Publications (24)
Binding Language Models in Symbolic Languages
Zhoujun Cheng, Tianbao Xie, Peng Shi +9
Though end-to-end neural approaches have recently been dominating NLP tasks in both performance and ease-of-use, they lack interpretability and robustness. We propose Binder, a tra…
Revisiting Reinforcement Learning for LLM Reasoning from A Cross-Domain Perspective
Zhoujun Cheng, Shibo Hao, Tianyang Liu +21
Reinforcement learning (RL) has emerged as a promising approach to improve large language model (LLM) reasoning, yet most open efforts focus narrowly on math and code, limiting our…
K2-V2: A 360-Open, Reasoning-Enhanced LLM
K2 Team, Zhengzhong Liu, Liping Tang +36
We introduce K2-V2, a 360-open LLM built from scratch as a superior base for reasoning adaptation, in addition to functions such as conversation and knowledge retrieval from genera…
MegaMath: Pushing the Limits of Open Math Corpora
Fan Zhou, Zengzhi Wang, Nikhil Ranjan +5
Mathematical reasoning is a cornerstone of human intelligence and a key benchmark for advanced capabilities in large language models (LLMs). However, the research community still l…
Human Correspondence Consensus for 3D Object Semantic Understanding
Yujing Lou, Yang You, Chengkun Li +5
Semantic understanding of 3D objects is crucial in many applications such as object manipulation. However, it is hard to give a universal definition of point-level semantics that e…
HiTab: A Hierarchical Table Dataset for Question Answering and Natural Language Generation
Zhoujun Cheng, Haoyu Dong, Zhiruo Wang +6
Tables are often created with hierarchies, but existing works on table reasoning mainly focus on flat tables and neglect hierarchical tables. Hierarchical tables challenge existing…