Abhilasha Ravichander

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 52

Top Topics

Persistent Homology

Top Venues

Publications

Da Yin, Faeze Brahman, Abhilasha Ravichander, Khyathi Raghavi Chandu, Kai-Wei Chang, Yejin Choi, Bill Yuchen Lin
Agent Lumos: Unified and Modular Training for Open-Source Language Agents. ACL (1) (2024)
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 (2024)
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? NAACL-HLT (2024)
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)
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 (2024)
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)
Faeze Brahman, Sachin Kumar, Vidhisha Balachandran, Pradeep Dasigi, Valentina Pyatkin, Abhilasha Ravichander, Sarah Wiegreffe, Nouha Dziri, Khyathi Raghavi Chandu, Jack Hessel, Yulia Tsvetkov, Noah A. Smith, Yejin Choi, Hannaneh Hajishirzi
The Art of Saying No: Contextual Noncompliance in Language Models. CoRR (2024)
Nishant Balepur, Abhilasha Ravichander, Rachel Rudinger
Artifacts or Abduction: How Do LLMs Answer Multiple-Choice Questions Without the Question? ACL (1) (2024)
Wenting Zhao, Tanya Goyal, Yu Ying Chiu, Liwei Jiang, Benjamin Newman, Abhilasha Ravichander, Khyathi Raghavi Chandu, Ronan Le Bras, Claire Cardie, Yuntian Deng, Yejin Choi
WildHallucinations: Evaluating Long-form Factuality in LLMs with Real-World Entity Queries. CoRR (2024)
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)
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)
Nishant Balepur, Abhilasha Ravichander, Rachel Rudinger
Artifacts or Abduction: How Do LLMs Answer Multiple-Choice Questions Without the Question? CoRR (2024)
Luca Soldaini, Rodney Kinney, Akshita Bhagia, Dustin Schwenk, David Atkinson, Russell Authur, Ben Bogin, Khyathi 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 (2024)
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 (2023)
Da Yin, Faeze Brahman, Abhilasha Ravichander, Khyathi Chandu, Kai-Wei Chang, Yejin Choi, Bill Yuchen Lin
Lumos: Learning Agents with Unified Data, Modular Design, and Open-Source LLMs. CoRR (2023)
Ximing Lu, Faeze Brahman, Peter West, Jaehun Jung, Khyathi 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 (2023)
Ximing Lu, Faeze Brahman, Peter West, Jaehun Jung, Khyathi Chandu, Abhilasha Ravichander, Prithviraj Ammanabrolu, Liwei Jiang, Sahana Ramnath, Nouha Dziri, Jillian Fisher, Bill 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)
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 (2023)
Abhilasha Ravichander, Joe Stacey, Marek Rei
When and Why Does Bias Mitigation Work? EMNLP (Findings) (2023)
Peter West, Ximing Lu, Nouha Dziri, Faeze Brahman, Linjie Li, Jena D. Hwang, Liwei Jiang, Jillian Fisher, Abhilasha Ravichander, Khyathi Chandu, Benjamin Newman, Pang Wei Koh, Allyson Ettinger, Yejin Choi
The Generative AI Paradox: "What It Can Create, It May Not Understand". CoRR (2023)
Bill Yuchen Lin, Abhilasha Ravichander, Ximing Lu, Nouha Dziri, Melanie Sclar, Khyathi Chandu, Chandra Bhagavatula, Yejin Choi
The Unlocking Spell on Base LLMs: Rethinking Alignment via In-Context Learning. CoRR (2023)
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 (2023)
Abhilasha Ravichander, Matt Gardner, Ana Marasovic
CONDAQA: A Contrastive Reading Comprehension Dataset for Reasoning about Negation. CoRR (2022)
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)
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 (2022)
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 (2022)
Abhilasha Ravichander, Matt Gardner, Ana Marasovic
CONDAQA: A Contrastive Reading Comprehension Dataset for Reasoning about Negation. EMNLP (2022)
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 (2021)
Abhilasha Ravichander, Yonatan Belinkov, Eduard H. Hovy
Probing the Probing Paradigm: Does Probing Accuracy Entail Task Relevance? EACL (2021)
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)
Yanai Elazar, Nora Kassner, Shauli Ravfogel, Abhilasha Ravichander, Eduard H. Hovy, Hinrich Schütze, Yoav Goldberg
Measuring and Improving Consistency in Pretrained Language Models. CoRR (2021)
Abhilasha Ravichander, Siddharth Dalmia, Maria Ryskina, Florian Metze, Eduard H. Hovy, Alan W. Black
NoiseQA: Challenge Set Evaluation for User-Centric Question Answering. CoRR (2021)
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 (2021)
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)
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 (2021)
Abhilasha Ravichander, Yonatan Belinkov, Eduard H. Hovy
Probing the Probing Paradigm: Does Probing Accuracy Entail Task Relevance? CoRR (2020)
Aman Madaan, Dheeraj Rajagopal, Yiming Yang, Abhilasha Ravichander, Eduard H. Hovy, Shrimai Prabhumoye
EIGEN: Event Influence GENeration using Pre-trained Language Models. CoRR (2020)
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)
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)
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) (2019)
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)
Abhilasha Ravichander, Aakanksha Naik, Carolyn Penstein Rosé, Eduard H. Hovy
EQUATE: A Benchmark Evaluation Framework for Quantitative Reasoning in Natural Language Inference. CoRR (2019)
Aakanksha Naik, Abhilasha Ravichander, Carolyn Penstein Rosé, Eduard H. Hovy
Exploring Numeracy in Word Embeddings. ACL (1) (2019)
Abhilasha Ravichander, Aakanksha Naik, Carolyn Penstein Rosé, Eduard H. Hovy
EQUATE: A Benchmark Evaluation Framework for Quantitative Reasoning in Natural Language Inference. CoNLL (2019)
Abhilasha Ravichander, Alan W. Black, Shomir Wilson, Thomas B. Norton, Norman M. Sadeh
Question Answering for Privacy Policies: Combining Computational and Legal Perspectives. CoRR (2019)
Aakanksha Naik, Abhilasha Ravichander, Norman M. Sadeh, Carolyn Penstein Rosé, Graham Neubig
Stress Test Evaluation for Natural Language Inference. CoRR (2018)
Aakanksha Naik, Abhilasha Ravichander, Norman M. Sadeh, Carolyn Penstein Rosé, Graham Neubig
Stress Test Evaluation for Natural Language Inference. COLING (2018)
Abhilasha Ravichander, Alan W. Black
An Empirical Study of Self-Disclosure in Spoken Dialogue Systems. SIGDIAL Conference (2018)
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)
Paul Michel, Abhilasha Ravichander, Shruti Rijhwani
Does the Geometry of Word Embeddings Help Document Classification? A Case Study on Persistent Homology Based Representations. CoRR (2017)
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)
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 (2017)
Abhilasha Ravichander, Supriya Vijay, Varshini Ramaseshan, S. Natarajan
VISAGE: A Support Vector Machine Approach to Group Dynamic Analysis. ICMLA (2015)
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)