collaborators

8 papers

cs.CL2025

PolyPythias: Stability and Outliers across Fifty Language Model Pre-Training Runs

Oskar van der Wal, Pietro Lesci, Max Muller-Eberstein +4

The stability of language model pre-training and its effects on downstream performance are still understudied. Prior work shows that the training process can yield significantly di…

cs.LG2025

Humanity's Last Exam

Long Phan, Alice Gatti, Ziwen Han +1144

Benchmarks are important tools for tracking the rapid advancements in large language model (LLM) capabilities. However, benchmarks are not keeping pace in difficulty: LLMs now achi…

cs.CL20241 cited

Self-Directed Synthetic Dialogues and Revisions Technical Report

Nathan Lambert, Hailey Schoelkopf, Aaron Gokaslan +3

Synthetic data has become an important tool in the fine-tuning of language models to follow instructions and solve complex problems. Nevertheless, the majority of open data to date…

cs.CL202413 cited

Consent in Crisis: The Rapid Decline of the AI Data Commons

Shayne Longpre, Robert Mahari, Ariel Lee +46

General-purpose artificial intelligence (AI) systems are built on massive swathes of public web data, assembled into corpora such as C4, RefinedWeb, and Dolma. To our knowledge, we…

cs.CL2024

From Decoding to Meta-Generation: Inference-time Algorithms for Large Language Models

Sean Welleck, Amanda Bertsch, Matthew Finlayson +5

One of the most striking findings in modern research on large language models (LLMs) is that scaling up compute during training leads to better results. However, less attention has…

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…