3 papers
cs.SE2025
ToolScan: A Benchmark for Characterizing Errors in Tool-Use LLMs
Shirley Kokane, Ming Zhu, Tulika Awalgaonkar +15
Evaluating Large Language Models (LLMs) is one of the most critical aspects of building a performant compound AI system. Since the output from LLMs propagate to downstream steps, i…
cs.CL2025
LAM SIMULATOR: Advancing Data Generation for Large Action Model Training via Online Exploration and Trajectory Feedback
Thai Hoang, Kung-Hsiang Huang, Shirley Kokane +12
Large Action Models (LAMs) for AI Agents offer incredible potential but face challenges due to the need for high-quality training data, especially for multi-steps tasks that involv…
cs.CL2025
Text2Data: Low-Resource Data Generation with Textual Control
Shiyu Wang, Yihao Feng, Tian Lan +6
Natural language serves as a common and straightforward signal for humans to interact seamlessly with machines. Recognizing the importance of this interface, the machine learning c…