activity
20232025
most citedCultureLLM: Incorporating Cultural Differences into Large Language Models

16 citations · 27 across the 7 of their papers we have counts for

collaborators

7 papers

cs.LG2025

Distribution Preference Optimization: A Fine-grained Perspective for LLM Unlearning

Kai Qin, Jiaqi Wu, Jianxiang He +8

As Large Language Models (LLMs) demonstrate remarkable capabilities learned from vast corpora, concerns regarding data privacy and safety are receiving increasing attention. LLM un…

cs.AI2025★ 2 cited

CultureVLM: Characterizing and Improving Cultural Understanding of Vision-Language Models for over 100 Countries

Shudong Liu, Yiqiao Jin, Cheng Li +6

Vision-language models (VLMs) have advanced human-AI interaction but struggle with cultural understanding, often misinterpreting symbols, gestures, and artifacts due to biases in p…

cs.CL2024★ 1 cited

MentalArena: Self-play Training of Language Models for Diagnosis and Treatment of Mental Health Disorders

Cheng Li, May Fung, Qingyun Wang +4

Mental health disorders are one of the most serious diseases in the world. Most people with such a disease lack access to adequate care, which highlights the importance of training…

cs.CL2024★ 1 cited

NegativePrompt: Leveraging Psychology for Large Language Models Enhancement via Negative Emotional Stimuli

Xu Wang, Cheng Li, Yi Chang +2

Large Language Models (LLMs) have become integral to a wide spectrum of applications, ranging from traditional computing tasks to advanced artificial intelligence (AI) applications…

cs.AI2024

CulturePark: Boosting Cross-cultural Understanding in Large Language Models

Cheng Li, Damien Teney, Linyi Yang +3

Cultural bias is pervasive in many large language models (LLMs), largely due to the deficiency of data representative of different cultures. Typically, cultural datasets and benchm…

cs.CL2024★ 16 cited

CultureLLM: Incorporating Cultural Differences into Large Language Models

Cheng Li, Mengzhou Chen, Jindong Wang +2

Large language models (LLMs) are reported to be partial to certain cultures owing to the training data dominance from the English corpora. Since multilingual cultural data are ofte…

cs.AI2023★ 7 cited

The Good, The Bad, and Why: Unveiling Emotions in Generative AI

Cheng Li, Jindong Wang, Yixuan Zhang +7

Emotion significantly impacts our daily behaviors and interactions. While recent generative AI models, such as large language models, have shown impressive performance in various t…