CoeViz 2: Protein Graphs Derived From Amino Acid Covariance. - Daniel Corcoran; Nicholas Maltbie; Shivchander Sudalairaj; Frazier N. Baker; Joseph Hirschfeld; Aleksey A. Porollo (Frontiers Bioinform., 2021)

On the Importance of Calibration in Semi-supervised Learning. - Charlotte Loh; Rumen Dangovski; Shivchander Sudalairaj; Seungwook Han; Ligong Han; Leonid Karlinsky; Marin Soljacic; Akash Srivastava (CoRR, 2022)

Multi-Symmetry Ensembles: Improving Diversity and Generalization via Opposing Symmetries. - Charlotte Loh; Seungwook Han; Shivchander Sudalairaj; Rumen Dangovski; Kai Xu 016; Florian Wenzel; Marin Soljacic; Akash Srivastava (ICML, 2023)

Post-processing Private Synthetic Data for Improving Utility on Selected Measures. - Hao Wang; Shivchander Sudalairaj; John Henning; Kristjan H. Greenewald; Akash Srivastava (NeurIPS, 2023)

Constructive Assimilation: Boosting Contrastive Learning Performance through View Generation Strategies. - Ligong Han; Seungwook Han; Shivchander Sudalairaj; Charlotte Loh; Rumen Dangovski; Fei Deng 001; Pulkit Agrawal 001; Dimitris N. Metaxas; Leonid Karlinsky; Tsui-Wei Weng; Akash Srivastava (CoRR, 2023)

Mitigating Confirmation Bias in Semi-supervised Learning via Efficient Bayesian Model Averaging. - Charlotte Loh; Rumen Dangovski; Shivchander Sudalairaj; Seungwook Han; Ligong Han; Leonid Karlinsky; Marin Soljacic; Akash Srivastava (Trans. Mach. Learn. Res., 2023)

Grafting Vision Transformers. - Jongwoo Park 003; Kumara Kahatapitiya; Donghyun Kim 006; Shivchander Sudalairaj; Quanfu Fan; Michael S. Ryoo (WACV, 2024)

LAB: Large-Scale Alignment for ChatBots. - Shivchander Sudalairaj; Abhishek Bhandwaldar; Aldo Pareja; Kai Xu 016; David D. Cox; Akash Srivastava (CoRR, 2024)

CDR: Customizable Density Ratios of Strong-over-weak LLMs for Preference Annotation. - Guangxuan Xu; Kai Xu 016; Shivchander Sudalairaj; Hao Wang; Akash Srivastava (CoRR, 2024)

Unveiling the Secret Recipe: A Guide For Supervised Fine-Tuning Small LLMs. - Aldo Pareja; Nikhil Shivakumar Nayak; Hao Wang; Krishnateja Killamsetty; Shivchander Sudalairaj; Wenlong Zhao 001; Seungwook Han; Abhishek Bhandwaldar; Guangxuan Xu; Kai Xu 016; Ligong Han; Luke Inglis; et al. (ICLR, 2025)

A Probabilistic Inference Approach to Inference-Time Scaling of LLMs using Particle-Based Monte Carlo Methods. - Isha Puri; Shivchander Sudalairaj; Guangxuan Xu; Kai Xu 016; Akash Srivastava (CoRR, 2025)