Aakanksha Naik
Aakanksha Naik
Allen Institute for Artificial Intelligence
Verified email at - Homepage
Cited by
Cited by
Stress test evaluation for natural language inference
A Naik, A Ravichander, N Sadeh, C Rose, G Neubig
arXiv preprint arXiv:1806.00692, 2018
EQUATE: A benchmark evaluation framework for quantitative reasoning in natural language inference
A Ravichander, A Naik, C Rose, E Hovy
arXiv preprint arXiv:1901.03735, 2019
Exploring numeracy in word embeddings
A Naik, A Ravichander, C Rose, E Hovy
Proceedings of the 57th Annual Meeting of the Association for Computational†…, 2019
Towards open domain event trigger identification using adversarial domain adaptation
A Naik, C Rose
arXiv preprint arXiv:2005.11355, 2020
TDDiscourse: A dataset for discourse-level temporal ordering of events
A Naik, L Breitfeller, C Rose
Proceedings of the 20th Annual SIGdial Meeting on Discourse and Dialogue†…, 2019
Tackling biomedical text summarization: Oaqa at bioasq 5b
K Chandu, A Naik, A Chandrasekar, Z Yang, N Gupta, E Nyberg
BioNLP 2017, 58-66, 2017
Literature-augmented clinical outcome prediction
A Naik, S Parasa, S Feldman, LL Wang, T Hope
arXiv preprint arXiv:2111.08374, 2021
Olmo: Accelerating the science of language models
D Groeneveld, I Beltagy, P Walsh, A Bhagia, R Kinney, O Tafjord, AH Jha, ...
arXiv preprint arXiv:2402.00838, 2024
Relatedly: Scaffolding literature reviews with existing related work sections
S Palani, A Naik, D Downey, AX Zhang, J Bragg, JC Chang
Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems†…, 2023
Dolma: An Open Corpus of Three Trillion Tokens for Language Model Pretraining Research
L Soldaini, R Kinney, A Bhagia, D Schwenk, D Atkinson, R Authur, ...
arXiv preprint arXiv:2402.00159, 2024
The semantic reader project: Augmenting scholarly documents through ai-powered interactive reading interfaces
K Lo, JC Chang, A Head, J Bragg, AX Zhang, C Trier, C Anastasiades, ...
arXiv preprint arXiv:2303.14334, 2023
FanfictionNLP: A text processing pipeline for fanfiction
MM Yoder, S Khosla, Q Shen, A Naik, H Jin, H Muralidharan, CP Rosť
The 3rd Workshop on Narrative Understanding, 2021
Using functional schemas to understand social media narratives
X Yan, A Naik, Y Jo, C Rose
Proceedings of the Second Workshop on Storytelling, 22-33, 2019
Dolma: An open corpus of 3 trillion tokens for language model pretraining research
L Soldaini, R Kinney, A Bhagia, D Schwenk, D Atkinson, R Authur, ...
Allen Institute for AI, Tech. Rep, 5998-6008, 2023
Extracting personal medical events for user timeline construction using minimal supervision
A Naik, C Bogart, C Rose
BioNLP 2017, 356-364, 2017
Designing Guiding Principles for NLP for Healthcare: A Case Study of Maternal Health
M Antoniak, A Naik, CS Alvarado, LL Wang, IY Chen
arXiv preprint arXiv:2312.11803, 2023
SynerGPT: In-Context Learning for Personalized Drug Synergy Prediction and Drug Design
CN Edwards, A Naik, T Khot, MD Burke, H Ji, T Hope
bioRxiv, 2023.07. 06.547759, 2023
Longbox: Evaluating transformers on long-sequence clinical tasks
M Parmar, A Naik, H Gupta, D Agrawal, C Baral
arXiv preprint arXiv:2311.09564, 2023
Adapting to the long tail: A meta-analysis of transfer learning research for language understanding tasks
A Naik, J Lehman, C Rosť
Transactions of the Association for Computational Linguistics 10, 956-980, 2022
Stage: tool for automated extraction of semantic time cues to enrich neural temporal ordering models
L Breitfeller, A Naik, C Rose
arXiv preprint arXiv:2105.07314, 2021
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