activity
20242026
collaborators

5 papers

cs.HC2026

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…

cs.HC2026

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…

cs.SE2026

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…

cs.SE2025

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…

cs.SE2024

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…