6 citations · 24 across the 15 of their papers we have counts for
15 papers
DRACO: Fine-Grained Credit Assignment with Dynamic Rubrics for Long-Horizon Agent Training
Shubham Gandhi, Saurabh Goyal, Kiran Kate +1
Reinforcement Learning from Verifiable Rewards works well when a task has a programmatic checker, but most long-horizon agent domains have none. We work in the outcome-blind settin…
OASBuilder: Generating OpenAPI Specifications from Online API Documentation with Large Language Models
Koren Lazar, Matan Vetzler, Kiran Kate +8
AI agents and business automation tools interacting with external web services require standardized, machine-readable information about their APIs in the form of API specifications…
Improving Examples in Web API Specifications using Iterated-Calls In-Context Learning
Kush Jain, Kiran Kate, Jason Tsay +2
Examples in web API specifications can be essential for API testing, API understanding, and even building chat-bots for APIs. Unfortunately, most API specifications lack human-writ…
Out of style: Misadventures with LLMs and code style transfer
Karl Munson, Chih-Kai Ting, Serenity Wade +4
Like text, programs have styles, and certain programming styles are more desirable than others for program readability, maintainability, and performance. Code style transfer, howev…
AI for Low-Code for AI
Nikitha Rao, Jason Tsay, Kiran Kate +2
Low-code programming allows citizen developers to create programs with minimal coding effort, typically via visual (e.g. drag-and-drop) interfaces. In parallel, recent AI-powered t…
MILO: Model-Agnostic Subset Selection Framework for Efficient Model Training and Tuning
Krishnateja Killamsetty, Alexandre V. Evfimievski, Tejaswini Pedapati +3
Training deep networks and tuning hyperparameters on large datasets is computationally intensive. One of the primary research directions for efficient training is to reduce trainin…