1 citations · 2 across the 9 of their papers we have counts for
9 papers
IndiMathBench: Autoformalizing Mathematical Reasoning Problems with a Human Touch
Param Biyani, Shashank Kirtania, Yasharth Bajpai +2
Reliable autoformalization remains challenging even in the era of large language models (LLMs). The scarcity of high-quality training data is a major bottleneck. Expert annotation…
SWE-Sharp-Bench: A Reproducible Benchmark for C# Software Engineering Tasks
Sanket Mhatre, Yasharth Bajpai, Sumit Gulwani +2
AI coding agents have shown great progress on Python software engineering benchmarks like SWE-Bench, and for other languages like Java and C in benchmarks like Multi-SWE-Bench. How…
Improving Language Agents through BREW: Bootstrapping expeRientially-learned Environmental knoWledge
Shashank Kirtania, Param Biyani, Priyanshu Gupta +4
Large Language Model (LLM)-based agents are increasingly capable of complex, multi-step tasks such as GUI automation, tool use, and data manipulation, yet they cannot learn from ex…
Why AI Agents Still Need You: Findings from Developer-Agent Collaborations in the Wild
Aayush Kumar, Yasharth Bajpai, Sumit Gulwani +2
Software Engineering Agents (SWE agents) can autonomously perform development tasks on benchmarks like SWE Bench, but still face challenges when tackling complex and ambiguous real…
TableTalk: Scaffolding Spreadsheet Development with a Language Agent
Jenny T. Liang, Aayush Kumar, Yasharth Bajpai +7
Spreadsheet programming is challenging. Programmers use spreadsheet programming knowledge (e.g., formulas) and problem-solving skills to combine actions into complex tasks. Advance…
Exploring Interaction Patterns for Debugging: Enhancing Conversational Capabilities of AI-assistants
Bhavya Chopra, Yasharth Bajpai, Param Biyani +4
The widespread availability of Large Language Models (LLMs) within Integrated Development Environments (IDEs) has led to their speedy adoption. Conversational interactions with LLM…
Augmented Embeddings for Custom Retrievals
Anirudh Khatry, Yasharth Bajpai, Priyanshu Gupta +2
Information retrieval involves selecting artifacts from a corpus that are most relevant to a given search query. The flavor of retrieval typically used in classical applications ca…
GrACE: Generation using Associated Code Edits
Priyanshu Gupta, Avishree Khare, Yasharth Bajpai +6
Developers expend a significant amount of time in editing code for a variety of reasons such as bug fixing or adding new features. Designing effective methods to predict code edits…
Overwatch: Learning Patterns in Code Edit Sequences
Yuhao Zhang, Yasharth Bajpai, Priyanshu Gupta +8
Integrated Development Environments (IDEs) provide tool support to automate many source code editing tasks. Traditionally, IDEs use only the spatial context, i.e., the location whe…