3 papers
cs.SE2026
Agent-Diff: Benchmarking LLM Agents on Enterprise API Tasks via Code Execution with State-Diff-Based Evaluation
Hubert M. Pysklo, Artem Zhuravel, Patrick D. Watson
We present Agent-Diff, a novel benchmarking framework for evaluating agentic Large Language Models (LLMs) on real-world productivity software API tasks via code execution. Agentic…
cs.CL2022
Frame Shift Prediction
Zheng-Xin Yong, Patrick D. Watson, Tiago Timponi Torrent +2
Frame shift is a cross-linguistic phenomenon in translation which results in corresponding pairs of linguistic material evoking different frames. The ability to predict frame shift…
cs.LG2019
P2L: Predicting Transfer Learning for Images and Semantic Relations
Bishwaranjan Bhattacharjee, John R. Kender, Matthew Hill +7
Transfer learning enhances learning across tasks, by leveraging previously learned representations -- if they are properly chosen. We describe an efficient method to accurately est…