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This comprehensive survey examines Lean 4, a state-of-the-art interactive theorem prover and functional programming language. We analyze its architectural design, type system, metaprogramming capabilities, and practical applications in…

计算机科学中的逻辑 · 计算机科学 2025-02-03 Xichen Tang

LLM-based formal proof assistants (e.g., in Lean) hold great promise for automating mathematical discovery. But beyond syntactic correctness, do these systems truly understand mathematical structure as humans do? We investigate this…

人工智能 · 计算机科学 2025-10-21 Haoyu Zhao , Yihan Geng , Shange Tang , Yong Lin , Bohan Lyu , Hongzhou Lin , Chi Jin , Sanjeev Arora

Enterprise searches require users to have complex knowledge of queries, configurations, and metadata, rendering it difficult for them to access information as needed. Most go-to-market (GTM) platforms utilize advanced search, an interface…

计算与语言 · 计算机科学 2024-11-11 Jesse Yao , Saurav Acharya , Priyaranjan Parida , Srinivas Attipalli , Ali Dasdan

LLM-generated explanations can make technical content more accessible, but there is a ceiling on what they can support interactively. Because LLM outputs are static text, they cannot be executed or stepped through. We argue that grounding…

人机交互 · 计算机科学 2026-04-13 Hita Kambhamettu , Will Crichton , Sean Welleck , Harrison Goldstein , Andrew Head

Large language models (LLMs) often struggle with complex logical reasoning due to logical inconsistencies and the inherent difficulty of such reasoning. We use Lean, a theorem proving framework, to address these challenges. By formalizing…

计算与语言 · 计算机科学 2024-03-21 Dongwei Jiang , Marcio Fonseca , Shay B. Cohen

Existing large language models (LLMs) driven search agents typically rely on prompt engineering to decouple the user queries into search plans, limiting their effectiveness in complex scenarios requiring reasoning. Furthermore, they suffer…

信息检索 · 计算机科学 2025-05-27 Jinzheng Li , Sibo Ju , Yanzhou Su , Hongguang Li , Yiqing Shen

Verifiable formal languages like Lean have profoundly impacted mathematical reasoning, particularly through the use of large language models (LLMs) for automated reasoning. A significant challenge in training LLMs for these formal languages…

计算与语言 · 计算机科学 2025-02-28 Guoxiong Gao , Yutong Wang , Jiedong Jiang , Qi Gao , Zihan Qin , Tianyi Xu , Bin Dong

Informal mathematics has been central to modern large language model (LLM) reasoning, offering flexibility and enabling efficient construction of arguments. However, purely informal reasoning is prone to logical gaps and subtle errors that…

人工智能 · 计算机科学 2025-11-25 Azim Ospanov , Zijin Feng , Jiacheng Sun , Haoli Bai , Xin Shen , Farzan Farnia

Conversational user queries are increasingly challenging traditional e-commerce platforms, whose search systems are typically optimized for keyword-based queries. We present an LLM-based semantic search framework that effectively captures…

信息检索 · 计算机科学 2026-01-26 Emad Siddiqui , Venkatesh Terikuti , Xuan Lu

The Lean mathematical library mathlib is developed by a community of users with very different backgrounds and levels of experience. To lower the barrier of entry for contributors and to lessen the burden of reviewing contributions, we have…

编程语言 · 计算机科学 2020-07-28 Floris van Doorn , Gabriel Ebner , Robert Y. Lewis

Large Language Models (LLMs) demonstrate impressive mathematical reasoning abilities, but their solutions frequently contain errors that cannot be automatically checked. Formal theorem proving systems such as Lean 4 offer automated…

人工智能 · 计算机科学 2026-03-18 Sumanth Varambally , Thomas Voice , Yanchao Sun , Zhifeng Chen , Rose Yu , Ke Ye

Large Language Models (LLMs) have demonstrated significant potential in generating mathematical proofs. However, a persistent challenge is that LLMs occasionally make mistakes, while even a minor mistake can invalidate an entire proof.…

计算机科学中的逻辑 · 计算机科学 2025-03-10 David Yin , Jing Gao

Recent advances in large language models have demonstrated impressive capabilities in mathematical formalization. However, existing benchmarks focus on logical verification of declarative propositions, often neglecting the task of…

计算机科学中的逻辑 · 计算机科学 2026-02-03 Bowen Yang , Yi Yuan , Chenyi Li , Ziyu Wang , Liangqi Li , Bo Zhang , Zhe Li , Zaiwen Wen

As automated reasoning systems advance rapidly, there is a growing need for research-level formal mathematical problems to accurately evaluate their capabilities. To address this, we present Formal Conjectures, an evolving benchmark of…

We present a novel AI-based ideation assistant and evaluate it in a user study with a group of innovators. The key contribution of our work is twofold: we propose a method of idea exploration in a constrained domain by means of…

人机交互 · 计算机科学 2024-11-07 Thomas Sandholm , Sarah Dong , Sayandev Mukherjee , John Feland , Bernardo A. Huberman

Large Language Models (LLMs) have been successful in mathematical reasoning tasks such as formal theorem proving when integrated with interactive proof assistants like Lean. Existing approaches involve training or fine-tuning an LLM on a…

机器学习 · 计算机科学 2025-03-07 Adarsh Kumarappan , Mo Tiwari , Peiyang Song , Robert Joseph George , Chaowei Xiao , Anima Anandkumar

We present **Lean4PHYS**, a comprehensive reasoning framework for college-level physics problems in Lean4. **Lean4PHYS** includes *LeanPhysBench*, a college-level benchmark for formal physics reasoning in Lean4, which contains 200…

人工智能 · 计算机科学 2025-10-31 Yuxin Li , Minghao Liu , Ruida Wang , Wenzhao Ji , Zhitao He , Rui Pan , Junming Huang , Tong Zhang , Yi R. Fung

The research in AI-based formal mathematical reasoning has shown an unstoppable growth trend. These studies have excelled in mathematical competitions like IMO and have made significant progress. This paper focuses on formal verification,…

We introduce CSLib, an open-source framework for proving computer-science-related theorems and writing formally verified code in the Lean proof assistant. CSLib aims to be for computer science what Lean's Mathlib is for mathematics. Mathlib…

Log data can reveal valuable information about how users interact with Web search services, what they want, and how satisfied they are. However, analyzing user intents in log data is not easy, especially for emerging forms of Web search…