6 papers
PhysProver: Advancing Automatic Theorem Proving for Physics
Hanning Zhang, Ruida Wang, Rui Pan +3
The combination of verifiable languages and LLMs has significantly influenced both the mathematical and computer science communities because it provides a rigorous foundation for t…
Lean4Physics: Comprehensive Reasoning Framework for College-level Physics in Lean4
Yuxin Li, Minghao Liu, Ruida Wang +6
We present **Lean4PHYS**, a comprehensive reasoning framework for college-level physics problems in Lean4. **Lean4PHYS** includes *LeanPhysBench*, a college-level benchmark for for…
Generalizable Geometric Image Caption Synthesis
Yue Xin, Wenyuan Wang, Rui Pan +5
Multimodal large language models have various practical applications that demand strong reasoning abilities. Despite recent advancements, these models still struggle to solve compl…
Let's Reason Formally: Natural-Formal Hybrid Reasoning Enhances LLM's Math Capability
Ruida Wang, Yuxin Li, Yi R. Fung +1
Enhancing the mathematical reasoning capabilities of LLMs has garnered significant attention in both the mathematical and computer science communities. Recent works have made subst…
FANS -- Formal Answer Selection for Natural Language Math Reasoning Using Lean4
Jiarui Yao, Ruida Wang, Tong Zhang
Large Language Models (LLMs) have displayed astonishing abilities in various tasks, especially in text generation, classification, question answering, etc. However, the reasoning a…
MA-LoT: Model-Collaboration Lean-based Long Chain-of-Thought Reasoning enhances Formal Theorem Proving
Ruida Wang, Rui Pan, Yuxin Li +6
Solving mathematical problems using computer-verifiable languages like Lean has significantly impacted the mathematical and computer science communities. State-of-the-art methods u…