4 papers
AMix-2: Establishing Protein as a Native Modality in Large Language Models
Keyue Qiu, Yixin Wu, Lihao Wang +19
We present AMix-2, a protein-text foundation model that establishes protein as a native modality in large language models (LLMs), unifying protein understanding and sequence design…
Parrot: A Training Pipeline Enhances Both Program CoT and Natural Language CoT for Reasoning
Senjie Jin, Lu Chen, Zhiheng Xi +9
Natural language chain-of-thought (N-CoT) and Program chain-of-thought (P-CoT) have emerged as two primary paradigms for large language models (LLMs) to solve mathematical reasonin…
Solving Formal Math Problems by Decomposition and Iterative Reflection
Yichi Zhou, Jianqiu Zhao, Yongxin Zhang +14
General-purpose Large Language Models (LLMs) have achieved remarkable success in intelligence, performing comparably to human experts on complex reasoning tasks such as coding and…
ReFT: Reasoning with Reinforced Fine-Tuning
Trung Quoc Luong, Xinbo Zhang, Zhanming Jie +3
One way to enhance the reasoning capability of Large Language Models (LLMs) is to conduct Supervised Fine-Tuning (SFT) using Chain-of-Thought (CoT) annotations. This approach does…