Leveraging Facebook's Free Basics Engine for Web Service Deployment in Developing Regions. - Siddharth Singh; Vedant Nanda; Rijurekha Sen; Satadal Sengupta; Ponnurangam Kumaraguru; Krishna P. Gummadi (ICTD, 2017)

An Empirical Analysis of Facebook's Free Basics. - Siddharth Singh; Vedant Nanda; Rijurekha Sen; Sohaib Ahmad; Satadal Sengupta; Amreesh Phokeer; Zaid Ahmed Farooq; Taslim Arefin Khan; Ponnurangam Kumaraguru; Ihsan Ayyub Qazi; David R. Choffnes; Krishna P. Gummadi (SIGMETRICS (Abstracts), 2017)

Stop the KillFies! Using Deep Learning Models to Identify Dangerous Selfies. - Vedant Nanda; Hemank Lamba; Divyansh Agarwal; Megha Arora; Niharika Sachdeva; Ponnurangam Kumaraguru (WWW (Companion Volume), 2018)

On the Long-term Impact of Algorithmic Decision Policies: Effort Unfairness and Feature Segregation through Social Learning. - Hoda Heidari; Vedant Nanda; Krishna P. Gummadi (ICML, 2019)

Balancing the Tradeoff between Profit and Fairness in Rideshare Platforms during High-Demand Hours. - Vedant Nanda; Pan Xu 001; Karthik Abinav Sankararaman; John P. Dickerson; Aravind Srinivasan (AAAI, 2020)

Unifying Model Explainability and Robustness via Machine-Checkable Concepts. - Vedant Nanda; Till Speicher; John P. Dickerson; Krishna P. Gummadi; Muhammad Bilal Zafar (CoRR, 2020)

Fairness Through Robustness: Investigating Robustness Disparity in Deep Learning. - Vedant Nanda; Samuel Dooley; Sahil Singla 002; Soheil Feizi; John P. Dickerson (FAccT, 2021)

Technical Challenges for Training Fair Neural Networks. - Valeriia Cherepanova; Vedant Nanda; Micah Goldblum; John P. Dickerson; Tom Goldstein (CoRR, 2021)

Exploring Alignment of Representations with Human Perception. - Vedant Nanda; Ayan Majumdar; Camila Kolling; John P. Dickerson; Krishna P. Gummadi; Bradley C. Love; Adrian Weller (CoRR, 2021)

Rawlsian Fairness in Online Bipartite Matching: Two-sided, Group, and Individual. - Seyed A. Esmaeili; Sharmila Duppala; Vedant Nanda; Aravind Srinivasan; John P. Dickerson (AAMAS, 2022)

Measuring Representational Robustness of Neural Networks Through Shared Invariances. - Vedant Nanda; Till Speicher; Camila Kolling; John P. Dickerson; Krishna P. Gummadi; Adrian Weller (ICML, 2022)

Rawlsian Fairness in Online Bipartite Matching: Two-Sided, Group, and Individual. - Seyed A. Esmaeili; Sharmila Duppala; Davidson Cheng; Vedant Nanda; Aravind Srinivasan; John P. Dickerson (AAAI, 2023)

Do Invariances in Deep Neural Networks Align with Human Perception? - Vedant Nanda; Ayan Majumdar; Camila Kolling; John P. Dickerson; Krishna P. Gummadi; Bradley C. Love; Adrian Weller (AAAI, 2023)

What Happens During Finetuning of Vision Transformers: An Invariance Based Investigation. - Gabriele Merlin; Vedant Nanda; Ruchit Rawal; Mariya Toneva (CoLLAs, 2023)

Diffused Redundancy in Pre-trained Representations. - Vedant Nanda; Till Speicher; John P. Dickerson; Krishna P. Gummadi; Soheil Feizi; Adrian Weller (NeurIPS, 2023)

Pointwise Representational Similarity. - Camila Kolling; Till Speicher; Vedant Nanda; Mariya Toneva; Krishna P. Gummadi (CoRR, 2023)

Towards Reliable Latent Knowledge Estimation in LLMs: In-Context Learning vs. Prompting Based Factual Knowledge Extraction. - Qinyuan Wu; Mohammad Aflah Khan; Soumi Das; Vedant Nanda; Bishwamittra Ghosh; Camila Kolling; Till Speicher; Laurent Bindschaedler; Krishna P. Gummadi; Evimaria Terzi (CoRR, 2024)

Lawma: The Power of Specialization for Legal Tasks. - Ricardo Dominguez-Olmedo; Vedant Nanda; Rediet Abebe; Stefan Bechtold; Christoph Engel; Jens Frankenreiter; Krishna P. Gummadi; Moritz Hardt; Michael Livermore (CoRR, 2024)

Understanding Memorisation in LLMs: Dynamics, Influencing Factors, and Implications. - Till Speicher; Mohammad Aflah Khan; Qinyuan Wu; Vedant Nanda; Soumi Das; Bishwamittra Ghosh; Krishna P. Gummadi; Evimaria Terzi (CoRR, 2024)

The Impact of Inference Acceleration Strategies on Bias of LLMs. - Elisabeth Kirsten; Ivan Habernal; Vedant Nanda; Muhammad Bilal Zafar (CoRR, 2024)

Understanding the Role of Invariance in Transfer Learning. - Till Speicher; Vedant Nanda; Krishna P. Gummadi (Trans. Mach. Learn. Res., 2024)

Foundations of Trustworthy Deep Learning: Fairness, robustness, and Explainability. - Vedant Nanda (2024)

Lawma: The Power of Specialization for Legal Annotation. - Ricardo Dominguez-Olmedo; Vedant Nanda; Rediet Abebe; Stefan Bechtold; Christoph Engel; Jens Frankenreiter; Krishna P. Gummadi; Moritz Hardt; Michael Livermore (ICLR, 2025)

The Impact of Inference Acceleration on Bias of LLMs. - Elisabeth Kirsten; Ivan Habernal; Vedant Nanda; Muhammad Bilal Zafar (NAACL (Long Papers), 2025)

Towards Reliable Latent Knowledge Estimation in LLMs: Zero-Prompt Many-Shot Based Factual Knowledge Extraction. - Qinyuan Wu; Mohammad Aflah Khan; Soumi Das; Vedant Nanda; Bishwamittra Ghosh; Camila Kolling; Till Speicher; Laurent Bindschaedler; Krishna P. Gummadi; Evimaria Terzi (WSDM, 2025)

Investigating the Effects of Fairness Interventions Using Pointwise Representational Similarity. - Camila Kolling; Till Speicher; Vedant Nanda; Mariya Toneva; Krishna P. Gummadi (Trans. Mach. Learn. Res., 2025)