9 citations · 9 across the 4 of their papers we have counts for
5 papers
Guaranteed Guess: A Language Modeling Approach for CISC-to-RISC Transpilation with Testing Guarantees
Ahmed Heakl, Sarim Hashmi, Chaimaa Abi +2
The hardware ecosystem is rapidly evolving, with increasing interest in translating low-level programs across different instruction set architectures (ISAs) in a quick, flexible, a…
The Counterfeit Conundrum: Can Code Language Models Grasp the Nuances of Their Incorrect Generations?
Alex Gu, Wen-Ding Li, Naman Jain +4
While language models are increasingly more proficient at code generation, they still frequently generate incorrect programs. Many of these programs are obviously wrong, but others…
Mixture of Soft Prompts for Controllable Data Generation
Derek Chen, Celine Lee, Yunan Lu +2
Large language models (LLMs) effectively generate fluent text when the target output follows natural language patterns. However, structured prediction tasks confine the output form…
MP-CodeCheck: Evolving Logical Expression Code Anomaly Learning with Iterative Self-Supervision
Urs C. Muff, Celine Lee, Paul Gottschlich +1
Machine programming (MP) is concerned with automating software development. According to studies, software engineers spend upwards of 50% of their development time debugging softwa…
Toward Code Generation: A Survey and Lessons from Semantic Parsing
Celine Lee, Justin Gottschlich, Dan Roth
With the growth of natural language processing techniques and demand for improved software engineering efficiency, there is an emerging interest in translating intention from human…