47 citations · 85 across the 19 of their papers we have counts for
4 papers · 1 filter
CRScore: Grounding Automated Evaluation of Code Review Comments in Code Claims and Smells
Atharva Naik, Marcus Alenius, Daniel Fried +1
The task of automated code review has recently gained a lot of attention from the machine learning community. However, current review comment evaluation metrics rely on comparisons…
Can Large Language Models Code Like a Linguist?: A Case Study in Low Resource Sound Law Induction
Atharva Naik, Kexun Zhang, Nathaniel Robinson +7
Historical linguists have long written a kind of incompletely formalized ''program'' that converts reconstructed words in an ancestor language into words in one of its attested des…
Generating Situated Reflection Triggers about Alternative Solution Paths: A Case Study of Generative AI for Computer-Supported Collaborative Learning
Atharva Naik, Jessica Ruhan Yin, Anusha Kamath +6
An advantage of Large Language Models (LLMs) is their contextualization capability - providing different responses based on student inputs like solution strategy or prior discussio…
On the Limitations of Embedding Based Methods for Measuring Functional Correctness for Code Generation
Atharva Naik
The task of code generation from natural language (NL2Code) has become extremely popular, especially with the advent of Large Language Models (LLMs). However, efforts to quantify a…