courses have significantly lowered the barrier to accessing education, yet the varying content quality of these videos poses challenges. In this work, we focus on the task o…
DetectBench: Can Large Language Model Detect and Piece Together Implicit Evidence?
Zhouhong Gu, Lin Zhang, Xiaoxuan Zhu +8
Detecting evidence within the context is a key step in the process of reasoning task. Evaluating and enhancing the capabilities of LLMs in evidence detection will strengthen contex…
AgentGroupChat: An Interactive Group Chat Simulacra For Better Eliciting Emergent Behavior
Zhouhong Gu, Xiaoxuan Zhu, Haoran Guo +10
Language significantly influences the formation and evolution of Human emergent behavior, which is crucial in understanding collective intelligence within human societies. Consider…
Efficiently Quantifying and Mitigating Ripple Effects in Model Editing
Jianchen Wang, Zhouhong Gu, Xiaoxuan Zhu +5
Large Language Models have revolutionized numerous tasks with their remarkable efficacy. However, editing these models, crucial for rectifying outdated or erroneous information, of…
Piecing Together Clues: A Benchmark for Evaluating the Detective Skills of Large Language Models
Zhouhong Gu, Lin Zhang, Jiangjie Chen +8
Detectives frequently engage in information detection and reasoning simultaneously when making decisions across various cases, especially when confronted with a vast amount of info…
Xiezhi: An Ever-Updating Benchmark for Holistic Domain Knowledge Evaluation
Zhouhong Gu, Xiaoxuan Zhu, Haoning Ye +16
New Natural Langauge Process~(NLP) benchmarks are urgently needed to align with the rapid development of large language models (LLMs). We present Xiezhi, the most comprehensive eva…
Domain Mastery Benchmark: An Ever-Updating Benchmark for Evaluating Holistic Domain Knowledge of Large Language Model--A Preliminary Release
Zhouhong Gu, Xiaoxuan Zhu, Haoning Ye +7
Domain knowledge refers to the in-depth understanding, expertise, and familiarity with a specific subject, industry, field, or area of special interest. The existing benchmarks are…