The Scientific Method in the Science of Machine Learning. - Jessica Zosa Forde; Michela Paganini (CoRR, 2019)

Individual predictions matter: Assessing the effect of data ordering in training fine-tuned CNNs for medical imaging. - John R. Zech; Jessica Zosa Forde; Michael L. Littman (CoRR, 2019)

On Iterative Neural Network Pruning, Reinitialization, and the Similarity of Masks. - Michela Paganini; Jessica Zosa Forde (CoRR, 2020)

Streamlining Tensor and Network Pruning in PyTorch. - Michela Paganini; Jessica Zosa Forde (CoRR, 2020)

dagger: A Python Framework for Reproducible Machine Learning Experiment Orchestration. - Michela Paganini; Jessica Zosa Forde (CoRR, 2020)

Bespoke vs. Prêt-à-Porter Lottery Tickets: Exploiting Mask Similarity for Trainable Sub-Network Finding. - Michela Paganini; Jessica Zosa Forde (CoRR, 2020)

Virtual, Augmented, and Mixed Reality for Human-Robot Interaction (VAM-HRI). - Eric Rosen; Thomas R. Groechel; Michael E. Walker; Christine T. Chang; Jessica Zosa Forde (HRI (Companion), 2021)

Model Selection's Disparate Impact in Real-World Deep Learning Applications. - Jessica Zosa Forde; A. Feder Cooper; Kweku Kwegyir-Aggrey; Chris De Sa; Michael Littman 002 (CoRR, 2021)

TOKCS: Tool for Organizing Key Characteristics of VAM-HRI Systems. - Thomas R. Groechel; Michael E. Walker; Christine T. Chang; Eric Rosen; Jessica Zosa Forde (CoRR, 2021)

Towards Reproducible Machine Learning Research in Natural Language Processing. - Ana Lucic; Maurits J. R. Bleeker; Samarth Bhargav 001; Jessica Zosa Forde; Koustuv Sinha; Jesse Dodge; Sasha Luccioni; Robert Stojnic (ACL (tutorial), 2022)

Virtual, Augmented, and Mixed Reality for HRI (VAM-HRI). - Christine T. Chang; Eric Rosen; Thomas R. Groechel; Michael E. Walker; Jessica Zosa Forde (HRI, 2022)

Does DQN really learn? Exploring adversarial training schemes in Pong. - Bowen He; Sreehari Rammohan; Jessica Zosa Forde; Michael L. Littman (CoRR, 2022)

Strengthening Subcommunities: Towards Sustainable Growth in AI Research. - Andi Peng; Jessica Zosa Forde; Yonadav Shavit; Jonathan Frankle (CoRR, 2022)

Reduce, Reuse, Recycle: Improving Training Efficiency with Distillation. - Cody Blakeney; Jessica Zosa Forde; Jonathan Frankle; Ziliang Zong; Matthew L. Leavitt (CoRR, 2022)

One Venue, Two Conferences: The Separation of Chinese and American Citation Networks. - Bingchen Zhao; Yuling Gu; Jessica Zosa Forde; Naomi Saphra (CoRR, 2022)

Evaluation Beyond Task Performance: Analyzing Concepts in AlphaZero in Hex. - Charles Lovering; Jessica Zosa Forde; George Konidaris 001; Ellie Pavlick; Michael L. Littman (CoRR, 2022)

A Tool for Organizing Key Characteristics of Virtual, Augmented, and Mixed Reality for Human-Robot Interaction Systems: Synthesizing VAM-HRI Trends and Takeaways. - Thomas R. Groechel; Michael E. Walker; Christine T. Chang; Eric Rosen; Jessica Zosa Forde (IEEE Robotics Autom. Mag., 2022)

Prompting Multilingual Large Language Models to Generate Code-Mixed Texts: The Case of South East Asian Languages. - Zheng Xin Yong; Ruochen Zhang; Jessica Zosa Forde; Skyler Wang; Samuel Cahyawijaya; Holy Lovenia; Genta Indra Winata; Lintang Sutawika; Jan Christian Blaise Cruz; Long Phan; Yin Lin Tan; Alham Fikri Aji (CoRR, 2023)

Surveying (Dis)Parities and Concerns of Compute Hungry NLP Research. - Ji-Ung Lee; Haritz Puerto; Betty van Aken; Yuki Arase; Jessica Zosa Forde; Leon Derczynski; Andreas Rücklé; Iryna Gurevych; Roy Schwartz 001; Emma Strubell; Jesse Dodge (CoRR, 2023)

Efficient Methods for Natural Language Processing: A Survey. - Marcos V. Treviso; Ji-Ung Lee; Tianchu Ji; Betty van Aken; Qingqing Cao; Manuel R. Ciosici; Michael Hassid; Kenneth Heafield; Sara Hooker; Colin Raffel; Pedro Henrique Martins; André F. T. Martins; et al. (Trans. Assoc. Comput. Linguistics, 2023)

Lessons from the Trenches on Reproducible Evaluation of Language Models. - Stella Biderman; Hailey Schoelkopf; Lintang Sutawika; Leo Gao; Jonathan Tow; Baber Abbasi; Alham Fikri Aji; Pawan Sasanka Ammanamanchi; Sidney Black; Jordan Clive; Anthony DiPofi; Julen Etxaniz; et al. (CoRR, 2024)

SHADES: Towards a Multilingual Assessment of Stereotypes in Large Language Models. - Margaret Mitchell; Giuseppe Attanasio; Ioana Baldini; Miruna Clinciu; Jordan Clive; Pieter Delobelle; Manan Dey; Sil Hamilton; Timm Dill; Jad Doughman; Ritam Dutt; Avijit Ghosh; et al. (NAACL (Long Papers), 2025)

Position: Machine Learning Conferences Should Establish a "Refutations and Critiques" Track. - Rylan Schaeffer; Joshua Kazdan; Yegor Denisov-Blanch; Brando Miranda; Matthias Gerstgrasser; Susan Zhang; Andreas Haupt; Isha Gupta; Elyas Obbad; Jesse Dodge; Jessica Zosa Forde; Koustuv Sinha; et al. (CoRR, 2025)