An End-To-End Machine Learning Pipeline That Ensures Fairness Policies. - Samiulla Shaikh; Harit Vishwakarma; Sameep Mehta; Kush R. Varshney; Karthikeyan Natesan Ramamurthy; Dennis Wei (CoRR, 2017)

Cogniculture: Towards a Better Human-Machine Co-evolution. - Rakesh Rameshrao Pimplikar; Kushal Mukherjee; Gyana R. Parija; Harit Vishwakarma; Ramasuri Narayanam; Sarthak Ahuja; Rohith Dwarakanath Vallam; Ritwik Chaudhuri; Joydeep Mondal (CoRR, 2017)

Know Thy Neighbors, and More!: Studying the Role of Context in Entity Recommendation. - Sumit Bhatia; Harit Vishwakarma (HT, 2018)

Quantum Embedding of Knowledge for Reasoning. - Dinesh Garg; Shajith Ikbal; Santosh K. Srivastava; Harit Vishwakarma; Hima P. Karanam; L. Venkata Subramaniam (NeurIPS, 2019)

Optimal Lottery Tickets via Subset Sum: Logarithmic Over-Parameterization is Sufficient. - Ankit Pensia; Shashank Rajput; Alliot Nagle; Harit Vishwakarma; Dimitris S. Papailiopoulos (NeurIPS, 2020)

Attack of the Tails: Yes, You Really Can Backdoor Federated Learning. - Hongyi Wang 001; Kartik Sreenivasan; Shashank Rajput; Harit Vishwakarma; Saurabh Agarwal; Jy-yong Sohn; Kangwook Lee 001; Dimitris S. Papailiopoulos (NeurIPS, 2020)

Optimal Lottery Tickets via SubsetSum: Logarithmic Over-Parameterization is Sufficient. - Ankit Pensia; Shashank Rajput; Alliot Nagle; Harit Vishwakarma; Dimitris S. Papailiopoulos (CoRR, 2020)

Universalizing Weak Supervision. - Changho Shin; Winfred Li; Harit Vishwakarma; Nicholas Carl Roberts; Frederic Sala (ICLR, 2022)

Lifting Weak Supervision To Structured Prediction. - Harit Vishwakarma; Frederic Sala (NeurIPS, 2022)

Good Data from Bad Models : Foundations of Threshold-based Auto-labeling. - Harit Vishwakarma; Heguang Lin; Frederic Sala; Ramya Korlakai Vinayak (CoRR, 2022)

Lifting Weak Supervision To Structured Prediction. - Harit Vishwakarma; Nicholas Roberts; Frederic Sala (CoRR, 2022)

Train 'n Trade: Foundations of Parameter Markets. - Tzu-Heng Huang; Harit Vishwakarma; Frederic Sala (NeurIPS, 2023)

Promises and Pitfalls of Threshold-based Auto-labeling. - Harit Vishwakarma; Heguang Lin; Frederic Sala; Ramya Korlakai Vinayak (NeurIPS, 2023)

Taming False Positives in Out-of-Distribution Detection with Human Feedback. - Harit Vishwakarma; Heguang Lin; Ramya Korlakai Vinayak (AISTATS, 2024)

OTTER: Effortless Label Distribution Adaptation of Zero-shot Models. - Changho Shin; Jitian Zhao; Sonia Cromp; Harit Vishwakarma; Frederic Sala (NeurIPS, 2024)

Pearls from Pebbles: Improved Confidence Functions for Auto-labeling. - Harit Vishwakarma; Yi Chen; Sui Jiet Tay; Satya Sai Srinath Namburi; Frederic Sala; Ramya Korlakai Vinayak (NeurIPS, 2024)

OTTER: Improving Zero-Shot Classification via Optimal Transport. - Changho Shin; Jitian Zhao; Sonia Cromp; Harit Vishwakarma; Frederic Sala (CoRR, 2024)

Pearls from Pebbles: Improved Confidence Functions for Auto-labeling. - Harit Vishwakarma; Reid Chen; Sui Jiet Tay; Satya Sai Srinath Namburi; Frederic Sala; Ramya Korlakai Vinayak (CoRR, 2024)

Monty Hall and Optimized Conformal Prediction to Improve Decision-Making with LLMs. - Harit Vishwakarma; Alan Mishler; Thomas Cook; Niccolò Dalmasso; Natraj Raman; Sumitra Ganesh (CoRR, 2025)

ScriptoriumWS: A Code Generation Assistant for Weak Supervision. - Tzu-Heng Huang; Catherine Cao; Spencer Schoenberg; Harit Vishwakarma; Nicholas Carl Roberts; Frederic Sala (CoRR, 2025)

Adaptive Scoring and Thresholding with Human Feedback for Robust Out-of-Distribution Detection. - Daisuke Yamada; Harit Vishwakarma; Ramya Korlakai Vinayak (CoRR, 2025)

Time To Impeach LLM-as-a-Judge: Programs are the Future of Evaluation. - Tzu-Heng Huang; Harit Vishwakarma; Frederic Sala (CoRR, 2025)