1 citations · 2 across the 11 of their papers we have counts for
11 papers
A Data-Efficient Path to Multilingual LLMs: Language Expansion via Post-training PARAM Integration into Upcycled MoE
Hao Zhou, Tianhao Li, Zhijun Wang +6
Expanding Large Language Models~(LLMs) to new languages is a costly endeavor, demanding extensive Continued Pre-Training~(CPT) and data-intensive alignment. While recent data-free…
Seed-X: Building Strong Multilingual Translation LLM with 7B Parameters
Shanbo Cheng, Yu Bao, Qian Cao +23
Multilingual translation stands as a challenging task for large language models (LLMs) to handle intricate language patterns and stilted translations that arise in automated transl…
DuPO: Enabling Reliable LLM Self-Verification via Dual Preference Optimization
Shuaijie She, Yu Bao, Yu Lu +7
We present DuPO, a dual learning-based preference optimization framework that generates annotation-free feedback via a generalized duality. DuPO addresses two key limitations: Rein…
How Does Alignment Enhance LLMs' Multilingual Capabilities? A Language Neurons Perspective
Shimao Zhang, Zhejian Lai, Xiang Liu +5
Multilingual Alignment is an effective and representative paradigm to enhance LLMs' multilingual capabilities, which transfers the capabilities from the high-resource languages to…
R-PRM: Reasoning-Driven Process Reward Modeling
Shuaijie She, Junxiao Liu, Yifeng Liu +3
Large language models (LLMs) inevitably make mistakes when performing step-by-step mathematical reasoning. Process Reward Models (PRMs) have emerged as a promising solution by eval…
Multilingual Contrastive Decoding via Language-Agnostic Layers Skipping
Wenhao Zhu, Sizhe Liu, Shujian Huang +3
Decoding by contrasting layers (DoLa), is designed to improve the generation quality of large language models (LLMs) by contrasting the prediction probabilities between an early ex…
Why Not Transform Chat Large Language Models to Non-English?
Xiang Geng, Ming Zhu, Jiahuan Li +14
The scarcity of non-English data limits the development of non-English large language models (LLMs). Transforming English-centric LLMs to non-English has been identified as an effe…
Question Translation Training for Better Multilingual Reasoning
Wenhao Zhu, Shujian Huang, Fei Yuan +3
Large language models show compelling performance on reasoning tasks but they tend to perform much worse in languages other than English. This is unsurprising given that their trai…
MAPO: Advancing Multilingual Reasoning through Multilingual Alignment-as-Preference Optimization
Shuaijie She, Wei Zou, Shujian Huang +4
Though reasoning abilities are considered language-agnostic, existing LLMs exhibit inconsistent reasoning abilities across different languages, e.g., reasoning in the dominant lang…
Exploring the Factual Consistency in Dialogue Comprehension of Large Language Models
Shuaijie She, Shujian Huang, Xingyun Wang +2
LLMs (Large Language Models) usually interact with users in the form of dialogue and generate responses following their instructions, which naturally require dialogue comprehension…
CoP: Factual Inconsistency Detection by Controlling the Preference
Shuaijie She, Xiang Geng, Shujian Huang +1
Abstractive summarization is the process of generating a summary given a document as input. Although significant progress has been made, the factual inconsistency between the docum…