Invertable Frowns: Video-to-Video Facial Emotion Translation. - Ian Magnusson; Aruna Sankaranarayanan; Andrew Lippman (ADGD @ ACM Multimedia, 2021)

Exploring The Landscape of Distributional Robustness for Question Answering Models. - Anas Awadalla; Mitchell Wortsman; Gabriel Ilharco; Sewon Min; Ian Magnusson; Hannaneh Hajishirzi; Ludwig Schmidt (EMNLP (Findings), 2022)

Just-DREAM-about-it: Figurative Language Understanding with DREAM-FLUTE. - Yuling Gu; Yao Fu; Valentina Pyatkin; Ian Magnusson; Bhavana Dalvi Mishra; Peter Clark (CoRR, 2022)

Reproducibility in NLP: What Have We Learned from the Checklist? - Ian Magnusson; Noah A. Smith; Jesse Dodge (ACL (Findings), 2023)

What's In My Big Data? - Yanai Elazar; Akshita Bhagia; Ian Magnusson; Abhilasha Ravichander; Dustin Schwenk; Alane Suhr; Pete Walsh; Dirk Groeneveld; Luca Soldaini; Sameer Singh 001; Hanna Hajishirzi; Noah A. Smith; et al. (CoRR, 2023)

Catwalk: A Unified Language Model Evaluation Framework for Many Datasets. - Dirk Groeneveld; Anas Awadalla; Iz Beltagy; Akshita Bhagia; Ian Magnusson; Hao Peng 009; Oyvind Tafjord; Pete Walsh; Kyle Richardson 001; Jesse Dodge (CoRR, 2023)

OLMo: Accelerating the Science of Language Models. - Dirk Groeneveld; Iz Beltagy; Evan Pete Walsh; Akshita Bhagia; Rodney Kinney; Oyvind Tafjord; Ananya Harsh Jha; Hamish Ivison; Ian Magnusson; Yizhong Wang; Shane Arora; David Atkinson; et al. (ACL (1), 2024)

Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research. - Luca Soldaini; Rodney Kinney; Akshita Bhagia; Dustin Schwenk; David Atkinson; Russell Authur; Ben Bogin; Khyathi Raghavi Chandu; Jennifer Dumas; Yanai Elazar; Valentin Hofmann; Ananya Harsh Jha; et al. (ACL (1), 2024)

Scalable Data Ablation Approximations for Language Models through Modular Training and Merging. - Clara Na; Ian Magnusson; Ananya Harsh Jha; Tom Sherborne; Emma Strubell; Jesse Dodge; Pradeep Dasigi (EMNLP, 2024)

What's In My Big Data? - Yanai Elazar; Akshita Bhagia; Ian Magnusson; Abhilasha Ravichander; Dustin Schwenk; Alane Suhr; Evan Pete Walsh; Dirk Groeneveld; Luca Soldaini; Sameer Singh 001; Hannaneh Hajishirzi; Noah A. Smith; et al. (ICLR, 2024)

Paloma: A Benchmark for Evaluating Language Model Fit. - Ian Magnusson; Akshita Bhagia; Valentin Hofmann; Luca Soldaini; Ananya Harsh Jha; Oyvind Tafjord; Dustin Schwenk; Evan Pete Walsh; Yanai Elazar; Kyle Lo; Dirk Groeneveld; Iz Beltagy; et al. (NeurIPS, 2024)

OLMo: Accelerating the Science of Language Models. - Dirk Groeneveld; Iz Beltagy; Pete Walsh; Akshita Bhagia; Rodney Kinney; Oyvind Tafjord; Ananya Harsh Jha; Hamish Ivison; Ian Magnusson; Yizhong Wang; Shane Arora; David Atkinson; et al. (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)

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)