Neel Guha

According to our database, Neel Guha authored at least 26 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Prospector Heads: Generalized Feature Attribution for Large Models & Data.

Gautam Machiraju, Alexander Derry, Arjun D. Desai, Neel Guha, Amir-Hossein Karimi, James Zou, Russ B. Altman, Christopher Ré, Parag Mallick

CoRR, 2024

Benchmarking and Building Long-Context Retrieval Models with LoCo and M2-BERT.

Jon Saad-Falcon, Daniel Y. Fu, Simran Arora, Neel Guha, Christopher Ré

CoRR, 2024

2023

LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models.

Neel Guha, Julian Nyarko, Daniel E. Ho, Christopher Ré, Adam Chilton, Aditya Narayana, Alex Chohlas-Wood, Austin Peters, Brandon Waldon, Daniel N. Rockmore, Diego Zambrano, Dmitry Talisman, Enam Hoque, Faiz Surani, Frank Fagan, Galit Sarfaty, Gregory M. Dickinson, Haggai Porat, Jason Hegland, Jessica Wu, Joe Nudell, Joel Niklaus, John J. Nay, Jonathan H. Choi, Kevin Tobia, Margaret Hagan, Megan Ma, Michael A. Livermore, Nikon Rasumov-Rahe, Nils Holzenberger, Noam Kolt, Peter Henderson, Sean Rehaag, Sharad Goel, Shang Gao, Spencer Williams, Sunny Gandhi, Tom Zur, Varun Iyer, Zehua Li

CoRR, 2023

LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models.

Neel Guha, Julian Nyarko, Daniel E. Ho, Christopher Ré, Adam Chilton, Aditya K, Alex Chohlas-Wood, Austin Peters, Brandon Waldon, Daniel N. Rockmore, Diego Zambrano, Dmitry Talisman, Enam Hoque, Faiz Surani, Frank Fagan, Galit Sarfaty, Gregory M. Dickinson, Haggai Porat, Jason Hegland, Jessica Wu, Joe Nudell, Joel Niklaus, John J. Nay, Jonathan H. Choi, Kevin Tobia, Margaret Hagan, Megan Ma, Michael A. Livermore, Nikon Rasumov-Rahe, Nils Holzenberger, Noam Kolt, Peter Henderson, Sean Rehaag, Sharad Goel, Shang Gao, Spencer Williams, Sunny Gandhi, Tom Zur, Varun Iyer, Zehua Li

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Embroid: Unsupervised Prediction Smoothing Can Improve Few-Shot Classification.

Neel Guha, Mayee F. Chen, Kush Bhatia, Azalia Mirhoseini, Frederic Sala, Christopher Ré

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Ask Me Anything: A simple strategy for prompting language models.

Simran Arora, Avanika Narayan, Mayee F. Chen, Laurel J. Orr, Neel Guha, Kush Bhatia, Ines Chami, Christopher Ré

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Don't Use a Cannon to Kill a Fly: An Efficient Cascading Pipeline for Long Documents.

Zehua Li, Neel Guha, Julian Nyarko

Proceedings of the Nineteenth International Conference on Artificial Intelligence and Law, 2023

2022

Holistic Evaluation of Language Models.

Percy Liang, Rishi Bommasani, Tony Lee, Dimitris Tsipras, Dilara Soylu, Michihiro Yasunaga, Yian Zhang, Deepak Narayanan, Yuhuai Wu, Ananya Kumar, Benjamin Newman, Binhang Yuan, Bobby Yan, Ce Zhang, Christian Cosgrove, Christopher D. Manning, Christopher Ré, Diana Acosta-Navas, Drew A. Hudson, Eric Zelikman, Esin Durmus, Faisal Ladhak, Frieda Rong, Hongyu Ren, Huaxiu Yao, Jue Wang, Keshav Santhanam, Laurel J. Orr, Lucia Zheng, Mert Yüksekgönül, Mirac Suzgun, Nathan Kim, Neel Guha, Niladri S. Chatterji, Omar Khattab, Peter Henderson, Qian Huang, Ryan Chi, Sang Michael Xie, Shibani Santurkar, Surya Ganguli, Tatsunori Hashimoto, Thomas Icard, Tianyi Zhang, Vishrav Chaudhary, William Wang, Xuechen Li, Yifan Mai, Yuhui Zhang, Yuta Koreeda

CoRR, 2022

Ask Me Anything: A simple strategy for prompting language models.

Simran Arora, Avanika Narayan, Mayee F. Chen, Laurel J. Orr, Neel Guha, Kush Bhatia, Ines Chami, Frederic Sala, Christopher Ré

CoRR, 2022

LegalBench: Prototyping a Collaborative Benchmark for Legal Reasoning.

Neel Guha, Daniel E. Ho, Julian Nyarko, Christopher Ré

CoRR, 2022

Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset.

Peter Henderson, Mark S. Krass, Lucia Zheng, Neel Guha, Christopher D. Manning, Dan Jurafsky, Daniel E. Ho

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

On the Opportunities and Risks of Foundation Models.

Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, Russ B. Altman, Simran Arora, Sydney von Arx, Michael S. Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, Erik Brynjolfsson, Shyamal Buch, Dallas Card, Rodrigo Castellon, Niladri S. Chatterji, Annie S. Chen, Kathleen Creel, Jared Quincy Davis, Dorottya Demszky, Chris Donahue, Moussa Doumbouya, Esin Durmus, Stefano Ermon, John Etchemendy, Kawin Ethayarajh, Li Fei-Fei, Chelsea Finn, Trevor Gale, Lauren Gillespie, Karan Goel, Noah D. Goodman, Shelby Grossman, Neel Guha, Tatsunori Hashimoto, Peter Henderson, John Hewitt, Daniel E. Ho, Jenny Hong, Kyle Hsu, Jing Huang, Thomas Icard, Saahil Jain, Dan Jurafsky, Pratyusha Kalluri, Siddharth Karamcheti, Geoff Keeling, Fereshte Khani, Omar Khattab, Pang Wei Koh, Mark S. Krass, Ranjay Krishna, Rohith Kuditipudi, et al.

CoRR, 2021

When Does Pretraining Help? Assessing Self-Supervised Learning for Law and the CaseHOLD Dataset.

Lucia Zheng, Neel Guha, Brandon R. Anderson, Peter Henderson, Daniel E. Ho

CoRR, 2021

When does pretraining help?: assessing self-supervised learning for law and the CaseHOLD dataset of 53, 000+ legal holdings.

Lucia Zheng, Neel Guha, Brandon R. Anderson, Peter Henderson, Daniel E. Ho

Proceedings of the ICAIL '21: Eighteenth International Conference for Artificial Intelligence and Law, São Paulo Brazil, June 21, 2021

Leveraging Administrative Data for Bias Audits: Assessing Disparate Coverage with Mobility Data for COVID-19 Policy.

Amanda Coston, Neel Guha, Derek Ouyang, Lisa Lu, Alexandra Chouldechova, Daniel E. Ho

Proceedings of the FAccT '21: 2021 ACM Conference on Fairness, 2021

Bootleg: Chasing the Tail with Self-Supervised Named Entity Disambiguation.

Laurel J. Orr, Megan Leszczynski, Neel Guha, Sen Wu, Simran Arora, Xiao Ling, Christopher Ré

Proceedings of the 11th Conference on Innovative Data Systems Research, 2021

2019

Machine Learning for AC Optimal Power Flow.

Neel Guha, Zhecheng Wang, Matt Wytock, Arun Majumdar

CoRR, 2019

One-Shot Federated Learning.

Neel Guha, Ameet Talwalkar, Virginia Smith

CoRR, 2019

2018

Knowledge Aggregation via Epsilon Model Spaces.

Neel Guha

CoRR, 2018

2017

Semantic Identification of Web Browsing Sessions.

Neel Guha

CoRR, 2017

Behavioral Tracing of Twitter Accounts.

Neel Guha

Proceedings of the 5th Workshop on Society, 2017

2016

Semantic Identification Attacks on Web Browsing.

Neel Guha

CoRR, 2016

2014

Tutoring from the desktop: facilitating learning through Google+ hangouts.

Neel Guha

Proceedings of the 23rd International World Wide Web Conference, 2014

2013

Course-specific search engines: semi-automated methods for identifying high quality topic-specific corpora.

Neel Guha, Matt Wytock

Proceedings of the 22nd International World Wide Web Conference, 2013

Spy Watch: A Tool for Transparency in Web Tracking.

Neel Guha

Proceedings of the Workshop on Society, 2013

Course specific search engines: a study in incorporating context into search.

Neel Guha

Proceedings of the ESAIR'13, 2013