leanCoP 2.0and ileanCoP 1.2: High Performance Lean Theorem Proving in Classical and Intuitionistic Logic (System Descriptions)

By J. Otten. 2008

52 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Theory and Mathematics, Program Analysis & Verification

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Yuhuai Wu
2. Ethan Dyer
3. Behnam Neyshabur
4. Guy Gur-Ari
5. Aitor Lewkowycz
6. Cezary Kaliszyk
7. Michael Färber
8. Josef Urban

In Computational Theory and Mathematics

1. Yuhuai Wu
2. Cezary Kaliszyk
3. Michael Färber
4. Josef Urban
5. Behnam Neyshabur
6. Henryk Michalewski
7. Cem Anil
8. Jia Deng

In Program Analysis & Verification

1. Cezary Kaliszyk
2. Michael Färber
3. Josef Urban
4. Yuhuai Wu
5. Henryk Michalewski

Citations in the corpus

• Solving Quantitative Reasoning Problems with Language Models (2022, background): “Work on automation of proof assistants and automated theorem provers such as E (Schulz, 2013), leanCoP (Otten, 2008), and Vampire (Kovács and Voronkov, 2013) has substantially benefited from integration with machine learning methods (Alemi et al.”
• Monte Carlo Tableau Proof Search (2016, methodology): “We implemented the proposed Monte Carlo Tableau calculus in the OCaml version [14] of leanCoP [18].”