On clinical decision support. - Arman Cohan; Luca Soldaini; Andrew Yates; Nazli Goharian; Ophir Frieder (BCB, 2014)

Query Reformulation for Clinical Decision Support Search. - Luca Soldaini; Arman Cohan; Andrew Yates; Nazli Goharian; Ophir Frieder (TREC, 2014)

Retrieving Medical Literature for Clinical Decision Support. - Luca Soldaini; Arman Cohan; Andrew Yates; Nazli Goharian; Ophir Frieder (ECIR, 2015)

Scientific Article Summarization Using Citation-Context and Article's Discourse Structure. - Arman Cohan; Nazli Goharian (EMNLP, 2015)

Matching Citation Text and Cited Spans in Biomedical Literature: a Search-Oriented Approach. - Arman Cohan; Luca Soldaini; Nazli Goharian (HLT-NAACL, 2015)

Revisiting Summarization Evaluation for Scientific Articles. - Arman Cohan; Nazli Goharian (LREC, 2016)

Triaging Mental Health Forum Posts. - Arman Cohan; Sydney Young; Nazli Goharian (CLPsych@HLT-NAACL, 2016)

GUIR at SemEval-2016 task 12: Temporal Information Processing for Clinical Narratives. - Arman Cohan; Kevin Meurer; Nazli Goharian (SemEval@NAACL-HLT, 2016)

Identifying Harm Events in Clinical Care through Medical Narratives. - Arman Cohan; Allan Fong; Raj M. Ratwani; Nazli Goharian (BCB, 2017)

A Neural Attention Model for Categorizing Patient Safety Events. - Arman Cohan; Allan Fong; Nazli Goharian; Raj M. Ratwani (ECIR, 2017)

Depression and Self-Harm Risk Assessment in Online Forums. - Andrew Yates; Arman Cohan; Nazli Goharian (EMNLP, 2017)

GUIR at SemEval-2017 Task 12: A Framework for Cross-Domain Clinical Temporal Information Extraction. - Sean MacAvaney; Arman Cohan; Nazli Goharian (SemEval@ACL, 2017)

Contextualizing Citations for Scientific Summarization using Word Embeddings and Domain Knowledge. - Arman Cohan; Nazli Goharian (SIGIR, 2017)

Triaging content severity in online mental health forums. - Arman Cohan; Sydney Young; Andrew Yates; Nazli Goharian (J. Assoc. Inf. Sci. Technol., 2017)

RSDD-Time: Temporal Annotation of Self-Reported Mental Health Diagnoses. - Sean MacAvaney; Bart Desmet; Arman Cohan; Luca Soldaini; Andrew Yates; Ayah Zirikly; Nazli Goharian (CLPsych@NAACL-HTL, 2018)

Helping or Hurting? Predicting Changes in Users' Risk of Self-Harm Through Online Community Interactions. - Luca Soldaini; Timothy Walsh 002; Arman Cohan; Julien Han; Nazli Goharian (CLPsych@NAACL-HTL, 2018)

Relation Extraction for Protein-protein Interactions Affected by Mutations. - Ziling Fan; Luca Soldaini; Arman Cohan; Nazli Goharian (BCB, 2018)

SMHD: a Large-Scale Resource for Exploring Online Language Usage for Multiple Mental Health Conditions. - Arman Cohan; Bart Desmet; Andrew Yates; Luca Soldaini; Sean MacAvaney; Nazli Goharian (COLING, 2018)

A Discourse-Aware Attention Model for Abstractive Summarization of Long Documents. - Arman Cohan; Franck Dernoncourt; Doo Soon Kim; Trung Bui; Seokhwan Kim; Walter Chang; Nazli Goharian (NAACL-HLT (2), 2018)

GU IRLAB at SemEval-2018 Task 7: Tree-LSTMs for Scientific Relation Classification. - Sean MacAvaney; Luca Soldaini; Arman Cohan; Nazli Goharian (SemEval@NAACL-HLT, 2018)

Characterizing Question Facets for Complex Answer Retrieval. - Sean MacAvaney; Andrew Yates; Arman Cohan; Luca Soldaini; Kai Hui 001; Nazli Goharian; Ophir Frieder (SIGIR, 2018)

Scientific document summarization via citation contextualization and scientific discourse. - Arman Cohan; Nazli Goharian (Int. J. Digit. Libr., 2018)

Text Summarization and Categorization for Scientific and Health-Related Data. - Arman Cohan (SIGIR Forum, 2018)

SciBERT: A Pretrained Language Model for Scientific Text. - Iz Beltagy; Kyle Lo; Arman Cohan (EMNLP/IJCNLP (1), 2019)

Pretrained Language Models for Sequential Sentence Classification. - Arman Cohan; Iz Beltagy; Daniel King; Bhavana Dalvi; Daniel S. Weld (EMNLP/IJCNLP (1), 2019)

Structural Scaffolds for Citation Intent Classification in Scientific Publications. - Arman Cohan; Waleed Ammar; Madeleine van Zuylen; Field Cady (NAACL-HLT (1), 2019)

Ontology-Aware Clinical Abstractive Summarization. - Sean MacAvaney; Sajad Sotudeh; Arman Cohan; Nazli Goharian; Ish A. Talati; Ross W. Filice (SIGIR, 2019)

CEDR: Contextualized Embeddings for Document Ranking. - Sean MacAvaney; Andrew Yates; Arman Cohan; Nazli Goharian (SIGIR, 2019)

SciBERT: Pretrained Contextualized Embeddings for Scientific Text. - Iz Beltagy; Arman Cohan; Kyle Lo (CoRR, 2019)

Extracting evidence of supplement-drug interactions from literature. - Lucy Lu Wang; Oyvind Tafjord; Sarthak Jain; Arman Cohan; Sam Skjonsberg; Carissa Schoenick; Nick Botner; Waleed Ammar (CoRR, 2019)

Overcoming low-utility facets for complex answer retrieval. - Sean MacAvaney; Andrew Yates; Arman Cohan; Luca Soldaini; Kai Hui 001; Nazli Goharian; Ophir Frieder (Inf. Retr. J., 2019)

SPECTER: Document-level Representation Learning using Citation-informed Transformers. - Arman Cohan; Sergey Feldman; Iz Beltagy; Doug Downey; Daniel S. Weld (ACL, 2020)

SUPP.AI: finding evidence for supplement-drug interactions. - Lucy Lu Wang; Oyvind Tafjord; Arman Cohan; Sarthak Jain; Sam Skjonsberg; Carissa Schoenick; Nick Botner; Waleed Ammar (ACL (demo), 2020)

Ranking Significant Discrepancies in Clinical Reports. - Sean MacAvaney; Arman Cohan; Nazli Goharian; Ross W. Filice (ECIR (2), 2020)

TLDR: Extreme Summarization of Scientific Documents. - Isabel Cachola; Kyle Lo; Arman Cohan; Daniel S. Weld (EMNLP (Findings), 2020)

GUIR @ LongSumm 2020: Learning to Generate Long Summaries from Scientific Documents. - Sajad Sotudeh Gharebagh; Arman Cohan; Nazli Goharian (SDP@EMNLP, 2020)

SLEDGE-Z: A Zero-Shot Baseline for COVID-19 Literature Search. - Sean MacAvaney; Arman Cohan; Nazli Goharian (EMNLP (1), 2020)

Fact or Fiction: Verifying Scientific Claims. - David Wadden; Shanchuan Lin; Kyle Lo; Lucy Lu Wang; Madeleine van Zuylen; Arman Cohan; Hannaneh Hajishirzi (EMNLP (1), 2020)

Longformer: The Long-Document Transformer. - Iz Beltagy; Matthew E. Peters; Arman Cohan (CoRR, 2020)

SLEDGE: A Simple Yet Effective Baseline for Coronavirus Scientific Knowledge Search. - Sean MacAvaney; Arman Cohan; Nazli Goharian (CoRR, 2020)

On Generating Extended Summaries of Long Documents. - Sajad Sotudeh; Arman Cohan; Nazli Goharian (SDU@AAAI, 2021)

CDLM: Cross-Document Language Modeling. - Avi Caciularu; Arman Cohan; Iz Beltagy; Matthew E. Peters; Arie Cattan; Ido Dagan (EMNLP (Findings), 2021)

A Dataset of Information-Seeking Questions and Answers Anchored in Research Papers. - Pradeep Dasigi; Kyle Lo; Iz Beltagy; Arman Cohan; Noah A. Smith; Matt Gardner 001 (NAACL-HLT, 2021)

FLEX: Unifying Evaluation for Few-Shot NLP. - Jonathan Bragg; Arman Cohan; Kyle Lo; Iz Beltagy (NeurIPS, 2021)

Simplified Data Wrangling with ir_datasets. - Sean MacAvaney; Andrew Yates; Sergey Feldman; Doug Downey; Arman Cohan; Nazli Goharian (SIGIR, 2021)

Cross-Document Language Modeling. - Avi Caciularu; Arman Cohan; Iz Beltagy; Matthew E. Peters; Arie Cattan; Ido Dagan (CoRR, 2021)

PRIMER: Pyramid-based Masked Sentence Pre-training for Multi-document Summarization. - Wen Xiao; Iz Beltagy; Giuseppe Carenini; Arman Cohan (CoRR, 2021)

LongChecker: Improving scientific claim verification by modeling full-abstract context. - David Wadden; Kyle Lo; Lucy Lu Wang; Arman Cohan; Iz Beltagy; Hannaneh Hajishirzi (CoRR, 2021)

Utilizing Evidence Spans via Sequence-Level Contrastive Learning for Long-Context Question Answering. - Avi Caciularu; Ido Dagan; Jacob Goldberger; Arman Cohan (CoRR, 2021)

ParsiNLU: A Suite of Language Understanding Challenges for Persian. - Daniel Khashabi; Arman Cohan; Siamak Shakeri; Pedram Hosseini; Pouya Pezeshkpour; Malihe Alikhani; Moin Aminnaseri; Marzieh Bitaab; Faeze Brahman; Sarik Ghazarian; Mozhdeh Gheini; Arman Kabiri; et al. (Trans. Assoc. Comput. Linguistics, 2021)

Generating Scientific Claims for Zero-Shot Scientific Fact Checking. - Dustin Wright 001; David Wadden; Kyle Lo; Bailey Kuehl; Arman Cohan; Isabelle Augenstein; Lucy Lu Wang (ACL (1), 2022)

Zero- and Few-Shot NLP with Pretrained Language Models. - Iz Beltagy; Arman Cohan; Robert L. Logan IV; Sewon Min; Sameer Singh 001 (ACL (tutorial), 2022)

Improving the Generalizability of Depression Detection by Leveraging Clinical Questionnaires. - Thong Nguyen; Andrew Yates; Ayah Zirikly; Bart Desmet; Arman Cohan (ACL (1), 2022)

PRIMERA: Pyramid-based Masked Sentence Pre-training for Multi-document Summarization. - Wen Xiao; Iz Beltagy; Giuseppe Carenini; Arman Cohan (ACL (1), 2022)

Overview of the Third Workshop on Scholarly Document Processing. - Arman Cohan; Guy Feigenblat; Dayne Freitag; Tirthankar Ghosal; Drahomira Herrmannova; Petr Knoth; Kyle Lo; Philipp Mayr 001; Michal Shmueli-Scheuer; Anita de Waard; Lucy Lu Wang (SDP@COLING, 2022)

Overview of the First Shared Task on Multi Perspective Scientific Document Summarization (MuP). - Arman Cohan; Guy Feigenblat; Tirthankar Ghosal; Michal Shmueli-Scheuer (SDP@COLING, 2022)

SciFact-Open: Towards open-domain scientific claim verification. - David Wadden; Kyle Lo; Bailey Kuehl; Arman Cohan; Iz Beltagy; Lucy Lu Wang; Hannaneh Hajishirzi (EMNLP (Findings), 2022)

Long Context Question Answering via Supervised Contrastive Learning. - Avi Caciularu; Ido Dagan; Jacob Goldberger; Arman Cohan (NAACL-HLT, 2022)

MultiCite: Modeling realistic citations requires moving beyond the single-sentence single-label setting. - Anne Lauscher; Brandon Ko; Bailey Kuehl; Sophie Johnson; Arman Cohan; David Jurgens; Kyle Lo (NAACL-HLT, 2022)

Multi-Vector Models with Textual Guidance for Fine-Grained Scientific Document Similarity. - Sheshera Mysore; Arman Cohan; Tom Hope (NAACL-HLT, 2022)

MultiVerS: Improving scientific claim verification with weak supervision and full-document context. - David Wadden; Kyle Lo; Lucy Lu Wang; Arman Cohan; Iz Beltagy; Hannaneh Hajishirzi (NAACL-HLT (Findings), 2022)

Exploring the Challenges of Open Domain Multi-Document Summarization. - John M. Giorgi; Luca Soldaini; Bo Wang 044; Gary D. Bader; Kyle Lo; Lucy Lu Wang; Arman Cohan (CoRR, 2022)

ABNIRML: Analyzing the Behavior of Neural IR Models. - Sean MacAvaney; Sergey Feldman; Nazli Goharian; Doug Downey; Arman Cohan (Trans. Assoc. Comput. Linguistics, 2022)

Aligning Factual Consistency for Clinical Studies Summarization through Reinforcement Learning. - Xiangru Tang; Arman Cohan; Mark Gerstein (ClinicalNLP@ACL, 2023)

Peek Across: Improving Multi-Document Modeling via Cross-Document Question-Answering. - Avi Caciularu; Matthew E. Peters; Jacob Goldberger; Ido Dagan; Arman Cohan (ACL (1), 2023)

OpenRT: An Open-source Framework for Reasoning Over Tabular Data. - Yilun Zhao 001; Boyu Mi; Zhenting Qi; Linyong Nan; Minghao Guo; Arman Cohan; Dragomir Radev (ACL (demo), 2023)

LongEval: Guidelines for Human Evaluation of Faithfulness in Long-form Summarization. - Kalpesh Krishna; Erin Bransom; Bailey Kuehl; Mohit Iyyer; Pradeep Dasigi; Arman Cohan; Kyle Lo (EACL, 2023)

Embedding Recycling for Language Models. - Jon Saad-Falcon; Amanpreet Singh; Luca Soldaini; Mike D'Arcy; Arman Cohan; Doug Downey (EACL (Findings), 2023)

QTSumm: Query-Focused Summarization over Tabular Data. - Yilun Zhao 001; Zhenting Qi; Linyong Nan; Boyu Mi; Yixin Liu 003; Weijin Zou; Simeng Han; Ruizhe Chen; Xiangru Tang; Yumo Xu; Dragomir Radev; Arman Cohan (EMNLP, 2023)

Investigating Table-to-Text Generation Capabilities of Large Language Models in Real-World Information Seeking Scenarios. - Yilun Zhao 001; Haowei Zhang; Shengyun Si; Linyong Nan; Xiangru Tang; Arman Cohan (EMNLP (Industry Track), 2023)

Medical Text Simplification: Optimizing for Readability with Unlikelihood Training and Reranked Beam Search Decoding. - Lorenzo Jaime Yu Flores; Heyuan Huang; Kejian Shi; Sophie Chheang; Arman Cohan (EMNLP (Findings), 2023)

Open Domain Multi-document Summarization: A Comprehensive Study of Model Brittleness under Retrieval. - John M. Giorgi; Luca Soldaini; Bo Wang 044; Gary D. Bader; Kyle Lo; Lucy Lu Wang; Arman Cohan (EMNLP (Findings), 2023)

Enhancing Text-to-SQL Capabilities of Large Language Models: A Study on Prompt Design Strategies. - Linyong Nan; Yilun Zhao 001; Weijin Zou; Narutatsu Ri; Jaesung Tae; Ellen Zhang; Arman Cohan; Dragomir Radev (EMNLP (Findings), 2023)

A Question Answering Framework for Decontextualizing User-facing Snippets from Scientific Documents. - Benjamin Newman; Luca Soldaini; Raymond Fok; Arman Cohan; Kyle Lo (EMNLP, 2023)

SciRepEval: A Multi-Format Benchmark for Scientific Document Representations. - Amanpreet Singh; Mike D'Arcy; Arman Cohan; Doug Downey; Sergey Feldman (EMNLP, 2023)

The Semantic Scholar Open Data Platform. - Rodney Kinney; Chloe Anastasiades; Russell Authur; Iz Beltagy; Jonathan Bragg; Alexandra Buraczynski; Isabel Cachola; Stefan Candra; Yoganand Chandrasekhar; Arman Cohan; Miles Crawford; Doug Downey; et al. (CoRR, 2023)

Inference-time Re-ranker Relevance Feedback for Neural Information Retrieval. - Revanth Gangi Reddy; Pradeep Dasigi; Md. Arafat Sultan; Arman Cohan; Avirup Sil; Heng Ji; Hannaneh Hajishirzi (CoRR, 2023)

Enhancing Few-shot Text-to-SQL Capabilities of Large Language Models: A Study on Prompt Design Strategies. - Linyong Nan; Yilun Zhao 001; Weijin Zou; Narutatsu Ri; Jaesung Tae; Ellen Zhang; Arman Cohan; Dragomir Radev (CoRR, 2023)

On Learning to Summarize with Large Language Models as References. - Yixin Liu 003; Alexander R. Fabbri; Pengfei Liu 003; Dragomir Radev; Arman Cohan (CoRR, 2023)

QTSumm: A New Benchmark for Query-Focused Table Summarization. - Yilun Zhao 001; Zhenting Qi; Linyong Nan; Boyu Mi; Yixin Liu 003; Weijin Zou; Simeng Han; Xiangru Tang; Yumo Xu; Arman Cohan; Dragomir Radev (CoRR, 2023)

A Controllable QA-based Framework for Decontextualization. - Benjamin Newman; Luca Soldaini; Raymond Fok; Arman Cohan; Kyle Lo (CoRR, 2023)

Large Language Models are Effective Table-to-Text Generators, Evaluators, and Feedback Providers. - Yilun Zhao 001; Haowei Zhang; Shengyun Si; Linyong Nan; Xiangru Tang; Arman Cohan (CoRR, 2023)

ODSum: New Benchmarks for Open Domain Multi-Document Summarization. - Yijie Zhou; Kejian Shi; Wencai Zhang; Yixin Liu 003; Yilun Zhao 001; Arman Cohan (CoRR, 2023)

Struc-Bench: Are Large Language Models Really Good at Generating Complex Structured Data? - Xiangru Tang; Yiming Zong; Jason Phang; Yilun Zhao 001; Wangchunshu Zhou; Arman Cohan; Mark Gerstein (CoRR, 2023)

L2CEval: Evaluating Language-to-Code Generation Capabilities of Large Language Models. - Ansong Ni; Pengcheng Yin; Yilun Zhao 001; Martin Riddell; Troy Feng; Rui Shen; Stephen Yin; Ye Liu 006; Semih Yavuz; Caiming Xiong; Shafiq Joty; Yingbo Zhou; et al. (CoRR, 2023)

Back to Basics: A Simple Recipe for Improving Out-of-Domain Retrieval in Dense Encoders. - Hyunji Lee; Luca Soldaini; Arman Cohan; Minjoon Seo; Kyle Lo (CoRR, 2023)

KnowledgeMath: Knowledge-Intensive Math Word Problem Solving in Finance Domains. - Yilun Zhao 001; Hongjun Liu; Yitao Long; Rui Zhang 037; Chen Zhao; Arman Cohan (CoRR, 2023)

DocMath-Eval: Evaluating Numerical Reasoning Capabilities of LLMs in Understanding Long Documents with Tabular Data. - Yilun Zhao 001; Yitao Long; Hongjun Liu; Linyong Nan; Lyuhao Chen; Ryo Kamoi; Yixin Liu 003; Xiangru Tang; Rui Zhang 037; Arman Cohan (CoRR, 2023)

ML-Bench: Large Language Models Leverage Open-source Libraries for Machine Learning Tasks. - Yuliang Liu; Xiangru Tang; Zefan Cai; Junjie Lu; Yichi Zhang; Yanjun Shao; Zexuan Deng; Helan Hu; Zengxian Yang; Kaikai An; Ruijun Huang; Shuzheng Si; et al. (CoRR, 2023)

MedAgents: Large Language Models as Collaborators for Zero-shot Medical Reasoning. - Xiangru Tang; Anni Zou; Zhuosheng Zhang 001; Yilun Zhao 001; Xingyao Zhang; Arman Cohan; Mark Gerstein (CoRR, 2023)

Observable Propagation: A Data-Efficient Approach to Uncover Feature Vectors in Transformers. - Jacob Dunefsky; Arman Cohan (CoRR, 2023)

TaPERA: Enhancing Faithfulness and Interpretability in Long-Form Table QA by Content Planning and Execution-based Reasoning. - Yilun Zhao 001; Lyuhao Chen; Arman Cohan; Chen Zhao (ACL (1), 2024)

DocMath-Eval: Evaluating Math Reasoning Capabilities of LLMs in Understanding Financial Documents. - Yilun Zhao 001; Yitao Long; Hongjun Liu; Ryo Kamoi; Linyong Nan; Lyuhao Chen; Yixin Liu 003; Xiangru Tang; Rui Zhang 037; Arman Cohan (ACL (1), 2024)

KnowledgeFMath: A Knowledge-Intensive Math Reasoning Dataset in Finance Domains. - Yilun Zhao 001; Hongjun Liu; Yitao Long; Rui Zhang 037; Chen Zhao; Arman Cohan (ACL (1), 2024)

Unveiling the Spectrum of Data Contamination in Language Model: A Survey from Detection to Remediation. - Chunyuan Deng; Yilun Zhao 001; Yuzhao Heng; Yitong Li; Jiannan Cao; Xiangru Tang; Arman Cohan (ACL (Findings), 2024)

OLMo: Accelerating the Science of Language Models. - Dirk Groeneveld; Iz Beltagy; Evan Pete Walsh; Akshita Bhagia; Rodney Kinney; Oyvind Tafjord; Ananya Harsh Jha; Hamish Ivison; Ian Magnusson; Yizhong Wang; Shane Arora; David Atkinson; et al. (ACL (1), 2024)

Rethinking Efficient Multilingual Text Summarization Meta-Evaluation. - Rilyn Han; Jiawen Chen; Yixin Liu 003; Arman Cohan (ACL (Findings), 2024)

Quantifying Contamination in Evaluating Code Generation Capabilities of Language Models. - Martin Riddell; Ansong Ni; Arman Cohan (ACL (1), 2024)

MedAgents: Large Language Models as Collaborators for Zero-shot Medical Reasoning. - Xiangru Tang; Anni Zou; Zhuosheng Zhang 001; Ziming Li; Yilun Zhao 001; Xingyao Zhang; Arman Cohan; Mark Gerstein (ACL (Findings), 2024)

On the Benefits of Fine-Grained Loss Truncation: A Case Study on Factuality in Summarization. - Lorenzo Jaime Flores; Arman Cohan (EACL (2), 2024)

TESS: Text-to-Text Self-Conditioned Simplex Diffusion. - Rabeeh Karimi Mahabadi; Hamish Ivison; Jaesung Tae; James Henderson 001; Iz Beltagy; Matthew E. Peters; Arman Cohan (EACL (1), 2024)

When do Generative Query and Document Expansions Fail? A Comprehensive Study Across Methods, Retrievers, and Datasets. - Orion Weller; Kyle Lo; David Wadden; Dawn J. Lawrie; Benjamin Van Durme; Arman Cohan; Luca Soldaini (EACL (Findings), 2024)

Observable Propagation: Uncovering Feature Vectors in Transformers. - Jacob Dunefsky; Arman Cohan (ICML, 2024)

NExT: Teaching Large Language Models to Reason about Code Execution. - Ansong Ni; Miltiadis Allamanis; Arman Cohan; Yinlin Deng; Kensen Shi; Charles Sutton; Pengcheng Yin (ICML, 2024)

Investigating Data Contamination in Modern Benchmarks for Large Language Models. - Chunyuan Deng; Yilun Zhao 001; Xiangru Tang; Mark Gerstein; Arman Cohan (NAACL-HLT, 2024)

Benchmarking Generation and Evaluation Capabilities of Large Language Models for Instruction Controllable Summarization. - Yixin Liu 003; Alexander R. Fabbri; Jiawen Chen; Yilun Zhao 001; Simeng Han; Shafiq Joty; Pengfei Liu 003; Dragomir Radev; Chien-Sheng Wu; Arman Cohan (NAACL-HLT (Findings), 2024)

On Learning to Summarize with Large Language Models as References. - Yixin Liu 003; Kejian Shi; Katherine He; Longtian Ye; Alexander R. Fabbri; Pengfei Liu 003; Dragomir Radev; Arman Cohan (NAACL-HLT, 2024)

On Evaluating the Integration of Reasoning and Action in LLM Agents with Database Question Answering. - Linyong Nan; Ellen Zhang; Weijin Zou; Yilun Zhao 001; Wenfei Zhou; Arman Cohan (NAACL-HLT (Findings), 2024)

Struc-Bench: Are Large Language Models Good at Generating Complex Structured Tabular Data? - Xiangru Tang; Yiming Zong; Jason Phang; Yilun Zhao 001; Wangchunshu Zhou; Arman Cohan; Mark Gerstein (NAACL (Short Papers), 2024)

OLMo: Accelerating the Science of Language Models. - Dirk Groeneveld; Iz Beltagy; Pete Walsh; Akshita Bhagia; Rodney Kinney; Oyvind Tafjord; Ananya Harsh Jha; Hamish Ivison; Ian Magnusson; Yizhong Wang; Shane Arora; David Atkinson; et al. (CoRR, 2024)

Prioritizing Safeguarding Over Autonomy: Risks of LLM Agents for Science. - Xiangru Tang; Qiao Jin 001; Kunlun Zhu; Tongxin Yuan; Yichi Zhang; Wangchunshu Zhou; Meng Qu; Yilun Zhao 001; Jian Tang; Zhuosheng Zhang 001; Arman Cohan; Zhiyong Lu; et al. (CoRR, 2024)

Calibrating Long-form Generations from Large Language Models. - Yukun Huang; Yixin Liu 003; Raghuveer Thirukovalluru; Arman Cohan; Bhuwan Dhingra (CoRR, 2024)

On the Benefits of Fine-Grained Loss Truncation: A Case Study on Factuality in Summarization. - Lorenzo Jaime Yu Flores; Arman Cohan (CoRR, 2024)

FollowIR: Evaluating and Teaching Information Retrieval Models to Follow Instructions. - Orion Weller; Benjamin Chang 007; Sean MacAvaney; Kyle Lo; Arman Cohan; Benjamin Van Durme; Dawn J. Lawrie; Luca Soldaini (CoRR, 2024)

Evaluating LLMs at Detecting Errors in LLM Responses. - Ryo Kamoi; Sarkar Snigdha Sarathi Das; Renze Lou; Jihyun Janice Ahn; Yilun Zhao 001; Xiaoxin Lu; Nan Zhang; Yusen Zhang 001; Ranran Haoran Zhang; Sujeeth Reddy Vummanthala; Salika Dave; Shaobo Qin; et al. (CoRR, 2024)

MIMIR: A Streamlined Platform for Personalized Agent Tuning in Domain Expertise. - Chunyuan Deng; Xiangru Tang; Yilun Zhao 001; Hanming Wang; Haoran Wang; Wangchunshu Zhou; Arman Cohan; Mark Gerstein (CoRR, 2024)

SciRIFF: A Resource to Enhance Language Model Instruction-Following over Scientific Literature. - David Wadden; Kejian Shi; Jacob Morrison; Aakanksha Naik; Shruti Singh; Nitzan Barzilay; Kyle Lo; Tom Hope; Luca Soldaini; Shannon Zejiang Shen; Doug Downey; Hannaneh Hajishirzi; et al. (CoRR, 2024)

Step-Back Profiling: Distilling User History for Personalized Scientific Writing. - Xiangru Tang; Xingyao Zhang; Yanjun Shao; Jie Wu; Yilun Zhao 001; Arman Cohan; Ming Gong; Dongmei Zhang; Mark Gerstein (CoRR, 2024)

Unveiling the Spectrum of Data Contamination in Language Models: A Survey from Detection to Remediation. - Chunyuan Deng; Yilun Zhao 001; Yuzhao Heng; Yitong Li; Jiannan Cao; Xiangru Tang; Arman Cohan (CoRR, 2024)

Understanding Reference Policies in Direct Preference Optimization. - Yixin Liu 003; Pengfei Liu 003; Arman Cohan (CoRR, 2024)

RouterRetriever: Exploring the Benefits of Routing over Multiple Expert Embedding Models. - Hyunji Lee; Luca Soldaini; Arman Cohan; Minjoon Seo; Kyle Lo (CoRR, 2024)

MetaMath: Integrating Natural Language and Code for Enhanced Mathematical Reasoning in Large Language Models. - Xuyuan Xiong; Simeng Han; Ziyue Zhou; Arman Cohan (CoRR, 2024)

L2CEval: Evaluating Language-to-Code Generation Capabilities of Large Language Models. - Ansong Ni; Pengcheng Yin; Yilun Zhao 001; Martin Riddell; Troy Feng; Rui Shen; Stephen Yin; Ye Liu 006; Semih Yavuz; Caiming Xiong; Shafiq Joty; Yingbo Zhou; et al. (Trans. Assoc. Comput. Linguistics, 2024)