Tackling Biomedical Text Summarization: OAQA at BioASQ 5B. - Khyathi Raghavi Chandu; Aakanksha Naik; Aditya Chandrasekar; Zi Yang; Niloy Gupta; Eric Nyberg (BioNLP, 2017)

Extracting Personal Medical Events for User Timeline Construction using Minimal Supervision. - Aakanksha Naik; Christopher Bogart; Carolyn P. Rosé (BioNLP, 2017)

Stress Test Evaluation for Natural Language Inference. - Aakanksha Naik; Abhilasha Ravichander; Norman M. Sadeh; Carolyn P. Rosé; Graham Neubig (COLING, 2018)

Exploring Numeracy in Word Embeddings. - Aakanksha Naik; Abhilasha Ravichander; Carolyn P. Rosé; Eduard H. Hovy (ACL (1), 2019)

EQUATE: A Benchmark Evaluation Framework for Quantitative Reasoning in Natural Language Inference. - Abhilasha Ravichander; Aakanksha Naik; Carolyn P. Rosé; Eduard H. Hovy (CoNLL, 2019)

TDDiscourse: A Dataset for Discourse-Level Temporal Ordering of Events. - Aakanksha Naik; Luke Breitfeller; Carolyn P. Rosé (SIGdial, 2019)

Towards Open Domain Event Trigger Identification using Adversarial Domain Adaptation. - Aakanksha Naik; Carolyn P. Rosé (ACL, 2020)

Adapting Event Extractors to Medical Data: Bridging the Covariate Shift. - Aakanksha Naik; Jill Fain Lehman; Carolyn P. Rosé (EACL, 2021)

STAGE: Tool for Automated Extraction of Semantic Time Cues to Enrich Neural Temporal Ordering Models. - Luke Breitfeller; Aakanksha Naik; Carolyn P. Rosé (CoRR, 2021)

Literature-Augmented Clinical Outcome Prediction. - Aakanksha Naik; Sravanthi Parasa; Sergey Feldman; Lucy Lu Wang; Tom Hope (NAACL-HLT (Findings), 2022)

Multi-Scale Contrastive Co-Training for Event Temporal Relation Extraction. - Hao-Ren Yao; Luke Breitfeller; Aakanksha Naik; Chunxiao Zhou; Carolyn P. Rosé (CoRR, 2022)

Adapting to the Long Tail: A Meta-Analysis of Transfer Learning Research for Language Understanding Tasks. - Aakanksha Naik; Jill Lehman; Carolyn P. Rosé (Trans. Assoc. Comput. Linguistics, 2022)

Relatedly: Scaffolding Literature Reviews with Existing Related Work Sections. - Srishti Palani; Aakanksha Naik; Doug Downey; Amy X. Zhang; Jonathan Bragg; Joseph Chee Chang (CHI, 2023)

S2abEL: A Dataset for Entity Linking from Scientific Tables. - Yuze Lou; Bailey Kuehl; Erin Bransom; Sergey Feldman; Aakanksha Naik; Doug Downey (EMNLP, 2023)

The Semantic Reader Project: Augmenting Scholarly Documents through AI-Powered Interactive Reading Interfaces. - Kyle Lo; Joseph Chee Chang; Andrew Head; Jonathan Bragg; Amy X. Zhang; Cassidy Trier; Chloe Anastasiades; Tal August; Russell Authur; Danielle Bragg; Erin Bransom; Isabel Cachola; et al. (CoRR, 2023)

SynerGPT: In-Context Learning for Personalized Drug Synergy Prediction and Drug Design. - Carl Edwards; Aakanksha Naik; Tushar Khot; Martin D. Burke; Heng Ji 001; Tom Hope (CoRR, 2023)

LongBoX: Evaluating Transformers on Long-Sequence Clinical Tasks. - Mihir Parmar; Aakanksha Naik; Himanshu Gupta; Disha Agrawal; Chitta Baral (CoRR, 2023)

Designing Guiding Principles for NLP for Healthcare: A Case Study of Maternal Health. - Maria Antoniak; Aakanksha Naik; Carla S. Alvarado; Lucy Lu Wang; Irene Y. Chen (CoRR, 2023)

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)

CHIME: LLM-Assisted Hierarchical Organization of Scientific Studies for Literature Review Support. - Chao-Chun Hsu; Erin Bransom; Jenna Sparks; Bailey Kuehl; Chenhao Tan; David Wadden; Lucy Lu Wang; Aakanksha Naik (ACL (Findings), 2024)

Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research. - Luca Soldaini; Rodney Kinney; Akshita Bhagia; Dustin Schwenk; David Atkinson; Russell Authur; Ben Bogin; Khyathi Raghavi Chandu; Jennifer Dumas; Yanai Elazar; Valentin Hofmann; Ananya Harsh Jha; et al. (ACL (1), 2024)

Distilling Multi-Scale Knowledge for Event Temporal Relation Extraction. - Hao-Ren Yao; Luke Breitfeller; Aakanksha Naik; Chunxiao Zhou; Carolyn P. Rosé (CIKM, 2024)

ArxivDIGESTables: Synthesizing Scientific Literature into Tables using Language Models. - Benjamin Newman; Yoonjoo Lee; Aakanksha Naik; Pao Siangliulue; Raymond Fok; Juho Kim 001; Daniel S. Weld; Joseph Chee Chang; Kyle Lo (EMNLP, 2024)

NLP for Maternal Healthcare: Perspectives and Guiding Principles in the Age of LLMs. - Maria Antoniak; Aakanksha Naik; Carla S. Alvarado; Lucy Lu Wang; Irene Y. Chen (FAccT, 2024)

On-the-fly Definition Augmentation of LLMs for Biomedical NER. - Monica Munnangi; Sergey Feldman; Byron C. Wallace; Silvio Amir; Tom Hope; Aakanksha Naik (NAACL-HLT, 2024)

CARE: Extracting Experimental Findings From Clinical Literature. - Aakanksha Naik; Bailey Kuehl; Erin Bransom; Doug Downey; Tom Hope (NAACL-HLT (Findings), 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)

SciRIFF: A Resource to Enhance Language Model Instruction-Following over Scientific Literature. - David Wadden; Kejian Shi; Jacob Morrison; Aakanksha Naik; Shruti Singh 001; Nitzan Barzilay; Kyle Lo; Tom Hope; Luca Soldaini; Shannon Zejiang Shen; Doug Downey; Hannaneh Hajishirzi; et al. (CoRR, 2024)

Exploring Long-Term Prediction of Type 2 Diabetes Microvascular Complications. - Elizabeth Remfry; Rafael Henkin; Michael R. Barnes; Aakanksha Naik (CoRR, 2024)

Adapting to the Long Tail in Language Understanding - Aakanksha Naik (2024)

The Semantic Reader Project. - Kyle Lo; Joseph Chee Chang; Andrew Head; Jonathan Bragg; Amy X. Zhang; Cassidy Trier; Chloe Anastasiades; Tal August; Russell Authur; Danielle Bragg; Erin Bransom; Isabel Cachola; et al. (Commun. ACM, 2024)

Ai2 Scholar QA: Organized Literature Synthesis with Attribution. - Amanpreet Singh; Joseph Chee Chang; Chloe Anastasiades; Dany Haddad; Aakanksha Naik; Amber Tanaka; Angele Zamarron; Cecile Nguyen; Jena D. Hwang; Jason Dunkleberger; Matt Latzke; Smita Rao; et al. (CoRR, 2025)

Setting The Table with Intent: Intent-aware Schema Generation and Editing for Literature Review Tables. - Vishakh Padmakumar; Joseph Chee Chang; Kyle Lo; Doug Downey; Aakanksha Naik (CoRR, 2025)