Cut the CARP: Fishing for zero-shot story evaluation. - Shahbuland Matiana; J. R. Smith; Ryan Teehan; Louis Castricato; Stella Biderman; Leo Gao; Spencer Frazier (CoRR, 2021)

Multitask Prompted Training Enables Zero-Shot Task Generalization. - Victor Sanh; Albert Webson; Colin Raffel; Stephen H. Bach; Lintang Sutawika; Zaid Alyafeai; Antoine Chaffin; Arnaud Stiegler; Teven Le Scao; Arun Raja; Manan Dey; M. Saiful Bari; et al. (CoRR, 2021)

NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation. - Kaustubh D. Dhole; Varun Gangal; Sebastian Gehrmann; Aadesh Gupta; Zhenhao Li; Saad Mahamood; Abinaya Mahendiran; Simon Mille; Ashish Srivastava; Samson Tan; Tongshuang Wu; Jascha Sohl-Dickstein; et al. (CoRR, 2021)

Multitask Prompted Training Enables Zero-Shot Task Generalization. - Victor Sanh; Albert Webson; Colin Raffel; Stephen H. Bach; Lintang Sutawika; Zaid Alyafeai; Antoine Chaffin; Arnaud Stiegler; Arun Raja; Manan Dey; M Saiful Bari; Canwen Xu; et al. (ICLR, 2022)

Socratic Questioning of Novice Debuggers: A Benchmark Dataset and Preliminary Evaluations. - Erfan Al-Hossami; Razvan C. Bunescu; Ryan Teehan; Laurel Powell; Khyati Mahajan; Mohsen Dorodchi (BEA@ACL, 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)

ProCreate, Don't Reproduce! Propulsive Energy Diffusion for Creative Generation. - Jack Lu; Ryan Teehan; Mengye Ren (ECCV (60), 2024)

Can Language Models Employ the Socratic Method? Experiments with Code Debugging. - Erfan Al-Hossami; Razvan C. Bunescu; Justin Smith 008; Ryan Teehan (SIGCSE (1), 2024)

CoLLEGe: Concept Embedding Generation for Large Language Models. - Ryan Teehan; Brenden M. Lake; Mengye Ren (CoRR, 2024)

Are LLMs Prescient? A Continuous Evaluation using Daily News as the Oracle. - Hui Dai; Ryan Teehan; Mengye Ren (CoRR, 2024)

A General Framework for Inference-time Scaling and Steering of Diffusion Models. - Raghav Singhal; Zachary Horvitz; Ryan Teehan; Mengye Ren; Zhou Yu; Kathleen McKeown; Rajesh Ranganath (CoRR, 2025)

Context Tuning for In-Context Optimization. - Jack Lu; Ryan Teehan; Zhenbang Yang; Mengye Ren (CoRR, 2025)