61 citations · 98 across the 30 of their papers we have counts for
35 papers · 1 filter
Unsupervised Post-Training of Foundation Models: A Survey
Yijie Xu, Qianyi Cai, Huizai Yao +9
Foundation-model post-training usually relies on human labels, preference data, stronger teachers, or executable verifiers. We study Unsupervised Post-Training (UPT): update-bearin…
You only need 4 extra tokens: Synergistic Test-time Adaptation for LLMs
Yijie Xu, Huizai Yao, Zhiyu Guo +5
Large language models (LLMs) are increasingly deployed in specialized domains such as finance, medicine, and agriculture, where they face significant distribution shifts from their…
A Survey on Parallel Text Generation: From Parallel Decoding to Diffusion Language Models
Lingzhe Zhang, Liancheng Fang, Chiming Duan +8
As text generation has become a core capability of modern Large Language Models (LLMs), it underpins a wide range of downstream applications. However, most existing LLMs rely on au…
Mark Your LLM: Detecting the Misuse of Open-Source Large Language Models via Watermarking
Yijie Xu, Aiwei Liu, Xuming Hu +2
As open-source large language models (LLMs) like Llama3 become more capable, it is crucial to develop watermarking techniques to detect their potential misuse. Existing watermarkin…
Can LLM Watermarks Robustly Prevent Unauthorized Knowledge Distillation?
Leyi Pan, Aiwei Liu, Shiyu Huang +5
The radioactive nature of Large Language Model (LLM) watermarking enables the detection of watermarks inherited by student models when trained on the outputs of watermarked teacher…
Interpretable Contrastive Monte Carlo Tree Search Reasoning
Zitian Gao, Boye Niu, Xuzheng He +5
We propose SC-MCTS*: a novel Monte Carlo Tree Search (MCTS) reasoning algorithm for Large Language Models (LLMs), significantly improves both reasoning accuracy and speed. Our moti…