3 citations · 3 across the 10 of their papers we have counts for
10 papers
LKValues: Aligning Large Language Models with Sri Lankan Societal Values
Nethmi Muthugala, Supryadi, Surangika Ranathunga +7
Value alignment of Large Language Models (LLMs) has been shown to be culturally biased toward Western norms. This results in the mishandling of local values in multilingual societi…
SARA: Unlocking Multilingual Knowledge in Mixture-of-Experts via Semantically Anchored Routing Alignment
Tianyu Dong, Yangyang Liu, Jiang Zhou +9
Sparse Mixture-of-Experts (MoE) architectures have emerged as an increasingly influential paradigm as they offer a strategic balance between parameter scalability and computational…
Beyond Value Benchmarks: Measuring Value-Structure Alignment in Large Language Models via Symmetric Q-Sorts
Jingting Zheng, Yuqi Ren, Linhao Yu +2
Large Language Models (LLMs) are increasingly deployed in contexts requiring complex moral reasoning and value trade-offs. However, existing evaluations typically rely on item-leve…
Incentivizing Parametric Knowledge via Reinforcement Learning with Verifiable Rewards for Cross-Cultural Entity Translation
Jiang Zhou, Xiaohu Zhao, Xinwei Wu +8
Cross-cultural entity translation remains challenging for large language models (LLMs) as literal or phonetic renderings are usually yielded instead of culturally appropriate trans…
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…
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…
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…
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…
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…
DEPN: Detecting and Editing Privacy Neurons in Pretrained Language Models
Xinwei Wu, Junzhuo Li, Minghui Xu +4
Large language models pretrained on a huge amount of data capture rich knowledge and information in the training data. The ability of data memorization and regurgitation in pretrai…