4 citations · 5 across the 5 of their papers we have counts for
6 papers
Self-Evolving Search Index
Sangam Lee, Wonjae Lee, Sunghwan Kim +5
Information retrieval is increasingly important as LLM agents tackle complex tasks involving diverse information needs. Because retrieval relies on an index that represents each do…
Motif: Discovering and Automating Personal Web Workflows
Shaokang Jiang, Daye Nam
Recent advances in LLMs and existing work on programming by demonstration have made it possible for end users to create automations by explicitly demonstrating their behavior to LL…
HANSEL: Extracting Breadcrumbs from Web Agent Trajectories for Interactive Verification
Yujin Zhang, Daye Nam
AI web agents can perform complex, multi-step tasks such as searching for products, comparing options, and making purchases on behalf of users. However, verifying the correctness o…
Beyond the Prompt: An Empirical Study of Cursor Rules
Shaokang Jiang, Daye Nam
While Large Language Models (LLMs) have demonstrated remarkable capabilities, research shows that their effectiveness depends not only on explicit prompts but also on the broader c…
Understanding and supporting how developers prompt for LLM-powered code editing in practice
Daye Nam, Ahmed Omran, Ambar Murillo +6
Large Language Models (LLMs) are rapidly transforming software engineering, with coding assistants embedded in an IDE becoming increasingly prevalent. While research has focused on…
How much does AI impact development speed? An enterprise-based randomized controlled trial
Elise Paradis, Kate Grey, Quinn Madison +6
How much does AI assistance impact developer productivity? To date, the software engineering literature has provided a range of answers, targeting a diversity of outcomes: from per…