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20242026
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cs.AI2026

Accordion-Thinking: Self-Regulated Step Summaries for Efficient and Readable LLM Reasoning

Zhicheng Yang, Zhijiang Guo, Yinya Huang +5

Scaling test-time compute via long Chain-of-Thought unlocks remarkable gains in reasoning capabilities, yet it faces practical limits due to the linear growth of KV cache and quadr…

cs.AI2025

CombiBench: Benchmarking LLM Capability for Combinatorial Mathematics

Junqi Liu, Xiaohan Lin, Jonas Bayer +12

Neurosymbolic approaches integrating large language models with formal reasoning have recently achieved human-level performance on mathematics competition problems in algebra, geom…

cs.AI2024

AlignedCoT: Prompting Large Language Models via Native-Speaking Demonstrations

Zhicheng Yang, Yinya Huang, Jing Xiong +4

Large Language Models prompting, such as using in-context demonstrations, is a mainstream technique for invoking LLMs to perform high-performance and solid complex reasoning (e.g.,…

cs.AI2024

FVEL: Interactive Formal Verification Environment with Large Language Models via Theorem Proving

Xiaohan Lin, Qingxing Cao, Yinya Huang +5

Formal verification (FV) has witnessed growing significance with current emerging program synthesis by the evolving large language models (LLMs). However, current formal verificati…

cs.AI2024

Proving Theorems Recursively

Haiming Wang, Huajian Xin, Zhengying Liu +8

Recent advances in automated theorem proving leverages language models to explore expanded search spaces by step-by-step proof generation. However, such approaches are usually base…

cs.AI2024

DeepSeek-Prover: Advancing Theorem Proving in LLMs through Large-Scale Synthetic Data

Huajian Xin, Daya Guo, Zhihong Shao +6

Proof assistants like Lean have revolutionized mathematical proof verification, ensuring high accuracy and reliability. Although large language models (LLMs) show promise in mathem…