activity
20192025
most citedOLMo: Accelerating the Science of Language Models

11 citations · 24 across the 8 of their papers we have counts for

collaborators

9 papers

cs.CL2025★ 2 cited

Olmo 3

Team Olmo, :, Allyson Ettinger +66

We introduce Olmo 3, a family of state-of-the-art, fully-open language models at the 7B and 32B parameter scales. Olmo 3 model construction targets long-context reasoning, function…

cs.LG2025

Critical Batch Size Revisited: A Simple Empirical Approach to Large-Batch Language Model Training

William Merrill, Shane Arora, Dirk Groeneveld +1

The right batch size is important when training language models at scale: a large batch size is necessary for fast training, but a batch size that is too large will harm token effi…

cs.CL2025★ 2 cited

2 OLMo 2 Furious

Team OLMo, Pete Walsh, Luca Soldaini +40

We present OLMo 2, the next generation of our fully open language models. OLMo 2 includes a family of dense autoregressive language models at 7B, 13B and 32B scales with fully rele…

cs.CL2024★ 7 cited

OLMoE: Open Mixture-of-Experts Language Models

Niklas Muennighoff, Luca Soldaini, Dirk Groeneveld +21

We introduce OLMoE, a fully open, state-of-the-art language model leveraging sparse Mixture-of-Experts (MoE). OLMoE-1B-7B has 7 billion (B) parameters but uses only 1B per input to…

cs.CL2024

CaLMQA: Exploring culturally specific long-form question answering across 23 languages

Shane Arora, Marzena Karpinska, Hung-Ting Chen +3

Despite rising global usage of large language models (LLMs), their ability to generate long-form answers to culturally specific questions remains unexplored in many languages. To f…

cs.CL2024★ 11 cited

OLMo: Accelerating the Science of Language Models

Dirk Groeneveld, Iz Beltagy, Pete Walsh +40

Language models (LMs) have become ubiquitous in both NLP research and in commercial product offerings. As their commercial importance has surged, the most powerful models have beco…

cs.CL2023

Understanding Retrieval Augmentation for Long-Form Question Answering

Hung-Ting Chen, Fangyuan Xu, Shane Arora +1

How retrieved documents are used in language models (LMs) for long-form generation task is understudied. We present two controlled studies on retrieval-augmented LM for long-form q…

math.FA2020

Solution branches of nonlinear eigenvalue problems on restricted domains

Shane Arora

We extend bifurcation results of nonlinear eigenvalue problems from real Banach spaces to any neighbourhood of a given point. For points of odd multiplicity on these restricted dom…

math.FA2019★ 2 cited

An alternative approach to Fréchet derivatives

Shane Arora, Hazel Browne, Daniel Daners

We discuss an alternative approach to Fréchet derivatives on Banach spaces inspired by a characterisation of derivatives due to Carathéodory. The approach allows us to reduce many…