Manish Nagireddy

According to our database, Manish Nagireddy authored at least 15 papers between 2022 and 2024.

Collaborative distances:

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

2024

Programming Refusal with Conditional Activation Steering.

Bruce W. Lee, Inkit Padhi, Karthikeyan Natesan Ramamurthy, Erik Miehling, Pierre L. Dognin, Manish Nagireddy, Amit Dhurandhar

CoRR, 2024

When in Doubt, Cascade: Towards Building Efficient and Capable Guardrails.

Manish Nagireddy, Inkit Padhi, Soumya Ghosh, Prasanna Sattigeri

CoRR, 2024

The RealHumanEval: Evaluating Large Language Models' Abilities to Support Programmers.

Hussein Mozannar, Valerie Chen, Mohammed Alsobay, Subhro Das, Sebastian Zhao, Dennis Wei, Manish Nagireddy, Prasanna Sattigeri, Ameet Talwalkar, David A. Sontag

CoRR, 2024

Multi-Level Explanations for Generative Language Models.

Lucas Monteiro Paes, Dennis Wei, Hyo Jin Do, Hendrik Strobelt, Ronny Luss, Amit Dhurandhar, Manish Nagireddy, Karthikeyan Natesan Ramamurthy, Prasanna Sattigeri, Werner Geyer, Soumya Ghosh

CoRR, 2024

Contextual Moral Value Alignment Through Context-Based Aggregation.

Pierre L. Dognin, Jesus Rios, Ronny Luss, Inkit Padhi, Matthew D. Riemer, Miao Liu, Prasanna Sattigeri, Manish Nagireddy, Kush R. Varshney, Djallel Bouneffouf

CoRR, 2024

Alignment Studio: Aligning Large Language Models to Particular Contextual Regulations.

Swapnaja Achintalwar, Ioana Baldini, Djallel Bouneffouf, Joan Byamugisha, Maria Chang, Pierre L. Dognin, Eitan Farchi, Ndivhuwo Makondo, Aleksandra Mojsilovic, Manish Nagireddy, Karthikeyan Natesan Ramamurthy, Inkit Padhi, Orna Raz, Jesus Rios, Prasanna Sattigeri, Moninder Singh, Siphiwe Thwala, Rosario A. Uceda-Sosa, Kush R. Varshney

CoRR, 2024

Detectors for Safe and Reliable LLMs: Implementations, Uses, and Limitations.

Swapnaja Achintalwar, Adriana Alvarado Garcia, Ateret Anaby-Tavor, Ioana Baldini, Sara E. Berger, Bishwaranjan Bhattacharjee, Djallel Bouneffouf, Subhajit Chaudhury, Pin-Yu Chen, Lamogha Chiazor, Elizabeth M. Daly, Rogério Abreu de Paula, Pierre L. Dognin, Eitan Farchi, Soumya Ghosh, Michael Hind, Raya Horesh, George Kour, Ja Young Lee, Erik Miehling, Keerthiram Murugesan, Manish Nagireddy, Inkit Padhi, David Piorkowski, Ambrish Rawat, Orna Raz, Prasanna Sattigeri, Hendrik Strobelt, Sarathkrishna Swaminathan, Christoph Tillmann, Aashka Trivedi, Kush R. Varshney, Dennis Wei, Shalisha Witherspoon, Marcel Zalmanovici

CoRR, 2024

DARE to Diversify: DAta Driven and Diverse LLM REd Teaming.

Manish Nagireddy, Bernat Guillen Pegueroles, Ioana Baldini

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

ComVas: Contextual Moral Values Alignment System.

Inkit Padhi, Pierre L. Dognin, Jesus Rios, Ronny Luss, Swapnaja Achintalwar, Matthew Riemer, Miao Liu, Prasanna Sattigeri, Manish Nagireddy, Kush R. Varshney, Djallel Bouneffouf

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Value Alignment from Unstructured Text.

Inkit Padhi, Karthikeyan Natesan Ramamurthy, Prasanna Sattigeri, Manish Nagireddy, Pierre L. Dognin, Kush R. Varshney

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing: EMNLP 2024, 2024

Language Models in Dialogue: Conversational Maxims for Human-AI Interactions.

Erik Miehling, Manish Nagireddy, Prasanna Sattigeri, Elizabeth Daly, David Piorkowski, John T. Richards

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

SocialStigmaQA: A Benchmark to Uncover Stigma Amplification in Generative Language Models.

Manish Nagireddy, Lamogha Chiazor, Moninder Singh, Ioana Baldini

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Function Composition in Trustworthy Machine Learning: Implementation Choices, Insights, and Questions.

Manish Nagireddy, Moninder Singh, Samuel C. Hoffman, Evaline Ju, Karthikeyan Natesan Ramamurthy, Kush R. Varshney

CoRR, 2023

2022

A Sandbox Tool to Bias(Stress)-Test Fairness Algorithms.

Nil-Jana Akpinar, Manish Nagireddy, Logan Stapleton, Hao Fei Cheng, Haiyi Zhu, Zhiwei Steven Wu, Hoda Heidari

CoRR, 2022

Exploring How Machine Learning Practitioners (Try To) Use Fairness Toolkits.

Wesley Hanwen Deng, Manish Nagireddy, Michelle Seng Ah Lee, Jatinder Singh, Zhiwei Steven Wu, Kenneth Holstein, Haiyi Zhu

Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022