Cohan, Arman

SciBERT: A Pretrained Language Model for Scientific Text

Beltagy, I., Lo, K., & Cohan, A. (2019) · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)

Topic ModelingMultimodal Machine Learning Applications

Cited by 3,218

Longformer: The Long-Document Transformer

Beltagy, I., Peters, M. E., & Cohan, A. (2020) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 2,281

A Discourse-Aware Attention Model for Abstractive Summarization of Long Documents

Cohan, A., Dernoncourt, F., Kim, D. S., Bui, T., Kim, S., Chang, W., & Goharian, N. (2018) · Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers)

Topic ModelingAdvanced Text Analysis Techniques

Cited by 658

Fact or Fiction: Verifying Scientific Claims

Wadden, D., Lin, S., Lo, K., Wang, L. L., van Zuylen, M., Cohan, A., & Hajishirzi, H. (2020) · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)

Misinformation and Its ImpactsTopic Modeling

Cited by 382

MedAgents: Large Language Models as Collaborators for Zero-shot Medical Reasoning

Tang, X., Zou, A., Zhang, Z., Li, Z., Zhao, Y., Zhang, X., Cohan, A., & Gerstein, M. (2024) · Findings of the Association for Computational Linguistics ACL 2024

Artificial Intelligence in Healthcare and EducationMultimodal Machine Learning Applications

Cited by 376

Structural Scaffolds for Citation Intent Classification in Scientific Publications

Cohan, A., Ammar, W., van Zuylen, M., & Cady, F. (2019) · Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)

scientometrics and bibliometrics researchAcademic Writing and Publishing

Cited by 214

TLDR: Extreme Summarization of Scientific Documents

Cachola, I., Lo, K., Cohan, A., & Weld, D. (2020) · Findings of the Association for Computational Linguistics: EMNLP 2020

Advanced Text Analysis TechniquesTopic Modeling

Cited by 169

A Dataset of Information-Seeking Questions and Answers Anchored in Research Papers

Dasigi, P., Lo, K., Beltagy, I., Cohan, A., Smith, N. A., & Gardner, M. (2021) · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

Topic ModelingInformation Retrieval and Search Behavior

Cited by 138

Measuring what Matters: Construct Validity in Large Language Model Benchmarks

Bean, A. M., Kearns, R. O., Romanou, A., Hafner, F. S., Mayne, H., Batzner, J., Foroutan Eghlidi, N., Schmitz, C., Korgul, K., Batra, H., et al. (2025) · Advances in Neural Information Processing Systems 38

Topic ModelingNatural Language Processing Techniques

Cited by 110

SciRepEval: A Multi-Format Benchmark for Scientific Document Representations

Singh, A., D'Arcy, M., Cohan, A., Downey, D., & Feldman, S. (2022) · arXiv

Topic ModelingInformation Retrieval and Search Behavior

Cited by 76

OLMo: Accelerating the Science of Language Models

Groeneveld, D., Beltagy, I., Walsh, E., Bhagia, A., Kinney, R., Tafjord, O., Jha, A., Ivison, H., Magnusson, I., Wang, Y., et al. (2024) · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Topic ModelingNatural Language Processing Techniques

Cited by 70

The Semantic Scholar Open Data Platform

Kinney, R., Anastasiades, C., Authur, R., Beltagy, I., Bragg, J., Buraczynski, A., Cachola, I., Candra, S., Chandrasekhar, Y., Cohan, A., et al. (2023) · arXiv

scientometrics and bibliometrics researchSemantic Web and Ontologies

Cited by 64

MultiVerS: Improving scientific claim verification with weak supervision and full-document context

Wadden, D., Lo, K., Wang, L., Cohan, A., Beltagy, I., & Hajishirzi, H. (2022) · Findings of the Association for Computational Linguistics: NAACL 2022

Misinformation and Its ImpactsTopic Modeling

Cited by 60

Investigating Data Contamination in Modern Benchmarks for Large Language Models

Deng, C., Zhao, Y., Tang, X., Gerstein, M., & Cohan, A. (2024) · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)

Topic ModelingNatural Language Processing Techniques

Cited by 45

SciBERT: A Pretrained Language Model for Scientific Text

Beltagy, I., Lo, K., & Cohan, A. (2019) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 41

SciFact-Open: Towards open-domain scientific claim verification

Wadden, D., Lo, K., Kuehl, B., Cohan, A., Beltagy, I., Wang, L. L., & Hajishirzi, H. (2022) · Findings of the Association for Computational Linguistics: EMNLP 2022

Topic ModelingMisinformation and Its Impacts

Cited by 35

SciFact-Open: Towards open-domain scientific claim verification

Wadden, D., Lo, K., Kuehl, B., Cohan, A., Beltagy, I., Wang, L. L., & Hajishirzi, H. (2022) · arXiv

Topic ModelingMisinformation and Its Impacts

Cited by 35

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

Krishna, K., Bransom, E., Kuehl, B., Iyyer, M., Dasigi, P., Cohan, A., & Lo, K. (2023) · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics

Topic ModelingAdvanced Text Analysis Techniques

Cited by 29

Survey on Evaluation of LLM-based Agents

Yehudai, A., Eden, L., Li, A., Uziel, G., Zhao, Y., Bar-Haim, R., Cohan, A., & Shmueli-Scheuer, M. (2025) · arXiv

AI-based Problem Solving and PlanningArtificial Intelligence Applications

Cited by 26

Contextualizing Citations for Scientific Summarization using Word Embeddings and Domain Knowledge

Cohan, A., & Goharian, N. (2017) · Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval

Advanced Text Analysis TechniquesTopic Modeling

Cited by 23

OLMo: Accelerating the Science of Language Models

Groeneveld, D., Beltagy, I., Walsh, P., Bhagia, A., Kinney, R., Tafjord, O., Jha, A. H., Ivison, H., Magnusson, I., Wang, Y., et al. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 10

M3SciQA: A Multi-Modal Multi-Document Scientific QA Benchmark for Evaluating Foundation Models

Li, C., Shangguan, Z., Zhao, Y., Li, D., Liu, Y., & Cohan, A. (2024) · Findings of the Association for Computational Linguistics: EMNLP 2024

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 8

Enhancing Few-shot Text-to-SQL Capabilities of Large Language Models: A Study on Prompt Design Strategies

Nan, L., Zhao, Y., Zou, W., Ri, N., Tae, J., Zhang, E., Cohan, A., & Radev, D. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 8

Investigating Data Contamination in Modern Benchmarks for Large Language Models

Deng, C., Zhao, Y., Tang, X., Gerstein, M., & Cohan, A. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 8