6 papers
Multiplex Thinking: Reasoning via Token-wise Branch-and-Merge
Yao Tang, Li Dong, Yaru Hao +3
Large language models often solve complex reasoning tasks more effectively with Chain-of-Thought (CoT), but at the cost of long, low-bandwidth token sequences. Humans, by contrast,…
NoteBar: An AI-Assisted Note-Taking System for Personal Knowledge Management
Josh Wisoff, Yao Tang, Zhengyu Fang +3
Note-taking is a critical practice for capturing, organizing, and reflecting on information in both academic and professional settings. The recent success of large language models…
Synthesizing Near-Boundary OOD Samples for Out-of-Distribution Detection
Jinglun Li, Kaixun Jiang, Zhaoyu Chen +4
Pre-trained vision-language models have exhibited remarkable abilities in detecting out-of-distribution (OOD) samples. However, some challenging OOD samples, which lie close to in-…
Reinforcement Pre-Training
Qingxiu Dong, Li Dong, Yao Tang +4
In this work, we introduce Reinforcement Pre-Training (RPT) as a new scaling paradigm for large language models and reinforcement learning (RL). Specifically, we reframe next-token…
QLASS: Boosting Language Agent Inference via Q-Guided Stepwise Search
Zongyu Lin, Yao Tang, Xingcheng Yao +4
Language agents have become a promising solution to complex interactive tasks. One of the key ingredients to the success of language agents is the reward model on the trajectory of…
Learning Versatile Skills with Curriculum Masking
Yao Tang, Zhihui Xie, Zichuan Lin +2
Masked prediction has emerged as a promising pretraining paradigm in offline reinforcement learning (RL) due to its versatile masking schemes, enabling flexible inference across va…