Recurrent Memory Addressing for Describing Videos. - Arnav Kumar Jain; Abhinav Agarwalla; Kumar Krishna Agrawal; Pabitra Mitra (CVPR Workshops, 2017)

Playing with Embeddings : Evaluating embeddings for Robot Language Learning through MUD Games. - Anmol Gulati; Kumar Krishna Agrawal (RepEval@EMNLP, 2017)

Towards Mixed Optimization for Reinforcement Learning with Program Synthesis. - Surya Bhupatiraju; Kumar Krishna Agrawal; Rishabh Singh (CoRR, 2018)

Addressing Sample Inefficiency and Reward Bias in Inverse Reinforcement Learning. - Ilya Kostrikov; Kumar Krishna Agrawal; Sergey Levine; Jonathan Tompson (CoRR, 2018)

Model AI Assignments 2019. - Todd W. Neller; Raja Sooriamurthi; Michael Guerzhoy; Lisa Zhang; Paul G. Talaga; Christopher Archibald; Adam Summerville; Joseph C. Osborn; Cinjon Resnick; Avital Oliver; Surya Bhupatiraju; Kumar Krishna Agrawal; et al. (AAAI, 2019)

GANSynth: Adversarial Neural Audio Synthesis. - Jesse H. Engel; Kumar Krishna Agrawal; Shuo Chen; Ishaan Gulrajani; Chris Donahue; Adam Roberts (ICLR (Poster), 2019)

Discriminator-Actor-Critic: Addressing Sample Inefficiency and Reward Bias in Adversarial Imitation Learning. - Ilya Kostrikov; Kumar Krishna Agrawal; Debidatta Dwibedi; Sergey Levine; Jonathan Tompson (ICLR (Poster), 2019)

Discrete Flows: Invertible Generative Models of Discrete Data. - Dustin Tran; Keyon Vafa; Kumar Krishna Agrawal; Laurent Dinh; Ben Poole (NeurIPS, 2019)

Model AI Assignments 2020. - Todd W. Neller; Stephen Keeley; Michael Guerzhoy; Wolfgang Hönig; Jiaoyang Li 001; Sven Koenig; Ameet Soni; Krista Thomason; Lisa Zhang; Bibin Sebastian; Cinjon Resnick; Avital Oliver; et al. (AAAI, 2020)

Learning from an Exploring Demonstrator: Optimal Reward Estimation for Bandits. - Wenshuo Guo; Kumar Krishna Agrawal; Aditya Grover; Vidya K. Muthukumar; Ashwin Pananjady (AISTATS, 2022)

Context-Aware Streaming Perception in Dynamic Environments. - Gur-Eyal Sela; Ionel Gog; Justin Wong; Kumar Krishna Agrawal; Xiangxi Mo; Sukrit Kalra; Peter Schafhalter; Eric Leong; Xin Wang 066; Bharathan Balaji; Joseph Gonzalez 001; Ion Stoica (ECCV (38), 2022)

$ alpha$-ReQ : Assessing Representation Quality in Self-Supervised Learning by measuring eigenspectrum decay. - Kumar Krishna Agrawal; Arnab Kumar Mondal; Arna Ghosh; Blake A. Richards (NeurIPS, 2022)

Investigating Power laws in Deep Representation Learning. - Arna Ghosh; Arnab Kumar Mondal; Kumar Krishna Agrawal; Blake A. Richards (CoRR, 2022)

Addressing Sample Inefficiency in Multi-View Representation Learning. - Kumar Krishna Agrawal; Arna Ghosh; Adam Oberman; Blake A. Richards (CoRR, 2023)

Attribute Diversity Determines the Systematicity Gap in VQA. - Ian Berlot-Attwell; Kumar Krishna Agrawal; Annabelle Michael Carrell; Yash Sharma; Naomi Saphra (EMNLP, 2024)

Harnessing small projectors and multiple views for efficient vision pretraining. - Arna Ghosh; Kumar Krishna Agrawal; Shagun Sodhani; Adam Oberman; Blake A. Richards (NeurIPS, 2024)

Atlas: Multi-Scale Attention Improves Long Context Image Modeling. - Kumar Krishna Agrawal; Long Lian; Longchao Liu; Natalia Harguindeguy; Boyi Li; Alexander Bick; Maggie Chung; Trevor Darrell; Adam Yala (CoRR, 2025)