Aakanksha Naik

53 papers A* 5A 2B 3Journal 30Unranked 12
YearRankTypeTitle / Venue / Authors
2026 J jnl
Deep Research, Shallow Evaluation: A Case Study in Meta-Evaluation for Long-Form QA Benchmarks.
CoRR
Jena D. Hwang, Varsha Kishore, Amanpreet Singh, Dany Haddad, Aakanksha Naik, Malachi Hamada, Jonathan Bragg, Mike D'Arcy, Daniel S. Weld, Lucy Lu Wang, Doug Downey, Sergey Feldman
2026 J jnl
Improving Attributed Long-form Question Answering with Intent Awareness.
CoRR
Xinran Zhao, Aakanksha Naik, Jay DeYoung, Joseph Chee Chang, Jena D. Hwang, Tongshuang Wu, Varsha Kishore
2026 J jnl
Language Models Don't Know What You Want: Evaluating Personalization in Deep Research Needs Real Users.
CoRR
Nishant Balepur, Malachi Hamada, Varsha Kishore, Sergey Feldman, Amanpreet Singh, Pao Siangliulue, Joseph Chee Chang, Eunsol Choi, Jordan Lee Boyd-Graber, Aakanksha Naik
2025 — conf
Ai2 Scholar QA: Organized Literature Synthesis with Attribution.
ACL (3)
Amanpreet Singh, Joseph Chee Chang, Dany Haddad, Aakanksha Naik, Jena D. Hwang, Rodney Kinney, Daniel S. Weld, Doug Downey, Sergey Feldman
2025 J jnl
Ai2 Scholar QA: Organized Literature Synthesis with Attribution.
CoRR
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, Jaron Lochner, Rob Evans, Rodney Kinney, Daniel S. Weld, Doug Downey, Sergey Feldman
2025 J jnl
AstaBench: Rigorous Benchmarking of AI Agents with a Scientific Research Suite.
CoRR
Jonathan Bragg, Mike D'Arcy, Nishant Balepur, Dan Bareket, Bhavana Dalvi, Sergey Feldman, Dany Haddad, Jena D. Hwang, Peter A. Jansen, Varsha Kishore, Bodhisattwa Prasad Majumder, Aakanksha Naik, Sigal Rahamimov, Kyle Richardson, Amanpreet Singh, Harshit Surana, Aryeh Tiktinsky, Rosni Vasu, Guy Wiener, Chloe Anastasiades, Stefan Candra, Jason Dunkelberger, Dan Emery, Rob Evans, Malachi Hamada, Regan Huff, Rodney Kinney, Matt Latzke, Jaron Lochner, Ruben Lozano-Aguilera, Cecile Nguyen, Smita Rao, Amber Tanaka, Brooke Vlahos, Peter Clark, Doug Downey, Yoav Goldberg, Ashish Sabharwal, Daniel S. Weld
2025 — conf
Intent-aware Schema Generation and Refinement for Literature Review Tables.
EMNLP (Findings)
Vishakh Padmakumar, Joseph Chee Chang, Kyle Lo, Doug Downey, Aakanksha Naik
2025 A* conf
SciRIFF: A Resource to Enhance Language Model Instruction-Following over Scientific Literature.
EMNLP
David Wadden, Kejian Shi, Jacob Morrison, Alan Li, Aakanksha Naik, Shruti Singh, Nitzan Barzilay, Kyle Lo, Tom Hope, Luca Soldaini, Shannon Zejiang Shen, Doug Downey, Hannaneh Hajishirzi, Arman Cohan
2025 J jnl
Setting The Table with Intent: Intent-aware Schema Generation and Editing for Literature Review Tables.
CoRR
Vishakh Padmakumar, Joseph Chee Chang, Kyle Lo, Doug Downey, Aakanksha Naik
2024 — —
Adapting to the Long Tail in Language Understanding
Aakanksha Naik
2024 A* conf
ArxivDIGESTables: Synthesizing Scientific Literature into Tables using Language Models.
EMNLP
Benjamin Newman, Yoonjoo Lee, Aakanksha Naik, Pao Siangliulue, Raymond Fok, Juho Kim, Daniel S. Weld, Joseph Chee Chang, Kyle Lo
2024 J jnl
ArxivDIGESTables: Synthesizing Scientific Literature into Tables using Language Models.
CoRR
Benjamin Newman, Yoonjoo Lee, Aakanksha Naik, Pao Siangliulue, Raymond Fok, Juho Kim, Daniel S. Weld, Joseph Chee Chang, Kyle Lo
2024 — conf
CARE: Extracting Experimental Findings From Clinical Literature.
NAACL-HLT (Findings)
Aakanksha Naik, Bailey Kuehl, Erin Bransom, Doug Downey, Tom Hope
2024 — conf
CHIME: LLM-Assisted Hierarchical Organization of Scientific Studies for Literature Review Support.
ACL (Findings)
Chao-Chun Hsu, Erin Bransom, Jenna Sparks, Bailey Kuehl, Chenhao Tan, David Wadden, Lucy Lu Wang, Aakanksha Naik
2024 J jnl
CHIME: LLM-Assisted Hierarchical Organization of Scientific Studies for Literature Review Support.
CoRR
Chao-Chun Hsu, Erin Bransom, Jenna Sparks, Bailey Kuehl, Chenhao Tan, David Wadden, Lucy Lu Wang, Aakanksha Naik
2024 A conf
Distilling Multi-Scale Knowledge for Event Temporal Relation Extraction.
CIKM
Hao-Ren Yao, Luke Breitfeller, Aakanksha Naik, Chunxiao Zhou, Carolyn P. Rosé
2024 — conf
Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research.
ACL (1)
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, Sachin Kumar, Li Lucy, Xinxi Lyu, Nathan Lambert, Ian Magnusson, Jacob Morrison, Niklas Muennighoff, Aakanksha Naik, Crystal Nam, Matthew E. Peters, Abhilasha Ravichander, Kyle Richardson, Zejiang Shen, Emma Strubell, Nishant Subramani, Oyvind Tafjord, Pete Walsh, Luke Zettlemoyer, Noah A. Smith, Hannaneh Hajishirzi, Iz Beltagy, Dirk Groeneveld, Jesse Dodge, Kyle Lo
2024 J jnl
Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research.
CoRR
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, Sachin Kumar, Li Lucy, Xinxi Lyu, Nathan Lambert, Ian Magnusson, Jacob Morrison, Niklas Muennighoff, Aakanksha Naik, Crystal Nam, Matthew E. Peters, Abhilasha Ravichander, Kyle Richardson, Zejiang Shen, Emma Strubell, Nishant Subramani, Oyvind Tafjord, Pete Walsh, Luke Zettlemoyer, Noah A. Smith, Hannaneh Hajishirzi, Iz Beltagy, Dirk Groeneveld, Jesse Dodge, Kyle Lo
2024 J jnl
Exploring Long-Term Prediction of Type 2 Diabetes Microvascular Complications.
CoRR
Elizabeth Remfry, Rafael Henkin, Michael R. Barnes, Aakanksha Naik
2024 — conf
NLP for Maternal Healthcare: Perspectives and Guiding Principles in the Age of LLMs.
FAccT
Maria Antoniak, Aakanksha Naik, Carla S. Alvarado, Lucy Lu Wang, Irene Y. Chen
2024 — conf
OLMo: Accelerating the Science of Language Models.
ACL (1)
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, Russell Authur, Khyathi Raghavi Chandu, Arman Cohan, Jennifer Dumas, Yanai Elazar, Yuling Gu, Jack Hessel, Tushar Khot, William Merrill, Jacob Morrison, Niklas Muennighoff, Aakanksha Naik, Crystal Nam, Matthew E. Peters, Valentina Pyatkin, Abhilasha Ravichander, Dustin Schwenk, Saurabh Shah, Will Smith, Emma Strubell, Nishant Subramani, Mitchell Wortsman, Pradeep Dasigi, Nathan Lambert, Kyle Richardson, Luke Zettlemoyer, Jesse Dodge, Kyle Lo, Luca Soldaini, Noah A. Smith, Hannaneh Hajishirzi
2024 J jnl
OLMo: Accelerating the Science of Language Models.
CoRR
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, Russell Authur, Khyathi Raghavi Chandu, Arman Cohan, Jennifer Dumas, Yanai Elazar, Yuling Gu, Jack Hessel, Tushar Khot, William Merrill, Jacob Morrison, Niklas Muennighoff, Aakanksha Naik, Crystal Nam, Matthew E. Peters, Valentina Pyatkin, Abhilasha Ravichander, Dustin Schwenk, Saurabh Shah, Will Smith, Emma Strubell, Nishant Subramani, Mitchell Wortsman, Pradeep Dasigi, Nathan Lambert, Kyle Richardson, Luke Zettlemoyer, Jesse Dodge, Kyle Lo, Luca Soldaini, Noah A. Smith, Hannaneh Hajishirzi
2024 — conf
On-the-fly Definition Augmentation of LLMs for Biomedical NER.
NAACL-HLT
Monica Munnangi, Sergey Feldman, Byron C. Wallace, Silvio Amir, Tom Hope, Aakanksha Naik
2024 J jnl
On-the-fly Definition Augmentation of LLMs for Biomedical NER.
CoRR
Monica Munnangi, Sergey Feldman, Byron C. Wallace, Silvio Amir, Tom Hope, Aakanksha Naik
2024 J jnl
SciRIFF: A Resource to Enhance Language Model Instruction-Following over Scientific Literature.
CoRR
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, Arman Cohan
2024 J jnl
The Semantic Reader Project.
Commun. ACM
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, Stefan Candra, Yoganand Chandrasekhar, Yen-Sung Chen, Evie Yu-Yen Cheng, Yvonne Chou, Doug Downey, Rob Evans, Raymond Fok, Fangzhou Hu, Regan Huff, Dongyeop Kang, Tae Soo Kim, Rodney Kinney, Aniket Kittur, Hyeonsu B. Kang, Egor Klevak, Bailey Kuehl, Michael Langan, Matt Latzke, Jaron Lochner, Kelsey MacMillan, Eric Marsh, Tyler Murray, Aakanksha Naik, Ngoc-Uyen Nguyen, Srishti Palani, Soya Park, Caroline Paulic, Napol Rachatasumrit, Smita Rao, Paul Sayre, Zejiang Shen, Pao Siangliulue, Luca Soldaini, Huy Tran, Madeleine van Zuylen, Lucy Lu Wang, Chris Wilhelm, Caroline Wu, Jiangjiang Yang, Angele Zamarron, Marti A. Hearst, Daniel S. Weld
2023 J jnl
CARE: Extracting Experimental Findings From Clinical Literature.
CoRR
Aakanksha Naik, Bailey Kuehl, Erin Bransom, Doug Downey, Tom Hope
2023 J jnl
Designing Guiding Principles for NLP for Healthcare: A Case Study of Maternal Health.
CoRR
Maria Antoniak, Aakanksha Naik, Carla S. Alvarado, Lucy Lu Wang, Irene Y. Chen
2023 J jnl
LongBoX: Evaluating Transformers on Long-Sequence Clinical Tasks.
CoRR
Mihir Parmar, Aakanksha Naik, Himanshu Gupta, Disha Agrawal, Chitta Baral
2023 A* conf
Relatedly: Scaffolding Literature Reviews with Existing Related Work Sections.
CHI
Srishti Palani, Aakanksha Naik, Doug Downey, Amy X. Zhang, Jonathan Bragg, Joseph Chee Chang
2023 J jnl
Relatedly: Scaffolding Literature Reviews with Existing Related Work Sections.
CoRR
Srishti Palani, Aakanksha Naik, Doug Downey, Amy X. Zhang, Jonathan Bragg, Joseph Chee Chang
2023 A* conf
S2abEL: A Dataset for Entity Linking from Scientific Tables.
EMNLP
Yuze Lou, Bailey Kuehl, Erin Bransom, Sergey Feldman, Aakanksha Naik, Doug Downey
2023 J jnl
S2abEL: A Dataset for Entity Linking from Scientific Tables.
CoRR
Yuze Lou, Bailey Kuehl, Erin Bransom, Sergey Feldman, Aakanksha Naik, Doug Downey
2023 J jnl
SynerGPT: In-Context Learning for Personalized Drug Synergy Prediction and Drug Design.
CoRR
Carl Edwards, Aakanksha Naik, Tushar Khot, Martin D. Burke, Heng Ji, Tom Hope
2023 J jnl
The Semantic Reader Project: Augmenting Scholarly Documents through AI-Powered Interactive Reading Interfaces.
CoRR
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, Stefan Candra, Yoganand Chandrasekhar, Yen-Sung Chen, Evie Yu-Yen Cheng, Yvonne Chou, Doug Downey, Rob Evans, Raymond Fok, Fangzhou Hu, Regan Huff, Dongyeop Kang, Tae Soo Kim, Rodney Kinney, Aniket Kittur, Hyeonsu B. Kang, Egor Klevak, Bailey Kuehl, Michael Langan, Matt Latzke, Jaron Lochner, Kelsey MacMillan, Eric Marsh, Tyler Murray, Aakanksha Naik, Ngoc-Uyen Nguyen, Srishti Palani, Soya Park, Caroline Paulic, Napol Rachatasumrit, Smita Rao, Paul Sayre, Zejiang Shen, Pao Siangliulue, Luca Soldaini, Huy Tran, Madeleine van Zuylen, Lucy Lu Wang, Chris Wilhelm, Caroline Wu, Jiangjiang Yang, Angele Zamarron, Marti A. Hearst, Daniel S. Weld
2022 J jnl
Adapting to the Long Tail: A Meta-Analysis of Transfer Learning Research for Language Understanding Tasks.
Trans. Assoc. Comput. Linguistics
Aakanksha Naik, Jill Lehman, Carolyn P. Rosé
2022 — conf
Literature-Augmented Clinical Outcome Prediction.
NAACL-HLT (Findings)
Aakanksha Naik, Sravanthi Parasa, Sergey Feldman, Lucy Lu Wang, Tom Hope
2022 J jnl
Multi-Scale Contrastive Co-Training for Event Temporal Relation Extraction.
CoRR
Hao-Ren Yao, Luke Breitfeller, Aakanksha Naik, Chunxiao Zhou, Carolyn P. Rosé
2021 A conf
Adapting Event Extractors to Medical Data: Bridging the Covariate Shift.
EACL
Aakanksha Naik, Jill Fain Lehman, Carolyn P. Rosé
2021 J jnl
Adapting to the Long Tail: A Meta-Analysis of Transfer Learning Research for Language Understanding Tasks.
CoRR
Aakanksha Naik, Jill Lehman, Carolyn P. Rosé
2021 J jnl
Literature-Augmented Clinical Outcome Prediction.
CoRR
Aakanksha Naik, Sravanthi Parasa, Sergey Feldman, Lucy Lu Wang, Tom Hope
2021 J jnl
STAGE: Tool for Automated Extraction of Semantic Time Cues to Enrich Neural Temporal Ordering Models.
CoRR
Luke Breitfeller, Aakanksha Naik, Carolyn P. Rosé
2020 J jnl
Adapting Event Extractors to Medical Data: Bridging the Covariate Shift.
CoRR
Aakanksha Naik, Jill Lehman, Carolyn P. Rosé
2020 A* conf
Towards Open Domain Event Trigger Identification using Adversarial Domain Adaptation.
ACL
Aakanksha Naik, Carolyn P. Rosé
2020 J jnl
Towards Open Domain Event Trigger Identification using Adversarial Domain Adaptation.
CoRR
Aakanksha Naik, Carolyn P. Rosé
2019 B conf
EQUATE: A Benchmark Evaluation Framework for Quantitative Reasoning in Natural Language Inference.
CoNLL
Abhilasha Ravichander, Aakanksha Naik, Carolyn P. Rosé, Eduard H. Hovy
2019 J jnl
EQUATE: A Benchmark Evaluation Framework for Quantitative Reasoning in Natural Language Inference.
CoRR
Abhilasha Ravichander, Aakanksha Naik, Carolyn P. Rosé, Eduard H. Hovy
2019 — conf
Exploring Numeracy in Word Embeddings.
ACL (1)
Aakanksha Naik, Abhilasha Ravichander, Carolyn P. Rosé, Eduard H. Hovy
2019 B conf
TDDiscourse: A Dataset for Discourse-Level Temporal Ordering of Events.
SIGdial
Aakanksha Naik, Luke Breitfeller, Carolyn P. Rosé
2018 B conf
Stress Test Evaluation for Natural Language Inference.
COLING
Aakanksha Naik, Abhilasha Ravichander, Norman M. Sadeh, Carolyn P. Rosé, Graham Neubig
2018 J jnl
Stress Test Evaluation for Natural Language Inference.
CoRR
Aakanksha Naik, Abhilasha Ravichander, Norman M. Sadeh, Carolyn P. Rosé, Graham Neubig
2017 — conf
Extracting Personal Medical Events for User Timeline Construction using Minimal Supervision.
BioNLP
Aakanksha Naik, Christopher Bogart, Carolyn P. Rosé
2017 — conf
Tackling Biomedical Text Summarization: OAQA at BioASQ 5B.
BioNLP
Khyathi Raghavi Chandu, Aakanksha Naik, Aditya Chandrasekar, Zi Yang, Niloy Gupta, Eric Nyberg