3 citations · 5 across the 14 of their papers we have counts for
15 papers
The "Knowledge-Behavior Gap" in Cultural Taboo Safety of Large Language Models
Ying He, Sihang Jiang, Xingzhou Chen +6
Cultural taboo safety is essential for deploying large language models (LLMs), as culturally insensitive outputs may cause offense or even social harm. However, existing cultural b…
The GaoYao Benchmark: A Comprehensive Framework for Evaluating Multilingual and Multicultural Abilities of Large Language Models
Yilun Liu, Chunguang Zhao, Mengyao Piao +14
Evaluating the multilingual and multicultural capabilities of Large Language Models (LLMs) is essential for their global utility. However, current benchmarks face three critical li…
HumanLLM: Benchmarking and Improving LLM Anthropomorphism via Human Cognitive Patterns
Xintao Wang, Jian Yang, Weiyuan Li +8
Large Language Models (LLMs) have demonstrated remarkable capabilities in reasoning and generation, serving as the foundation for advanced persona simulation and Role-Playing Langu…
CultureScope: A Dimensional Lens for Probing Cultural Understanding in LLMs
Jinghao Zhang, Sihang Jiang, Shiwei Guo +7
As large language models (LLMs) are increasingly deployed in diverse cultural environments, evaluating their cultural understanding capability has become essential for ensuring tru…
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…
LITE: LLM-Impelled efficient Taxonomy Evaluation
Lin Zhang, Zhouhong Gu, Suhang Zheng +4
This paper presents LITE, an LLM-based evaluation method designed for efficient and flexible assessment of taxonomy quality. To address challenges in large-scale taxonomy evaluatio…
RECKON: Large-scale Reference-based Efficient Knowledge Evaluation for Large Language Model
Lin Zhang, Zhouhong Gu, Xiaoran Shi +2
As large language models (LLMs) advance, efficient knowledge evaluation becomes crucial to verifying their capabilities. Traditional methods, relying on benchmarks, face limitation…
GAPO: Learning Preferential Prompt through Generative Adversarial Policy Optimization
Zhouhong Gu, Xingzhou Chen, Xiaoran Shi +5
Recent advances in large language models have highlighted the critical need for precise control over model outputs through predefined constraints. While existing methods attempt to…
LLM-GAN: Construct Generative Adversarial Network Through Large Language Models For Explainable Fake News Detection
Yifeng Wang, Zhouhong Gu, Siwei Zhang +5
Explainable fake news detection predicts the authenticity of news items with annotated explanations. Today, Large Language Models (LLMs) are known for their powerful natural langua…
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…
StrucText-Eval: Evaluating Large Language Model's Reasoning Ability in Structure-Rich Text
Zhouhong Gu, Haoning Ye, Xingzhou Chen +3
The effective utilization of structured data, integral to corporate data strategies, has been challenged by the rise of large language models (LLMs) capable of processing unstructu…
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…