2 citations · 2 across the 2 of their papers we have counts for
4 papers
Better Harnesses, Smaller Models: Building 90% Cheaper Agents via Automated Harness Adaptation
Chenyang Yang, Xinran Zhao, Tongshuang Wu +1
Frontier LLM agents are automating many business tasks, but their high inference cost makes large-scale deployment unsustainable. Small language models (SLMs) offer a cheaper alter…
What Prompts Don't Say: Understanding and Managing Underspecification in LLM Prompts
Chenyang Yang, Yike Shi, Qianou Ma +3
Prompt underspecification is a common challenge when interacting with LLMs. In this paper, we present an in-depth analysis of this problem, showing that while LLMs can often infer…
(Why) Is My Prompt Getting Worse? Rethinking Regression Testing for Evolving LLM APIs
Wanqin Ma, Chenyang Yang, Christian Kästner
Large Language Models (LLMs) are increasingly integrated into software applications. Downstream application developers often access LLMs through APIs provided as a service. However…
Beyond Testers' Biases: Guiding Model Testing with Knowledge Bases using LLMs
Chenyang Yang, Rishabh Rustogi, Rachel Brower-Sinning +3
Current model testing work has mostly focused on creating test cases. Identifying what to test is a step that is largely ignored and poorly supported. We propose Weaver, an interac…