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Ryan Teehan
Ryan Teehan
Charles River Analytics
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Year
Multitask prompted training enables zero-shot task generalization
V Sanh, A Webson, C Raffel, SH Bach, L Sutawika, Z Alyafeai, A Chaffin, ...
arXiv preprint arXiv:2110.08207, 2021
12482021
Bloom: A 176b-parameter open-access multilingual language model
T Le Scao, A Fan, C Akiki, E Pavlick, S Ilić, D Hesslow, R Castagné, ...
11922023
Beyond the imitation game: Quantifying and extrapolating the capabilities of language models
A Srivastava, A Rastogi, A Rao, AAM Shoeb, A Abid, A Fisch, AR Brown, ...
arXiv preprint arXiv:2206.04615, 2022
7562022
Nl-augmenter: A framework for task-sensitive natural language augmentation
KD Dhole, V Gangal, S Gehrmann, A Gupta, Z Li, S Mahamood, ...
arXiv preprint arXiv:2112.02721, 2021
652021
Emergent structures and training dynamics in large language models
R Teehan, M Clinciu, O Serikov, E Szczechla, N Seelam, S Mirkin, ...
Proceedings of BigScience Episode# 5--Workshop on Challenges & Perspectives …, 2022
132022
Cut the carp: Fishing for zero-shot story evaluation
S Matiana, JR Smith, R Teehan, L Castricato, S Biderman, L Gao, ...
arXiv preprint arXiv:2110.03111, 2021
122021
Socratic questioning of novice debuggers: A benchmark dataset and preliminary evaluations
E Al-Hossami, R Bunescu, R Teehan, L Powell, K Mahajan, M Dorodchi
Proceedings of the 18th Workshop on Innovative Use of NLP for Building …, 2023
102023
Multitask prompted training enables zero-shot task generalization. arXiv
V Sanh, A Webson, C Raffel, SH Bach, L Sutawika, Z Alyafeai, A Chaffin, ...
arXiv preprint arXiv:2110.08207, 2021
102021
CoLLEGe: Concept Embedding Generation for Large Language Models
R Teehan, B Lake, M Ren
arXiv preprint arXiv:2403.15362, 2024
12024
Can language models employ the socratic method? experiments with code debugging
E Al-Hossami, R Bunescu, J Smith, R Teehan
Proceedings of the 55th ACM Technical Symposium on Computer Science …, 2024
12024
SPICES: SURVEY PAPERS AS INTERACTIVE CHEATSHEET EMBEDDINGS
M McAteer, R Teehan
Beyond static papers: Rethinking how we share scientific understanding in ML …, 2021
2021
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