| Data generation for neural programming by example J Clymo, H Manukian, N Fijalkow, A Gascón, B Paige International Conference on Artificial Intelligence and Statistics, 3450-3459, 2020 | 15 | 2020 |
| Short proofs in QBF expansion O Beyersdorff, L Chew, J Clymo, M Mahajan Theory and Applications of Satisfiability Testing–SAT 2019: 22nd …, 2019 | 8 | 2019 |
| Relating size and width in variants of Q-resolution J Clymo, O Beyersdorff Information Processing Letters 138, 1-6, 2018 | 8 | 2018 |
| How QBF expansion makes strategy extraction hard L Chew, J Clymo Automated Reasoning: 10th International Joint Conference, IJCAR 2020, Paris …, 2020 | 6 | 2020 |
| The equivalences of refutational QRAT L Chew, J Clymo Theory and Applications of Satisfiability Testing–SAT 2019: 22nd …, 2019 | 6 | 2019 |
| Proof Complexity for Quantified Boolean Formulas JC Clymo University of Leeds, 2021 | 4 | 2021 |
| Exploration of chemical space through automated reasoning J Clymo, CM Collins, K Atkinson, MS Dyer, MW Gaultois, VV Gusev, ... Angewandte Chemie, e202417657, 2025 | 2 | 2025 |
| KARaML: Integrating Knowledge-Based and Machine Learning Approaches to Solve the Winograd Schema Challenge. SJ Hong, B Bennett, J Clymo, LG Álvarez AAAI Spring Symposium: MAKE, 2022 | 2 | 2022 |
| More on Size and Width in QBF Resolution. O Beyersdorff, J Clymo Electronic Colloquium on Computational Complexity (ECCC) 25, 25, 2018 | 1 | 2018 |
| Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Y Zimmermann, A Bazgir, Z Afzal, F Agbere, Q Ai, N Alampara, ... arXiv preprint arXiv:2411.15221, 2024 | | 2024 |
| The Riis Complexity Gap for QBF Resolution O Beyersdorff, J Clymo, S Dantchev, B Martin Journal on Satisfiability, Boolean Modeling and Computation 15 (1), 9-25, 2024 | | 2024 |
