Papers by Clayton Marr
Programming by Example meets Historical Linguistics: A Large Language Model Based Approach to Sound Law Induction (2025.acl-long)
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Atharva Naik, Darsh Agrawal, Hong Sng, Clayton Marr, Kexun Zhang, Nathaniel Romney Robinson, Kalvin Chang, Rebecca Byrnes, Aravind Mysore, Carolyn Rose, David R. Mortensen
| Challenge: | Historical linguists have written programs that convert reconstructed words into their attested descendants via ordered string rewrite functions. |
| Approach: | They propose to use a model to generate a "similar distribution" for sound law induction . they propose four kinds of methods with varying amounts of inductive bias to investigate best performance . |
| Outcome: | The proposed model shows that it can be fine tuned with training data and evaluation data. |
PBEBench: A Multi-Step Programming by Examples Reasoning Benchmark inspired by Historical Linguistics (2026.findings-acl)
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Atharva Naik, null Prakam, Yash Mathur, Darsh Agrawal, Manav Nitin Kapadnis, Yuwei An, Clayton Marr, Carolyn Rose, David R. Mortensen
| Challenge: | a benchmark for inductive reasoning is based on sound law induction in historical linguistics . solve rates are below 5% on hard PBEBench instances with long program cascades despite expensive scaling strategies . |
| Approach: | They propose a benchmark for inductive reasoning inspired by sound law induction in historical linguistics. |
| Outcome: | The proposed approach generates problems with controllable difficulty and ordering constraints . solve rates remain below 5% on hard PBEBench instances with long program cascades . |