3 papers
cs.CL2026
Failure by Interference: Language Models Make Balanced Parentheses Errors When Faulty Mechanisms Overshadow Sound Ones
Daking Rai, Samuel Miller, Kevin Moran +1
Despite remarkable advances in coding capabilities, language models (LMs) still struggle with simple syntactic tasks such as generating balanced parentheses. In this study, we inve…
cs.SE2025
Mechanistic Understanding of Language Models in Syntactic Code Completion
Samuel Miller, Daking Rai, Ziyu Yao
Recently, language models (LMs) have shown impressive proficiency in code generation tasks, especially when fine-tuned on code-specific datasets, commonly known as Code LMs. Howeve…
cs.CL2024
AgreeMate: Teaching LLMs to Haggle
Ainesh Chatterjee, Samuel Miller, Nithin Parepally
We introduce AgreeMate, a framework for training Large Language Models (LLMs) to perform strategic price negotiations through natural language. We apply recent advances to a negoti…