TFX: A TensorFlow-Based Production-Scale Machine Learning Platform. - Denis Baylor; Eric Breck; Heng-Tze Cheng; Noah Fiedel; Chuan Yu Foo; Zakaria Haque; Salem Haykal; Mustafa Ispir; Vihan Jain; Levent Koc 001; Chiu Yuen Koo; Lukasz Lew; et al. (KDD, 2017)

TensorFlow-Serving: Flexible, High-Performance ML Serving. - Christopher Olston; Noah Fiedel; Kiril Gorovoy; Jeremiah Harmsen; Li Lao; Fangwei Li; Vinu Rajashekhar; Sukriti Ramesh; Jordan Soyke (CoRR, 2017)

Towards a Human-like Open-Domain Chatbot. - Daniel Adiwardana; Minh-Thang Luong; David R. So; Jamie Hall; Noah Fiedel; Romal Thoppilan; Zi Yang; Apoorv Kulshreshtha; Gaurav Nemade; Yifeng Lu; Quoc V. Le (CoRR, 2020)

WT5?! Training Text-to-Text Models to Explain their Predictions. - Sharan Narang; Colin Raffel; Katherine Lee; Adam Roberts; Noah Fiedel; Karishma Malkan (CoRR, 2020)

Do Transformer Modifications Transfer Across Implementations and Applications? - Sharan Narang; Hyung Won Chung; Yi Tay; Liam Fedus; Thibault Févry; Michael Matena; Karishma Malkan; Noah Fiedel; Noam Shazeer; Zhenzhong Lan; Yanqi Zhou; Wei Li 133; et al. (EMNLP (1), 2021)

Scaling Up Models and Data with t5x and seqio. - Adam Roberts; Hyung Won Chung; Anselm Levskaya; Gaurav Mishra; James Bradbury; Daniel Andor; Sharan Narang; Brian Lester; Colin Gaffney; Afroz Mohiuddin; Curtis Hawthorne; Aitor Lewkowycz; et al. (CoRR, 2022)

TALM: Tool Augmented Language Models. - Aaron Parisi; Yao Zhao; Noah Fiedel (CoRR, 2022)

Understanding HTML with Large Language Models. - Izzeddin Gur; Ofir Nachum; Yingjie Miao; Mustafa Safdari; Austin V. Huang; Aakanksha Chowdhery; Sharan Narang; Noah Fiedel; Aleksandra Faust (EMNLP (Findings), 2023)

Levels of AGI: Operationalizing Progress on the Path to AGI. - Meredith Ringel Morris; Jascha Sohl-Dickstein; Noah Fiedel; Tris Warkentin; Allan Dafoe; Aleksandra Faust; Clément Farabet; Shane Legg (CoRR, 2023)

Frontier Language Models are not Robust to Adversarial Arithmetic, or "What do I need to say so you agree 2+2=5? - C. Daniel Freeman; Laura Culp; Aaron Parisi; Maxwell L. Bileschi; Gamaleldin F. Elsayed; Alex Rizkowsky; Isabelle Simpson; Alex Alemi; Azade Nova; Ben Adlam; Bernd Bohnet; Gaurav Mishra; et al. (CoRR, 2023)

PaLM: Scaling Language Modeling with Pathways. - Aakanksha Chowdhery; Sharan Narang; Jacob Devlin; Maarten Bosma; Gaurav Mishra; Adam Roberts; Paul Barham 001; Hyung Won Chung; Charles Sutton; Sebastian Gehrmann; Parker Schuh; Kensen Shi; et al. (J. Mach. Learn. Res., 2023)

Scaling Up Models and Data with t5x and seqio. - Adam Roberts; Hyung Won Chung; Gaurav Mishra; Anselm Levskaya; James Bradbury; Daniel Andor; Sharan Narang; Brian Lester; Colin Gaffney; Afroz Mohiuddin; Curtis Hawthorne; Aitor Lewkowycz; et al. (J. Mach. Learn. Res., 2023)

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models. - Aarohi Srivastava; Abhinav Rastogi; Abhishek Rao; Abu Awal Md Shoeb; Abubakar Abid; Adam Fisch; Adam R. Brown; Adam Santoro; Aditya Gupta; Adrià Garriga-Alonso; Agnieszka Kluska; Aitor Lewkowycz; et al. (Trans. Mach. Learn. Res., 2023)

Position: Levels of AGI for Operationalizing Progress on the Path to AGI. - Meredith Ringel Morris; Jascha Sohl-Dickstein; Noah Fiedel; Tris Warkentin; Allan Dafoe; Aleksandra Faust; Clément Farabet; Shane Legg (ICML, 2024)

Transfer Learning for Text Diffusion Models. - Kehang Han; Kathleen Kenealy; Aditya Barua; Noah Fiedel; Noah Constant (CoRR, 2024)

RecurrentGemma: Moving Past Transformers for Efficient Open Language Models. - Aleksandar Botev; Soham De; Samuel L. Smith; Anushan Fernando; George-Cristian Muraru; Ruba Haroun; Leonard Berrada; Razvan Pascanu; Pier Giuseppe Sessa; Robert Dadashi; Léonard Hussenot; Johan Ferret; et al. (CoRR, 2024)

Long-Span Question-Answering: Automatic Question Generation and QA-System Ranking via Side-by-Side Evaluation. - Bernd Bohnet; Kevin Swersky; Rosanne Liu; Pranjal Awasthi; Azade Nova; Javier Snaider; Hanie Sedghi; Aaron T. Parisi; Michael Collins 001; Angeliki Lazaridou; Orhan Firat; Noah Fiedel (CoRR, 2024)

Exploring and Benchmarking the Planning Capabilities of Large Language Models. - Bernd Bohnet; Azade Nova; Aaron T. Parisi; Kevin Swersky; Katayoon Goshvadi; Hanjun Dai; Dale Schuurmans; Noah Fiedel; Hanie Sedghi (CoRR, 2024)

Training Language Models on the Knowledge Graph: Insights on Hallucinations and Their Detectability. - Jiri Hron; Laura Culp; Gamaleldin F. Elsayed; Rosanne Liu; Ben Adlam; Maxwell L. Bileschi; Bernd Bohnet; JD Co-Reyes; Noah Fiedel; C. Daniel Freeman; Izzeddin Gur; Kathleen Kenealy; et al. (CoRR, 2024)

Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models. - Avi Singh; John D. Co-Reyes; Rishabh Agarwal; Ankesh Anand; Piyush Patil; Xavier Garcia; Peter J. Liu; James Harrison; Jaehoon Lee 001; Kelvin Xu; Aaron T. Parisi; Abhishek Kumar; et al. (Trans. Mach. Learn. Res., 2024)

Gemma 3 Technical Report. - Aishwarya Kamath; Johan Ferret; Shreya Pathak; Nino Vieillard; Ramona Merhej; Sarah Perrin; Tatiana Matejovicova; Alexandre Ramé; Morgane Rivière; Louis Rouillard; Thomas Mesnard; Geoffrey Cideron; et al. (CoRR, 2025)

Because we have LLMs, we Can and Should Pursue Agentic Interpretability. - Been Kim; John Hewitt; Neel Nanda; Noah Fiedel; Oyvind Tafjord (CoRR, 2025)