3 papers
cs.CY2026
A Human-Centric Framework for Data Attribution in Large Language Models
Amelie Wührl, Mattes Ruckdeschel, Kyle Lo +1
In the current Large Language Model (LLM) ecosystem, creators have little agency over how their data is used, and LLM users may find themselves unknowingly plagiarizing existing so…
cs.LG2024
The Responsible Foundation Model Development Cheatsheet: A Review of Tools & Resources
Shayne Longpre, Stella Biderman, Alon Albalak +20
Foundation model development attracts a rapidly expanding body of contributors, scientists, and applications. To help shape responsible development practices, we introduce the Foun…
cs.LG2024
DataComp-LM: In search of the next generation of training sets for language models
Jeffrey Li, Alex Fang, Georgios Smyrnis +56
We introduce DataComp for Language Models (DCLM), a testbed for controlled dataset experiments with the goal of improving language models. As part of DCLM, we provide a standardize…