155 citations · 309 across the 27 of their papers we have counts for
4 papers · 1 filter
An Empirical Study of Validating Synthetic Data for Formula Generation
Usneek Singh, José Cambronero, Sumit Gulwani +5
Large language models (LLMs) can be leveraged to help with writing formulas in spreadsheets, but resources on these formulas are scarce, impacting both the base performance of pre-…
MASAI: Modular Architecture for Software-engineering AI Agents
Daman Arora, Atharv Sonwane, Nalin Wadhwa +5
A common method to solve complex problems in software engineering, is to divide the problem into multiple sub-problems. Inspired by this, we propose a Modular Architecture for Soft…
Class-Level Code Generation from Natural Language Using Iterative, Tool-Enhanced Reasoning over Repository
Ajinkya Deshpande, Anmol Agarwal, Shashank Shet +4
LLMs have demonstrated significant potential in code generation tasks, achieving promising results at the function or statement level across various benchmarks. However, the comple…
NoFunEval: Funny How Code LMs Falter on Requirements Beyond Functional Correctness
Manav Singhal, Tushar Aggarwal, Abhijeet Awasthi +2
Existing evaluation benchmarks of language models of code (code LMs) focus almost exclusively on whether the LMs can generate functionally-correct code. In real-world software engi…