---
title: "Colin Raffel — papers"
description: "Colin Raffel: 12 papers in the Elamur Research library (2019–2024) — our summary of each, its ideas, references and who cites it."
canonical: "https://research.elamur.ai/free/en/authors/colin-raffel/"
---
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# Colin Raffel

12 papers on this site (2019–2024)

[OpenAlex](https://openalex.org/A5045077843) · [ORCID](https://orcid.org/0000-0002-5009-8048) · h-index 48 · 152 works · 23785 citations (openalex-snapshot, 2026-10-14)

Profile data from OpenAlex; authors with the same name are not always told apart.

- [The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale](https://md.research.elamur.ai/free/en/papers/penedo-2024-fineweb-datasets-decanting-web-finest/) — Guilherme Penedo, Hynek Kydlíček, Loubna Ben allal, et al. · 2024
- [An Empirical Survey of Data Augmentation for Limited Data Learning in NLP](https://md.research.elamur.ai/free/en/papers/chen-2023-empirical-survey-data-augmentation-limited/) — Jiaao Chen, Derek Tam, Colin Raffel, et al. · 2023
- [TIES-Merging: Resolving Interference When Merging Models](https://md.research.elamur.ai/free/en/papers/yadav-2023-ties-merging-resolving-interference-merging/) — Prateek Yadav, Derek Tam, Leshem Choshen, et al. · 2023
- [Deduplicating Training Data Mitigates Privacy Risks in Language Models](https://md.research.elamur.ai/free/en/papers/kandpal-2022-deduplicating-training-data-mitigates-privacy/) — Nikhil Kandpal, Eric Wallace, Colin Raffel · 2022
- [Emergent Abilities of Large Language Models](https://md.research.elamur.ai/free/en/papers/wei-2022-emergent-abilities-large-language-models/) — Jason Wei, Yi Tay, Rishi Bommasani, et al. · 2022
- [Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning](https://md.research.elamur.ai/free/en/papers/liu-2022-few-shot-parameter-efficient-fine/) — Haokun Liu, Derek Tam, Mohammed Muqeeth, et al. · 2022
- [Large Language Models Struggle to Learn Long-Tail Knowledge](https://md.research.elamur.ai/free/en/papers/kandpal-2022-large-language-models-struggle-learn/) — Nikhil Kandpal, Haikang Deng, Adam Roberts, et al. · 2022
- [PromptSource: An Integrated Development Environment and Repository for Natural Language Prompts](https://md.research.elamur.ai/free/en/papers/bach-2022-promptsource-integrated-development-environment-repository/) — Stephen H. Bach, Victor Sanh, Zheng-Xin Yong, et al. · 2022
- [Merging Models with Fisher-Weighted Averaging](https://md.research.elamur.ai/free/en/papers/matena-2021-merging-models-fisher-weighted-averaging/) — Michael Matena, Colin Raffel · 2021
- [Multitask Prompted Training Enables Zero-Shot Task Generalization](https://md.research.elamur.ai/free/en/papers/sanh-2021-multitask-prompted-training-enables-zero/) — Victor Sanh, Albert Webson, Colin Raffel, et al. · 2021
- [Extracting Training Data from Large Language Models](https://md.research.elamur.ai/free/en/papers/carlini-2020-extracting-training-data-large-language/) — Nicholas Carlini, Florian Tramer, Eric Wallace, et al. · 2020
- [Monotonic Infinite Lookback Attention for Simultaneous Machine Translation](https://md.research.elamur.ai/free/en/papers/arivazhagan-2019-monotonic-infinite-lookback-attention-simultaneous/) — Naveen Arivazhagan, Colin Cherry, Wolfgang Macherey, et al. · 2019