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Abhilasha Ravichander
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2020 – today
- 2024
- [c22]Yanai Elazar, Akshita Bhagia, Ian Magnusson, Abhilasha Ravichander, Dustin Schwenk, Alane Suhr, Evan Pete Walsh, Dirk Groeneveld, Luca Soldaini, Sameer Singh, Hannaneh Hajishirzi, Noah A. Smith, Jesse Dodge:
What's In My Big Data? ICLR 2024 - [c21]Bill Yuchen Lin, Abhilasha Ravichander, Ximing Lu, Nouha Dziri, Melanie Sclar, Khyathi Raghavi Chandu, Chandra Bhagavatula, Yejin Choi:
The Unlocking Spell on Base LLMs: Rethinking Alignment via In-Context Learning. ICLR 2024 - [c20]Peter West, Ximing Lu, Nouha Dziri, Faeze Brahman, Linjie Li, Jena D. Hwang, Liwei Jiang, Jillian Fisher, Abhilasha Ravichander, Khyathi Raghavi Chandu, Benjamin Newman, Pang Wei Koh, Allyson Ettinger, Yejin Choi:
The Generative AI Paradox: "What It Can Create, It May Not Understand". ICLR 2024 - [c19]Yuanyuan Feng, Abhilasha Ravichander, Yaxing Yao, Shikun Zhang, Rex Chen, Shomir Wilson, Norman Sadeh:
Understanding How to Inform Blind and Low-Vision Users about Data Privacy through Privacy Question Answering Assistants. USENIX Security Symposium 2024 - [i24]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:
Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research. CoRR abs/2402.00159 (2024) - [i23]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:
OLMo: Accelerating the Science of Language Models. CoRR abs/2402.00838 (2024) - [i22]Nishant Balepur, Abhilasha Ravichander, Rachel Rudinger:
Artifacts or Abduction: How Do LLMs Answer Multiple-Choice Questions Without the Question? CoRR abs/2402.12483 (2024) - [i21]Bill Yuchen Lin, Yuntian Deng, Khyathi Raghavi Chandu, Faeze Brahman, Abhilasha Ravichander, Valentina Pyatkin, Nouha Dziri, Ronan Le Bras, Yejin Choi:
WildBench: Benchmarking LLMs with Challenging Tasks from Real Users in the Wild. CoRR abs/2406.04770 (2024) - 2023
- [c18]Ximing Lu, Faeze Brahman, Peter West, Jaehun Jung, Khyathi Raghavi Chandu, Abhilasha Ravichander, Prithviraj Ammanabrolu, Liwei Jiang, Sahana Ramnath, Nouha Dziri, Jillian Fisher, Bill Y. Lin, Skyler Hallinan, Lianhui Qin, Xiang Ren, Sean Welleck, Yejin Choi:
Inference-Time Policy Adapters (IPA): Tailoring Extreme-Scale LMs without Fine-tuning. EMNLP 2023: 6863-6883 - [c17]Abhilasha Ravichander, Joe Stacey, Marek Rei:
When and Why Does Bias Mitigation Work? EMNLP (Findings) 2023: 9233-9247 - [e1]Burcu Can, Maximilian Mozes, Samuel Cahyawijaya, Naomi Saphra, Nora Kassner, Shauli Ravfogel, Abhilasha Ravichander, Chen Zhao, Isabelle Augenstein, Anna Rogers, Kyunghyun Cho, Edward Grefenstette, Lena Voita:
Proceedings of the 8th Workshop on Representation Learning for NLP, RepL4NLP@ACL 2023, Toronto, Canada, July 13, 2023. Association for Computational Linguistics 2023, ISBN 978-1-959429-77-7 [contents] - [i20]Ximing Lu, Faeze Brahman, Peter West, Jaehun Jung, Khyathi Raghavi Chandu, Abhilasha Ravichander, Lianhui Qin, Prithviraj Ammanabrolu, Liwei Jiang, Sahana Ramnath, Nouha Dziri, Jillian Fisher, Bill Yuchen Lin, Skyler Hallinan, Xiang Ren, Sean Welleck, Yejin Choi:
Inference-Time Policy Adapters (IPA): Tailoring Extreme-Scale LMs without Fine-tuning. CoRR abs/2305.15065 (2023) - [i19]Yuanyuan Feng, Abhilasha Ravichander, Yaxing Yao, Shikun Zhang, Rex Chen, Shomir Wilson, Norman Sadeh:
Understanding How to Inform Blind and Low-Vision Users about Data Privacy through Privacy Question Answering Assistants. CoRR abs/2310.08687 (2023) - [i18]Yanai Elazar, Akshita Bhagia, Ian Magnusson, Abhilasha Ravichander, Dustin Schwenk, Alane Suhr, Pete Walsh, Dirk Groeneveld, Luca Soldaini, Sameer Singh, Hanna Hajishirzi, Noah A. Smith, Jesse Dodge:
What's In My Big Data? CoRR abs/2310.20707 (2023) - [i17]Peter West, Ximing Lu, Nouha Dziri, Faeze Brahman, Linjie Li, Jena D. Hwang, Liwei Jiang, Jillian Fisher, Abhilasha Ravichander, Khyathi Raghavi Chandu, Benjamin Newman, Pang Wei Koh, Allyson Ettinger, Yejin Choi:
The Generative AI Paradox: "What It Can Create, It May Not Understand". CoRR abs/2311.00059 (2023) - [i16]Da Yin, Faeze Brahman, Abhilasha Ravichander, Khyathi Raghavi Chandu, Kai-Wei Chang, Yejin Choi, Bill Yuchen Lin:
Lumos: Learning Agents with Unified Data, Modular Design, and Open-Source LLMs. CoRR abs/2311.05657 (2023) - [i15]Yufei Tian, Abhilasha Ravichander, Lianhui Qin, Ronan Le Bras, Raja Marjieh, Nanyun Peng, Yejin Choi, Thomas L. Griffiths, Faeze Brahman:
MacGyver: Are Large Language Models Creative Problem Solvers? CoRR abs/2311.09682 (2023) - [i14]Bill Yuchen Lin, Abhilasha Ravichander, Ximing Lu, Nouha Dziri, Melanie Sclar, Khyathi Raghavi Chandu, Chandra Bhagavatula, Yejin Choi:
The Unlocking Spell on Base LLMs: Rethinking Alignment via In-Context Learning. CoRR abs/2312.01552 (2023) - 2022
- [c16]Abhilasha Ravichander, Matt Gardner, Ana Marasovic:
CONDAQA: A Contrastive Reading Comprehension Dataset for Reasoning about Negation. EMNLP 2022: 8729-8755 - [c15]Siddhant Arora, Henry Hosseini, Christine Utz, Vinayshekhar Bannihatti Kumar, Tristan Dhellemmes, Abhilasha Ravichander, Peter Story, Jasmine Mangat, Rex Chen, Martin Degeling, Thomas B. Norton, Thomas Hupperich, Shomir Wilson, Norman M. Sadeh:
A Tale of Two Regulatory Regimes: Creation and Analysis of a Bilingual Privacy Policy Corpus. LREC 2022: 5460-5472 - [i13]Yanai Elazar, Nora Kassner, Shauli Ravfogel, Amir Feder, Abhilasha Ravichander, Marius Mosbach, Yonatan Belinkov, Hinrich Schütze, Yoav Goldberg:
Measuring Causal Effects of Data Statistics on Language Model's 'Factual' Predictions. CoRR abs/2207.14251 (2022) - [i12]Yuanyuan Feng, Abhilasha Ravichander, Yaxing Yao, Shikun Zhang, Norman Sadeh:
Exploring and Improving the Accessibility of Data Privacy-related Information for People Who Are Blind or Low-vision. CoRR abs/2208.09959 (2022) - [i11]Abhilasha Ravichander, Matt Gardner, Ana Marasovic:
CONDAQA: A Contrastive Reading Comprehension Dataset for Reasoning about Negation. CoRR abs/2211.00295 (2022) - 2021
- [j3]Yanai Elazar, Nora Kassner, Shauli Ravfogel, Abhilasha Ravichander, Eduard H. Hovy
, Hinrich Schütze, Yoav Goldberg:
Measuring and Improving Consistency in Pretrained Language Models. Trans. Assoc. Comput. Linguistics 9: 1012-1031 (2021) - [j2]Yanai Elazar, Nora Kassner, Shauli Ravfogel, Abhilasha Ravichander, Eduard H. Hovy
, Hinrich Schütze, Yoav Goldberg:
Erratum: Measuring and Improving Consistency in Pretrained Language Models. Trans. Assoc. Comput. Linguistics 9: 1407 (2021) - [c14]Abhilasha Ravichander, Alan W. Black, Thomas B. Norton, Shomir Wilson, Norman M. Sadeh:
Breaking Down Walls of Text: How Can NLP Benefit Consumer Privacy? ACL/IJCNLP (1) 2021: 4125-4140 - [c13]Abhilasha Ravichander, Siddharth Dalmia, Maria Ryskina
, Florian Metze, Eduard H. Hovy, Alan W. Black:
NoiseQA: Challenge Set Evaluation for User-Centric Question Answering. EACL 2021: 2976-2992 - [c12]Abhilasha Ravichander, Yonatan Belinkov, Eduard H. Hovy:
Probing the Probing Paradigm: Does Probing Accuracy Entail Task Relevance? EACL 2021: 3363-3377 - [i10]Yanai Elazar, Nora Kassner, Shauli Ravfogel, Abhilasha Ravichander, Eduard H. Hovy, Hinrich Schütze, Yoav Goldberg:
Measuring and Improving Consistency in Pretrained Language Models. CoRR abs/2102.01017 (2021) - [i9]Abhilasha Ravichander, Siddharth Dalmia, Maria Ryskina, Florian Metze, Eduard H. Hovy, Alan W. Black:
NoiseQA: Challenge Set Evaluation for User-Centric Question Answering. CoRR abs/2102.08345 (2021) - [i8]Dheeraj Rajagopal, Aman Madaan, Niket Tandon, Yiming Yang, Shrimai Prabhumoye, Abhilasha Ravichander, Peter Clark, Eduard H. Hovy:
CURIE: An Iterative Querying Approach for Reasoning About Situations. CoRR abs/2104.00814 (2021) - 2020
- [c11]Muthu Kumar Chandrasekaran, Guy Feigenblat, Eduard H. Hovy, Abhilasha Ravichander, Michal Shmueli-Scheuer, Anita de Waard:
Overview and Insights from the Shared Tasks at Scholarly Document Processing 2020: CL-SciSumm, LaySumm and LongSumm. SDP@EMNLP 2020: 214-224 - [c10]Abhilasha Ravichander, Eduard H. Hovy, Kaheer Suleman, Adam Trischler, Jackie Chi Kit Cheung:
On the Systematicity of Probing Contextualized Word Representations: The Case of Hypernymy in BERT. *SEM@COLING 2020: 88-102 - [i7]Abhilasha Ravichander, Yonatan Belinkov, Eduard H. Hovy:
Probing the Probing Paradigm: Does Probing Accuracy Entail Task Relevance? CoRR abs/2005.00719 (2020) - [i6]Aman Madaan, Dheeraj Rajagopal, Yiming Yang, Abhilasha Ravichander, Eduard H. Hovy, Shrimai Prabhumoye:
EIGEN: Event Influence GENeration using Pre-trained Language Models. CoRR abs/2010.11764 (2020)
2010 – 2019
- 2019
- [j1]Sebastian Zimmeck, Peter Story
, Daniel Smullen, Abhilasha Ravichander, Ziqi Wang
, Joel R. Reidenberg, N. Cameron Russell, Norman M. Sadeh:
MAPS: Scaling Privacy Compliance Analysis to a Million Apps. Proc. Priv. Enhancing Technol. 2019(3): 66-86 (2019) - [c9]Aakanksha Naik, Abhilasha Ravichander, Carolyn P. Rosé
, Eduard H. Hovy:
Exploring Numeracy in Word Embeddings. ACL (1) 2019: 3374-3380 - [c8]Abhilasha Ravichander, Aakanksha Naik, Carolyn P. Rosé
, Eduard H. Hovy:
EQUATE: A Benchmark Evaluation Framework for Quantitative Reasoning in Natural Language Inference. CoNLL 2019: 349-361 - [c7]Abhilasha Ravichander, Alan W. Black, Shomir Wilson, Thomas B. Norton, Norman M. Sadeh:
Question Answering for Privacy Policies: Combining Computational and Legal Perspectives. EMNLP/IJCNLP (1) 2019: 4946-4957 - [i5]Abhilasha Ravichander, Aakanksha Naik, Carolyn P. Rosé
, Eduard H. Hovy:
EQUATE: A Benchmark Evaluation Framework for Quantitative Reasoning in Natural Language Inference. CoRR abs/1901.03735 (2019) - [i4]Abhilasha Ravichander, Alan W. Black, Shomir Wilson, Thomas B. Norton, Norman M. Sadeh:
Question Answering for Privacy Policies: Combining Computational and Legal Perspectives. CoRR abs/1911.00841 (2019) - 2018
- [c6]Aakanksha Naik, Abhilasha Ravichander, Norman M. Sadeh, Carolyn P. Rosé, Graham Neubig:
Stress Test Evaluation for Natural Language Inference. COLING 2018: 2340-2353 - [c5]Abhilasha Ravichander, Alan W. Black:
An Empirical Study of Self-Disclosure in Spoken Dialogue Systems. SIGDIAL Conference 2018: 253-263 - [i3]Aakanksha Naik, Abhilasha Ravichander, Norman M. Sadeh, Carolyn P. Rosé
, Graham Neubig:
Stress Test Evaluation for Natural Language Inference. CoRR abs/1806.00692 (2018) - 2017
- [c4]Paul Michel, Abhilasha Ravichander, Shruti Rijhwani:
Does the Geometry of Word Embeddings Help Document Classification? A Case Study on Persistent Homology-Based Representations. Rep4NLP@ACL 2017: 235-240 - [c3]Abhilasha Ravichander, Thomas Manzini, Matthias Grabmair, Graham Neubig, Jonathan Francis, Eric Nyberg:
How Would You Say It? Eliciting Lexically Diverse Dialogue for Supervised Semantic Parsing. SIGDIAL Conference 2017: 374-383 - [i2]Paul Michel, Abhilasha Ravichander, Shruti Rijhwani:
Does the Geometry of Word Embeddings Help Document Classification? A Case Study on Persistent Homology Based Representations. CoRR abs/1705.10900 (2017) - [i1]Abhilasha Ravichander, Shruti Rijhwani, Rajat Kulshreshtha, Chirag Nagpal, Tadas Baltrusaitis, Louis-Philippe Morency:
Preserving Intermediate Objectives: One Simple Trick to Improve Learning for Hierarchical Models. CoRR abs/1706.07867 (2017) - 2015
- [c2]Abhilasha Ravichander, Supriya Vijay, Varshini Ramaseshan, S. Natarajan:
VISAGE: A Support Vector Machine Approach to Group Dynamic Analysis. ICMLA 2015: 640-643 - [c1]Alok Shankar Mysore, Vikas S. Yaligar, Imanol Arrieta Ibarra, Camelia Simoiu, Sharad Goel, Ramesh Arvind, Chiraag Sumanth, Arvind Srikantan, Bhargav HS, Mayank Pahadia, Tushar Dobha, Atif Ahmed, Mani Shankar, Himani Agarwal, Rajat Agarwal, Sai Anirudh-Kondaveeti, Shashank Arun-Gokhale, Aayush Attri, Arpita Chandra, Yogitha Chilukur, Sharath Dharmaji, Deepak Garg, Naman Gupta, Paras Gupta, Glincy Mary Jacob, Siddharth Jain, Shashank Joshi, Tarun Khajuria
, Sameeksha Khillan, Sandeep Konam, Praveen Kumar-Kolla, Sahil Loomba
, Rachit Madan, Akshansh Maharaja, Vidit Mathur, Bharat Munshi, Mohammed Nawazish, Venkata Neehar-Kurukunda, Venkat Nirmal-Gavarraju, Sonali Parashar, Harsh Parikh, Avinash Paritala, Amit Patil, Rahul Phatak, Mandar Pradhan, Abhilasha Ravichander, Krishna Sangeeth, Sreecharan Sankaranarayanan, Vibhor Sehgal, Ashrith Sheshan, Suprajha Shibiraj, Aditya Singh, Anjali Singh, Prashant Sinha, Pushkin Soni, Bipin Thomas, Kasyap Varma-Dattada, Sukanya Venkataraman, Pulkit Verma
, Ishan Yelurwar:
Investigating the "Wisdom of Crowds" at Scale. UIST (Adjunct Volume) 2015: 75-76
Coauthor Index
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last updated on 2024-08-10 01:25 CEST by the dblp team
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