LENS: A Learnable Evaluation Metric for Text Simplification. - Mounica Maddela; Yao Dou; David Heineman; Wei Xu 004 (ACL (1), 2023)

Dancing Between Success and Failure: Edit-level Simplification Evaluation using SALSA. - David Heineman; Yao Dou; Mounica Maddela; Wei Xu 004 (EMNLP, 2023)

Thresh: A Unified, Customizable and Deployable Platform for Fine-Grained Text Evaluation. - David Heineman; Yao Dou; Wei Xu 004 (EMNLP (Demos), 2023)

Improving Minimum Bayes Risk Decoding with Multi-Prompt. - David Heineman; Yao Dou; Wei Xu 004 (EMNLP, 2024)

Towards a Path Dependent Account of Category Fluency. - David Heineman; Reba Koenen; Sashank Varma (CoRR, 2024)

Establishing Task Scaling Laws via Compute-Efficient Model Ladders. - Akshita Bhagia; Jiacheng Liu 010; Alexander Wettig; David Heineman; Oyvind Tafjord; Ananya Harsh Jha; Luca Soldaini; Noah A. Smith; Dirk Groeneveld; Pang Wei Koh; Jesse Dodge; Hannaneh Hajishirzi (CoRR, 2024)

DataDecide: How to Predict Best Pretraining Data with Small Experiments. - Ian Magnusson; Nguyen Tai; Ben Bogin; David Heineman; Jena D. Hwang; Luca Soldaini; Akshita Bhagia; Jiacheng Liu 010; Dirk Groeneveld; Oyvind Tafjord; Noah A. Smith; Pang Wei Koh; et al. (CoRR, 2025)

Evaluating LLMs on Chinese Idiom Translation. - Cai Yang; Yao Dou; David Heineman; Xiaofeng Wu; Wei Xu 004 (CoRR, 2025)

Signal and Noise: A Framework for Reducing Uncertainty in Language Model Evaluation. - David Heineman; Valentin Hofmann; Ian Magnusson; Yuling Gu; Noah A. Smith; Hannaneh Hajishirzi; Kyle Lo; Jesse Dodge (CoRR, 2025)