activity
20212026
most citedThe Semantic Scholar Open Data Platform

59 citations · 102 across the 21 of their papers we have counts for

collaborators

21 papers

cs.LG2026

Olmo Hybrid: From Theory to Practice and Back

William Merrill, Yanhong Li, Tyler Romero +19

Recent work has demonstrated the potential of non-transformer language models, especially linear recurrent neural networks (RNNs) and hybrid models that mix recurrence and attentio…

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.CL2025

OLMoTrace: Tracing Language Model Outputs Back to Trillions of Training Tokens

Jiacheng Liu, Taylor Blanton, Yanai Elazar +28

We present OLMoTrace, the first system that traces the outputs of language models back to their full, multi-trillion-token training data in real time. OLMoTrace finds and shows ver…

cs.CL2024★ 1 cited

CHIME: LLM-Assisted Hierarchical Organization of Scientific Studies for Literature Review Support

Chao-Chun Hsu, Erin Bransom, Jenna Sparks +5

Literature review requires researchers to synthesize a large amount of information and is increasingly challenging as the scientific literature expands. In this work, we investigat…

cs.CL2024

OLMES: A Standard for Language Model Evaluations

Yuling Gu, Oyvind Tafjord, Bailey Kuehl +3

Progress in AI is often demonstrated by new models claiming improved performance on tasks measuring model capabilities. Evaluating language models can be particularly challenging,…

cs.CL2024

KIWI: A Dataset of Knowledge-Intensive Writing Instructions for Answering Research Questions

Fangyuan Xu, Kyle Lo, Luca Soldaini +3

Large language models (LLMs) adapted to follow user instructions are now widely deployed as conversational agents. In this work, we examine one increasingly common instruction-foll…

cs.CL2023

CARE: Extracting Experimental Findings From Clinical Literature

Aakanksha Naik, Bailey Kuehl, Erin Bransom +2

Extracting fine-grained experimental findings from literature can provide dramatic utility for scientific applications. Prior work has developed annotation schemas and datasets for…

cs.CL2023★ 1 cited

ARIES: A Corpus of Scientific Paper Edits Made in Response to Peer Reviews

Mike D'Arcy, Alexis Ross, Erin Bransom +4

We introduce the task of automatically revising scientific papers based on peer feedback and release ARIES, a dataset of review comments and their corresponding paper edits. The da…

cs.CL2023★ 3 cited

Automated Metrics for Medical Multi-Document Summarization Disagree with Human Evaluations

Lucy Lu Wang, Yulia Otmakhova, Jay DeYoung +4

Evaluating multi-document summarization (MDS) quality is difficult. This is especially true in the case of MDS for biomedical literature reviews, where models must synthesize contr…

cs.CL2023

S2abEL: A Dataset for Entity Linking from Scientific Tables

Yuze Lou, Bailey Kuehl, Erin Bransom +3

Entity linking (EL) is the task of linking a textual mention to its corresponding entry in a knowledge base, and is critical for many knowledge-intensive NLP applications. When app…

cs.HC2023★ 8 cited

The Semantic Reader Project: Augmenting Scholarly Documents through AI-Powered Interactive Reading Interfaces

Kyle Lo, Joseph Chee Chang, Andrew Head +52

Scholarly publications are key to the transfer of knowledge from scholars to others. However, research papers are information-dense, and as the volume of the scientific literature…

cs.CL2023★ 3 cited

LongEval: Guidelines for Human Evaluation of Faithfulness in Long-form Summarization

Kalpesh Krishna, Erin Bransom, Bailey Kuehl +4

While human evaluation remains best practice for accurately judging the faithfulness of automatically-generated summaries, few solutions exist to address the increased difficulty a…

cs.DL2023★ 59 cited

The Semantic Scholar Open Data Platform

Rodney Kinney, Chloe Anastasiades, Russell Authur +45

The volume of scientific output is creating an urgent need for automated tools to help scientists keep up with developments in their field. Semantic Scholar (S2) is an open data pl…

cs.CL2022★ 4 cited

SciFact-Open: Towards open-domain scientific claim verification

David Wadden, Kyle Lo, Bailey Kuehl +4

While research on scientific claim verification has led to the development of powerful systems that appear to approach human performance, these approaches have yet to be tested in…

cs.CL2022

ACCoRD: A Multi-Document Approach to Generating Diverse Descriptions of Scientific Concepts

Sonia K. Murthy, Kyle Lo, Daniel King +7

Systems that can automatically define unfamiliar terms hold the promise of improving the accessibility of scientific texts, especially for readers who may lack prerequisite backgro…

cs.CL2022★ 1 cited

Generating Scientific Claims for Zero-Shot Scientific Fact Checking

Dustin Wright, David Wadden, Kyle Lo +4

Automated scientific fact checking is difficult due to the complexity of scientific language and a lack of significant amounts of training data, as annotation requires domain exper…

cs.CL2021

A Search Engine for Discovery of Scientific Challenges and Directions

Dan Lahav, Jon Saad Falcon, Bailey Kuehl +8

Keeping track of scientific challenges, advances and emerging directions is a fundamental part of research. However, researchers face a flood of papers that hinders discovery of im…

cs.CL2021★ 3 cited

MultiCite: Modeling realistic citations requires moving beyond the single-sentence single-label setting

Anne Lauscher, Brandon Ko, Bailey Kuehl +4

Citation context analysis (CCA) is an important task in natural language processing that studies how and why scholars discuss each others' work. Despite decades of study, tradition…

cs.CL2021

VILA: Improving Structured Content Extraction from Scientific PDFs Using Visual Layout Groups

Zejiang Shen, Kyle Lo, Lucy Lu Wang +3

Accurately extracting structured content from PDFs is a critical first step for NLP over scientific papers. Recent work has improved extraction accuracy by incorporating elementary…

cs.DL2021★ 9 cited

Improving the Accessibility of Scientific Documents: Current State, User Needs, and a System Solution to Enhance Scientific PDF Accessibility for Blind and Low Vision Users

Lucy Lu Wang, Isabel Cachola, Jonathan Bragg +7

The majority of scientific papers are distributed in PDF, which pose challenges for accessibility, especially for blind and low vision (BLV) readers. We characterize the scope of t…

cs.CL2021★ 8 cited

MS2: Multi-Document Summarization of Medical Studies

Jay DeYoung, Iz Beltagy, Madeleine van Zuylen +2

To assess the effectiveness of any medical intervention, researchers must conduct a time-intensive and highly manual literature review. NLP systems can help to automate or assist i…