activity
20222026
most citedWeLM: A Well-Read Pre-trained Language Model for Chinese

6 citations · 6 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CL2026

Probing Cultural Awareness in LLMs: A Case Study of Cross-Culture Aesthetic Stylistics

Jiashuo Wang, Fenggang Yu, Jian Wang +6

Large Language Models (LLMs) are increasingly deployed in diverse cultural contexts, yet their ability to master aesthetic stylistics, i.e., the strategic use of language to evoke…

cs.LG2026

E^2-LLM: Bridging Neural Signals and Interpretable Affective Analysis

Fei Ma, Han Lin, Yifan Xie +4

Emotion recognition from electroencephalography (EEG) signals remains challenging due to high inter-subject variability, limited labeled data, and the lack of interpretable reasoni…

cs.CL2025

Probing the Difficulty Perception Mechanism of Large Language Models

Sunbowen Lee, Qingyu Yin, Chak Tou Leong +5

Large language models (LLMs) are increasingly deployed on complex reasoning tasks, yet little is known about their ability to internally evaluate problem difficulty, which is an es…

cs.LG2024

Deeper Insights Without Updates: The Power of In-Context Learning Over Fine-Tuning

Qingyu Yin, Xuzheng He, Luoao Deng +5

Fine-tuning and in-context learning (ICL) are two prevalent methods in imbuing large language models with task-specific knowledge. It is commonly believed that fine-tuning can surp…

cs.CL2024

StableMask: Refining Causal Masking in Decoder-only Transformer

Qingyu Yin, Xuzheng He, Xiang Zhuang +4

The decoder-only Transformer architecture with causal masking and relative position encoding (RPE) has become the de facto choice in language modeling. Despite its exceptional perf…

cs.CL2022★ 6 cited

WeLM: A Well-Read Pre-trained Language Model for Chinese

Hui Su, Xiao Zhou, Houjin Yu +5

Large Language Models pre-trained with self-supervised learning have demonstrated impressive zero-shot generalization capabilities on a wide spectrum of tasks. In this work, we pre…