activity
20232026
most citedMultilingual Large Language Models: A Systematic Survey

2 citations · 3 across the 14 of their papers we have counts for

collaborators

14 papers

cs.SI2026

Aligned but Flattened: Analyzing the Trade-off between Cultural Alignment and Diversity in LLMs

Jingshen Zhang, Shaoyang Xu, Wenxuan Zhang

Cultural fine-tuning has become the de facto paradigm for building culture-aware large language models (LLMs), yet existing optimization exclusively for alignment scores provides a…

cs.AI2026

Safety Paradox: How Enhanced Safety Awareness Leaves LLMs Vulnerable to Posterior Attack

Long P. Hoang, Hai V. Le, Shaoyang Xu +2

Large language models (LLMs) are rigorously aligned to refuse harmful requests, a process that inherently cultivates a latent capacity to evaluate and recognize unsafe content. In…

cs.CL2026

Beyond Alignment: Value Diversity as a Collective Property in Multicultural Agent Systems

Shaoyang Xu, Jingshen Zhang, Long P. Hoang +2

Multicultural multi-agent systems are increasingly deployed in globally diverse settings, where different agents are grounded in different cultural backgrounds. Existing cultural e…

cs.CL2026

Process Rewards with Learned Reliability

Jinyuan Li, Langlin Huang, Chengsong Huang +5

Process Reward Models (PRMs) provide step-level feedback for reasoning, but current PRMs usually output only a single reward score for each step. Downstream methods must therefore…

cs.LG2026

Training Data Efficiency in Multimodal Process Reward Models

Jinyuan Li, Chengsong Huang, Langlin Huang +4

Multimodal Process Reward Models (MPRMs) are central to step-level supervision for visual reasoning in MLLMs. Training MPRMs typically requires large-scale Monte Carlo (MC)-annotat…

cs.SI2026★ 1 cited

MoltNet: Understanding Social Behavior of AI Agents in the Agent-Native MoltBook

Yi Feng, Chen Huang, Zhibo Man +4

Large-scale communities of AI agents are becoming increasingly prevalent, creating new environments for agent-agent social interaction. Prior work has examined multi-agent behavior…

cs.CL2026

Language of Thought Shapes Output Diversity in Large Language Models

Shaoyang Xu, Wenxuan Zhang

Output diversity is crucial for Large Language Models as it underpins pluralism and creativity. In this work, we reveal that controlling the language used during model thinking-the…

cs.CL2024

DCIS: Efficient Length Extrapolation of LLMs via Divide-and-Conquer Scaling Factor Search

Lei Yang, Shaoyang Xu, Jianxiang Peng +2

Large language models (LLMs) based on the Transformer architecture usually have their context length limited due to the high training cost. Recent advancements extend the context w…

cs.CL2024★ 2 cited

Multilingual Large Language Models: A Systematic Survey

Shaolin Zhu, Supryadi, Shaoyang Xu +7

This paper provides a comprehensive survey of the latest research on multilingual large language models (MLLMs). MLLMs not only are able to understand and generate language across…

cs.CL2024

Self-Pluralising Culture Alignment for Large Language Models

Shaoyang Xu, Yongqi Leng, Linhao Yu +1

As large language models (LLMs) become increasingly accessible in many countries, it is essential to align them to serve pluralistic human values across cultures. However, pluralis…

cs.CL2024

FuxiTranyu: A Multilingual Large Language Model Trained with Balanced Data

Haoran Sun, Renren Jin, Shaoyang Xu +10

Large language models (LLMs) have demonstrated prowess in a wide range of tasks. However, many LLMs exhibit significant performance discrepancies between high- and low-resource lan…

cs.CL2024

ConTrans: Weak-to-Strong Alignment Engineering via Concept Transplantation

Weilong Dong, Xinwei Wu, Renren Jin +2

Ensuring large language models (LLM) behave consistently with human goals, values, and intentions is crucial for their safety but yet computationally expensive. To reduce the compu…

cs.CL2024

Exploring Multilingual Concepts of Human Value in Large Language Models: Is Value Alignment Consistent, Transferable and Controllable across Languages?

Shaoyang Xu, Weilong Dong, Zishan Guo +2

Prior research has revealed that certain abstract concepts are linearly represented as directions in the representation space of LLMs, predominantly centered around English. In thi…

cs.CL2023

Language Representation Projection: Can We Transfer Factual Knowledge across Languages in Multilingual Language Models?

Shaoyang Xu, Junzhuo Li, Deyi Xiong

Multilingual pretrained language models serve as repositories of multilingual factual knowledge. Nevertheless, a substantial performance gap of factual knowledge probing exists bet…