3 citations · 7 across the 9 of their papers we have counts for
10 papers
The First Few Tokens Are All You Need: An Efficient and Effective Unsupervised Prefix Fine-Tuning Method for Reasoning Models
Ke Ji, Jiahao Xu, Tian Liang +10
Improving the reasoning capabilities of large language models (LLMs) typically requires supervised fine-tuning with labeled data or computationally expensive sampling. We introduce…
Thoughts Are All Over the Place: On the Underthinking of o1-Like LLMs
Yue Wang, Qiuzhi Liu, Jiahao Xu +11
Large language models (LLMs) such as OpenAI's o1 have demonstrated remarkable abilities in complex reasoning tasks by scaling test-time compute and exhibiting human-like deep think…
Do NOT Think That Much for 2+3=? On the Overthinking of o1-Like LLMs
Xingyu Chen, Jiahao Xu, Tian Liang +11
The remarkable performance of models like the OpenAI o1 can be attributed to their ability to emulate human-like long-time thinking during inference. These models employ extended c…
Weak-to-Strong Preference Optimization: Stealing Reward from Weak Aligned Model
Wenhong Zhu, Zhiwei He, Xiaofeng Wang +2
Aligning language models (LMs) with human preferences has become a key area of research, enabling these models to meet diverse user needs better. Inspired by weak-to-strong general…
Evaluating Knowledge-based Cross-lingual Inconsistency in Large Language Models
Xiaolin Xing, Zhiwei He, Haoyu Xu +3
This paper investigates the cross-lingual inconsistencies observed in Large Language Models (LLMs), such as ChatGPT, Llama, and Baichuan, which have shown exceptional performance i…
Unsupervised Sign Language Translation and Generation
Zhengsheng Guo, Zhiwei He, Wenxiang Jiao +6
Motivated by the success of unsupervised neural machine translation (UNMT), we introduce an unsupervised sign language translation and generation network (USLNet), which learns fro…
Improving Open-Ended Text Generation via Adaptive Decoding
Wenhong Zhu, Hongkun Hao, Zhiwei He +2
Current language models decode text token by token according to probabilistic distribution, and determining the appropriate candidates for the next token is crucial to ensure gener…
Is Self-knowledge and Action Consistent or Not: Investigating Large Language Model's Personality
Yiming Ai, Zhiwei He, Ziyin Zhang +5
In this study, we delve into the validity of conventional personality questionnaires in capturing the human-like personality traits of Large Language Models (LLMs). Our objective i…
Can Watermarks Survive Translation? On the Cross-lingual Consistency of Text Watermark for Large Language Models
Zhiwei He, Binglin Zhou, Hongkun Hao +5
Text watermarking technology aims to tag and identify content produced by large language models (LLMs) to prevent misuse. In this study, we introduce the concept of cross-lingual c…
Improving Machine Translation with Human Feedback: An Exploration of Quality Estimation as a Reward Model
Zhiwei He, Xing Wang, Wenxiang Jiao +4
Insufficient modeling of human preferences within the reward model is a major obstacle for leveraging human feedback to improve translation quality. Fortunately, quality estimation…