Abhilasha Ravichander

76 papers A* 8A 2B 3C 1Journal 41Unranked 20
YearRankTypeTitle / Venue / Authors
2026 J jnl
Fractional Rotation, Full Potential? Investigating Performance and Convergence of Partial RoPE.
CoRR
Mohammad Aflah Khan, Krishna P. Gummadi, Manish Gupta, Abhilasha Ravichander
2026 J jnl
In Agents We Trust, but Who Do Agents Trust? Latent Source Preferences Steer LLM Generations.
CoRR
Mohammad Aflah Khan, Mahsa Amani, Soumi Das, Bishwamittra Ghosh, Qinyuan Wu, Krishna P. Gummadi, Manish Gupta, Abhilasha Ravichander
2025 — conf
HALoGEN: Fantastic LLM Hallucinations and Where to Find Them.
ACL (1)
Abhilasha Ravichander, Shrusti Ghela, David Wadden, Yejin Choi
2025 J jnl
HALoGEN: Fantastic LLM Hallucinations and Where to Find Them.
CoRR
Abhilasha Ravichander, Shrusti Ghela, David Wadden, Yejin Choi
2025 — conf
Information-Guided Identification of Training Data Imprint in (Proprietary) Large Language Models.
NAACL (Long Papers)
Abhilasha Ravichander, Jillian Fisher, Taylor Sorensen, Ximing Lu, Maria Antoniak, Bill Yuchen Lin, Niloofar Mireshghallah, Chandra Bhagavatula, Yejin Choi
2025 J jnl
Information-Guided Identification of Training Data Imprint in (Proprietary) Large Language Models.
CoRR
Abhilasha Ravichander, Jillian Fisher, Taylor Sorensen, Ximing Lu, Yuchen Lin, Maria Antoniak, Niloofar Mireshghallah, Chandra Bhagavatula, Yejin Choi
2025 J jnl
Model State Arithmetic for Machine Unlearning.
CoRR
Keivan Rezaei, Mehrdad Saberi, Abhilasha Ravichander, Soheil Feizi
2025 J jnl
RESTOR: Knowledge Recovery in Machine Unlearning.
Trans. Mach. Learn. Res.
Keivan Rezaei, Khyathi Raghavi Chandu, Soheil Feizi, Yejin Choi, Faeze Brahman, Abhilasha Ravichander
2025 — conf
Reverse Question Answering: Can an LLM Write a Question so Hard (or Bad) that it Can't Answer?
NAACL (Short Papers)
Nishant Balepur, Feng Gu, Abhilasha Ravichander, Shi Feng, Jordan Lee Boyd-Graber, Rachel Rudinger
2025 J jnl
The Curious Case of Factuality Finetuning: Models' Internal Beliefs Can Improve Factuality.
CoRR
Benjamin Newman, Abhilasha Ravichander, Jaehun Jung, Rui Xin, Hamish Ivison, Yegor Kuznetsov, Pang Wei Koh, Yejin Choi
2025 J jnl
The Surprising Effectiveness of Membership Inference with Simple N-Gram Coverage.
CoRR
Skyler Hallinan, Jaehun Jung, Melanie Sclar, Ximing Lu, Abhilasha Ravichander, Sahana Ramnath, Yejin Choi, Sai Praneeth Karimireddy, Niloofar Mireshghallah, Xiang Ren
2025 — conf
What Has Been Lost with Synthetic Evaluation?
EMNLP (Findings)
Alexander Gill, Abhilasha Ravichander, Ana Marasovic
2025 J jnl
What Has Been Lost with Synthetic Evaluation?
CoRR
Alexander Gill, Abhilasha Ravichander, Ana Marasovic
2025 J jnl
Why and How LLMs Hallucinate: Connecting the Dots with Subsequence Associations.
CoRR
Yiyou Sun, Yu Gai, Lijie Chen, Abhilasha Ravichander, Yejin Choi, Dawn Song
2025 A* conf
WildBench: Benchmarking LLMs with Challenging Tasks from Real Users in the Wild.
ICLR
Bill Yuchen Lin, Yuntian Deng, Khyathi Raghavi Chandu, Abhilasha Ravichander, Valentina Pyatkin, Nouha Dziri, Ronan Le Bras, Yejin Choi
2024 — conf
Agent Lumos: Unified and Modular Training for Open-Source Language Agents.
ACL (1)
Da Yin, Faeze Brahman, Abhilasha Ravichander, Khyathi Raghavi Chandu, Kai-Wei Chang, Yejin Choi, Bill Yuchen Lin
2024 — conf
Artifacts or Abduction: How Do LLMs Answer Multiple-Choice Questions Without the Question?
ACL (1)
Nishant Balepur, Abhilasha Ravichander, Rachel Rudinger
2024 J jnl
Artifacts or Abduction: How Do LLMs Answer Multiple-Choice Questions Without the Question?
CoRR
Nishant Balepur, Abhilasha Ravichander, Rachel Rudinger
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 — conf
Incorporating Taxonomic Reasoning and Regulatory Knowledge into Automated Privacy Question Answering.
WISE (1)
Abhilasha Ravichander, Ian Yang, Rex Chen, Shomir Wilson, Thomas B. Norton, Norman M. Sadeh
2024 — conf
MacGyver: Are Large Language Models Creative Problem Solvers?
NAACL-HLT
Yufei Tian, Abhilasha Ravichander, Lianhui Qin, Ronan Le Bras, Raja Marjieh, Nanyun Peng, Yejin Choi, Thomas L. Griffiths, Faeze Brahman
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 J jnl
RESTOR: Knowledge Recovery through Machine Unlearning.
CoRR
Keivan Rezaei, Khyathi Raghavi Chandu, Soheil Feizi, Yejin Choi, Faeze Brahman, Abhilasha Ravichander
2024 J jnl
Reverse Question Answering: Can an LLM Write a Question so Hard (or Bad) that it Can't Answer?
CoRR
Nishant Balepur, Feng Gu, Abhilasha Ravichander, Shi Feng, Jordan L. Boyd-Graber, Rachel Rudinger
2024 A* conf
The Art of Saying No: Contextual Noncompliance in Language Models.
NeurIPS
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, Hanna Hajishirzi
2024 J jnl
The Art of Saying No: Contextual Noncompliance in Language Models.
CoRR
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
2024 A* conf
The Generative AI Paradox: "What It Can Create, It May Not Understand".
ICLR
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
2024 A* conf
The Unlocking Spell on Base LLMs: Rethinking Alignment via In-Context Learning.
ICLR
Bill Yuchen Lin, Abhilasha Ravichander, Ximing Lu, Nouha Dziri, Melanie Sclar, Khyathi Raghavi Chandu, Chandra Bhagavatula, Yejin Choi
2024 A* conf
Understanding How to Inform Blind and Low-Vision Users about Data Privacy through Privacy Question Answering Assistants.
USENIX Security Symposium
Yuanyuan Feng, Abhilasha Ravichander, Yaxing Yao, Shikun Zhang, Rex Chen, Shomir Wilson, Norman Sadeh
2024 A* conf
What's In My Big Data?
ICLR
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
2024 J jnl
WildBench: Benchmarking LLMs with Challenging Tasks from Real Users in the Wild.
CoRR
Bill Yuchen Lin, Yuntian Deng, Khyathi Raghavi Chandu, Faeze Brahman, Abhilasha Ravichander, Valentina Pyatkin, Nouha Dziri, Ronan Le Bras, Yejin Choi
2024 J jnl
WildHallucinations: Evaluating Long-form Factuality in LLMs with Real-World Entity Queries.
CoRR
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
2023 A* conf
Inference-Time Policy Adapters (IPA): Tailoring Extreme-Scale LMs without Fine-tuning.
EMNLP
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
2023 J jnl
Inference-Time Policy Adapters (IPA): Tailoring Extreme-Scale LMs without Fine-tuning.
CoRR
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
2023 J jnl
Lumos: Learning Agents with Unified Data, Modular Design, and Open-Source LLMs.
CoRR
Da Yin, Faeze Brahman, Abhilasha Ravichander, Khyathi Raghavi Chandu, Kai-Wei Chang, Yejin Choi, Bill Yuchen Lin
2023 J jnl
MacGyver: Are Large Language Models Creative Problem Solvers?
CoRR
Yufei Tian, Abhilasha Ravichander, Lianhui Qin, Ronan Le Bras, Raja Marjieh, Nanyun Peng, Yejin Choi, Thomas L. Griffiths, Faeze Brahman
2023 — ed.
Proceedings of the 8th Workshop on Representation Learning for NLP, RepL4NLP@ACL 2023, Toronto, Canada, July 13, 2023.
RepL4NLP@ACL
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
2023 J jnl
The Generative AI Paradox: "What It Can Create, It May Not Understand".
CoRR
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
2023 J jnl
The Unlocking Spell on Base LLMs: Rethinking Alignment via In-Context Learning.
CoRR
Bill Yuchen Lin, Abhilasha Ravichander, Ximing Lu, Nouha Dziri, Melanie Sclar, Khyathi Raghavi Chandu, Chandra Bhagavatula, Yejin Choi
2023 J jnl
Understanding How to Inform Blind and Low-Vision Users about Data Privacy through Privacy Question Answering Assistants.
CoRR
Yuanyuan Feng, Abhilasha Ravichander, Yaxing Yao, Shikun Zhang, Rex Chen, Shomir Wilson, Norman Sadeh
2023 J jnl
What's In My Big Data?
CoRR
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
2023 — conf
When and Why Does Bias Mitigation Work?
EMNLP (Findings)
Abhilasha Ravichander, Joe Stacey, Marek Rei
2022 B conf
A Tale of Two Regulatory Regimes: Creation and Analysis of a Bilingual Privacy Policy Corpus.
LREC
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
2022 A* conf
CONDAQA: A Contrastive Reading Comprehension Dataset for Reasoning about Negation.
EMNLP
Abhilasha Ravichander, Matt Gardner, Ana Marasovic
2022 J jnl
CONDAQA: A Contrastive Reading Comprehension Dataset for Reasoning about Negation.
CoRR
Abhilasha Ravichander, Matt Gardner, Ana Marasovic
2022 J jnl
Exploring and Improving the Accessibility of Data Privacy-related Information for People Who Are Blind or Low-vision.
CoRR
Yuanyuan Feng, Abhilasha Ravichander, Yaxing Yao, Shikun Zhang, Norman Sadeh
2022 J jnl
Measuring Causal Effects of Data Statistics on Language Model's 'Factual' Predictions.
CoRR
Yanai Elazar, Nora Kassner, Shauli Ravfogel, Amir Feder, Abhilasha Ravichander, Marius Mosbach, Yonatan Belinkov, Hinrich Schütze, Yoav Goldberg
2021 — conf
Breaking Down Walls of Text: How Can NLP Benefit Consumer Privacy?
ACL/IJCNLP (1)
Abhilasha Ravichander, Alan W. Black, Thomas B. Norton, Shomir Wilson, Norman M. Sadeh
2021 J jnl
CURIE: An Iterative Querying Approach for Reasoning About Situations.
CoRR
Dheeraj Rajagopal, Aman Madaan, Niket Tandon, Yiming Yang, Shrimai Prabhumoye, Abhilasha Ravichander, Peter Clark, Eduard H. Hovy
2021 J jnl
Erratum: Measuring and Improving Consistency in Pretrained Language Models.
Trans. Assoc. Comput. Linguistics
Yanai Elazar, Nora Kassner, Shauli Ravfogel, Abhilasha Ravichander, Eduard H. Hovy, Hinrich Schütze, Yoav Goldberg
2021 J jnl
Measuring and Improving Consistency in Pretrained Language Models.
CoRR
Yanai Elazar, Nora Kassner, Shauli Ravfogel, Abhilasha Ravichander, Eduard H. Hovy, Hinrich Schütze, Yoav Goldberg
2021 J jnl
Measuring and Improving Consistency in Pretrained Language Models.
Trans. Assoc. Comput. Linguistics
Yanai Elazar, Nora Kassner, Shauli Ravfogel, Abhilasha Ravichander, Eduard H. Hovy, Hinrich Schütze, Yoav Goldberg
2021 A conf
NoiseQA: Challenge Set Evaluation for User-Centric Question Answering.
EACL
Abhilasha Ravichander, Siddharth Dalmia, Maria Ryskina, Florian Metze, Eduard H. Hovy, Alan W. Black
2021 J jnl
NoiseQA: Challenge Set Evaluation for User-Centric Question Answering.
CoRR
Abhilasha Ravichander, Siddharth Dalmia, Maria Ryskina, Florian Metze, Eduard H. Hovy, Alan W. Black
2021 A conf
Probing the Probing Paradigm: Does Probing Accuracy Entail Task Relevance?
EACL
Abhilasha Ravichander, Yonatan Belinkov, Eduard H. Hovy
2020 J jnl
EIGEN: Event Influence GENeration using Pre-trained Language Models.
CoRR
Aman Madaan, Dheeraj Rajagopal, Yiming Yang, Abhilasha Ravichander, Eduard H. Hovy, Shrimai Prabhumoye
2020 — conf
On the Systematicity of Probing Contextualized Word Representations: The Case of Hypernymy in BERT.
*SEM@COLING
Abhilasha Ravichander, Eduard H. Hovy, Kaheer Suleman, Adam Trischler, Jackie Chi Kit Cheung
2020 — conf
Overview and Insights from the Shared Tasks at Scholarly Document Processing 2020: CL-SciSumm, LaySumm and LongSumm.
SDP@EMNLP
Muthu Kumar Chandrasekaran, Guy Feigenblat, Eduard H. Hovy, Abhilasha Ravichander, Michal Shmueli-Scheuer, Anita de Waard
2020 J jnl
Probing the Probing Paradigm: Does Probing Accuracy Entail Task Relevance?
CoRR
Abhilasha Ravichander, Yonatan Belinkov, Eduard H. Hovy
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 J jnl
MAPS: Scaling Privacy Compliance Analysis to a Million Apps.
Proc. Priv. Enhancing Technol.
Sebastian Zimmeck, Peter Story, Daniel Smullen, Abhilasha Ravichander, Ziqi Wang, Joel R. Reidenberg, N. Cameron Russell, Norman M. Sadeh
2019 — conf
Question Answering for Privacy Policies: Combining Computational and Legal Perspectives.
EMNLP/IJCNLP (1)
Abhilasha Ravichander, Alan W. Black, Shomir Wilson, Thomas B. Norton, Norman M. Sadeh
2019 J jnl
Question Answering for Privacy Policies: Combining Computational and Legal Perspectives.
CoRR
Abhilasha Ravichander, Alan W. Black, Shomir Wilson, Thomas B. Norton, Norman M. Sadeh
2018 — conf
An Empirical Study of Self-Disclosure in Spoken Dialogue Systems.
SIGDIAL Conference
Abhilasha Ravichander, Alan W. Black
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 J jnl
Does the Geometry of Word Embeddings Help Document Classification? A Case Study on Persistent Homology Based Representations.
CoRR
Paul Michel, Abhilasha Ravichander, Shruti Rijhwani
2017 — conf
Does the Geometry of Word Embeddings Help Document Classification? A Case Study on Persistent Homology-Based Representations.
Rep4NLP@ACL
Paul Michel, Abhilasha Ravichander, Shruti Rijhwani
2017 — conf
How Would You Say It? Eliciting Lexically Diverse Dialogue for Supervised Semantic Parsing.
SIGDIAL Conference
Abhilasha Ravichander, Thomas Manzini, Matthias Grabmair, Graham Neubig, Jonathan Francis, Eric Nyberg
2017 J jnl
Preserving Intermediate Objectives: One Simple Trick to Improve Learning for Hierarchical Models.
CoRR
Abhilasha Ravichander, Shruti Rijhwani, Rajat Kulshreshtha, Chirag Nagpal, Tadas Baltrusaitis, Louis-Philippe Morency
2015 — conf
Investigating the "Wisdom of Crowds" at Scale.
UIST (Adjunct Volume)
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
2015 C conf
VISAGE: A Support Vector Machine Approach to Group Dynamic Analysis.
ICMLA
Abhilasha Ravichander, Supriya Vijay, Varshini Ramaseshan, S. Natarajan