15 citations · 18 across the 7 of their papers we have counts for
8 papers
Who's Keeping Score? Interactive Steering of LLM-Powered Scoring with Attune
Bhavya Chopra, Meng Chen, Rebecca Dang +5
Large language models (LLMs) are increasingly used to score text records at scale (e.g., rating candidate resumes on a 1-5 scale). However, existing LLM-powered approaches do not a…
Semantic Data Processing with Holistic Data Understanding
Youran Sun, Sepanta Zeighami, Bhavya Chopra +2
Semantic operators have increasingly become integrated within data systems to enable processing data using Large Language Models (LLMs). Despite significant recent effort in improv…
Rethinking Dataset Discovery with DataScout
Rachel Lin, Bhavya Chopra, Wenjing Lin +3
Dataset Search -- the process of finding appropriate datasets for a given task -- remains a critical yet under-explored challenge in data science workflows. Assessing dataset suita…
Steering Semantic Data Processing With DocWrangler
Shreya Shankar, Bhavya Chopra, Mawil Hasan +5
Unstructured text has long been difficult to automatically analyze at scale. Large language models (LLMs) now offer a way forward by enabling {\em semantic data processing}, where…
Why Do Multi-Agent LLM Systems Fail?
Mert Cemri, Melissa Z. Pan, Shuyi Yang +10
Despite enthusiasm for Multi-Agent LLM Systems (MAS), their performance gains on popular benchmarks are often minimal. This gap highlights a critical need for a principled understa…
Semantically Aligned Question and Code Generation for Automated Insight Generation
Ananya Singha, Bhavya Chopra, Anirudh Khatry +6
Automated insight generation is a common tactic for helping knowledge workers, such as data scientists, to quickly understand the potential value of new and unfamiliar data. Unfort…
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…
Conversational Challenges in AI-Powered Data Science: Obstacles, Needs, and Design Opportunities
Bhavya Chopra, Ananya Singha, Anna Fariha +4
Large Language Models (LLMs) are being increasingly employed in data science for tasks like data preprocessing and analytics. However, data scientists encounter substantial obstacl…