Historical Research Using Email Archives. - Sudheendra Hangal; Vihari Piratla; Chaiyasit Manovit; Peter Chan; Glynn Edwards; Monica S. Lam (CHI Extended Abstracts, 2015)

Generalizing Across Domains via Cross-Gradient Training. - Shiv Shankar; Vihari Piratla; Soumen Chakrabarti; Siddhartha Chaudhuri; Preethi Jyothi; Sunita Sarawagi (ICLR (Poster), 2018)

Topic Sensitive Attention on Generic Corpora Corrects Sense Bias in Pretrained Embeddings. - Vihari Piratla; Sunita Sarawagi; Soumen Chakrabarti (ACL (1), 2019)

Parallel Iterative Edit Models for Local Sequence Transduction. - Abhijeet Awasthi; Sunita Sarawagi; Rasna Goyal; Sabyasachi Ghosh; Vihari Piratla (EMNLP/IJCNLP (1), 2019)

NLP Service APIs and Models for Efficient Registration of New Clients. - Sahil Shah; Vihari Piratla; Soumen Chakrabarti; Sunita Sarawagi (EMNLP (Findings), 2020)

Efficient Domain Generalization via Common-Specific Low-Rank Decomposition. - Vihari Piratla; Praneeth Netrapalli; Sunita Sarawagi (ICML, 2020)

Untapped Potential of Data Augmentation: A Domain Generalization Viewpoint. - Vihari Piratla; Shiv Shankar (CoRR, 2020)

Training for the Future: A Simple Gradient Interpolation Loss to Generalize Along Time. - Anshul Nasery; Soumyadeep Thakur; Vihari Piratla; Abir De; Sunita Sarawagi (NeurIPS, 2021)

Active Assessment of Prediction Services as Accuracy Surface Over Attribute Combinations. - Vihari Piratla; Soumen Chakrabarti; Sunita Sarawagi (NeurIPS, 2021)

An Analysis of Frame-skipping in Reinforcement Learning. - Shivaram Kalyanakrishnan; Siddharth Aravindan; Vishwajeet Bagdawat; Varun Bhatt; Harshith Goka; Archit Gupta; Kalpesh Krishna; Vihari Piratla (CoRR, 2021)

Focus on the Common Good: Group Distributional Robustness Follows. - Vihari Piratla; Praneeth Netrapalli; Sunita Sarawagi (ICLR, 2022)

Web-based Elicitation of Human Perception on mixup Data. - Katherine M. Collins; Umang Bhatt; Weiyang Liu; Vihari Piratla; Bradley C. Love; Adrian Weller (CoRR, 2022)

Implicit Training of Energy Model for Structure Prediction. - Shiv Shankar; Vihari Piratla (CoRR, 2022)

Use perturbations when learning from explanations. - Juyeon Heo; Vihari Piratla; Matthew Wicker; Adrian Weller (NeurIPS, 2023)

Certification of Distributional Individual Fairness. - Matthew Wicker; Vihari Piratla; Adrian Weller (NeurIPS, 2023)

Human-in-the-Loop Mixup. - Katherine M. Collins; Umang Bhatt; Weiyang Liu; Vihari Piratla; Ilia Sucholutsky; Bradley C. Love; Adrian Weller (UAI, 2023)

Robustness, Evaluation and Adaptation of Machine Learning Models in the Wild. - Vihari Piratla (CoRR, 2023)

Robust Learning from Explanations. - Juyeon Heo; Vihari Piratla; Matthew Wicker; Adrian Weller (CoRR, 2023)

Estimation of Concept Explanations Should be Uncertainty Aware. - Vihari Piratla; Juyeon Heo; Sukriti Singh; Adrian Weller (CoRR, 2023)

LLMs on interactive feature collections with implicit dynamic decision strategy. - Juyeon Heo; Vihari Piratla; Kyunghyun Lee 006; Hyonkeun Joh; Adrian Weller (COLING, 2025)

Model Guidance via Robust Feature Attribution. - Mihnea Ghitu; Matthew Wicker; Vihari Piratla (CoRR, 2025)