Kumar Krishna Agrawal

According to our database, Kumar Krishna Agrawal authored at least 22 papers between 2017 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

Inference Time Context Sparsity: Illusion or Opportunity?

Sahil Joshi, Prithvi Dixit, Agniva Chowdhury, Anshumali Shrivastava, Joseph E. Gonzalez, Ion Stoica, Kumar Krishna Agrawal, Aditya Desai

CoRR, May, 2026

2025

RedunCut: Measurement-Driven Sampling and Accuracy Performance Modeling for Low-Cost Live Video Analytics.

Gur-Eyal Sela, Kumar Krishna Agrawal, Bharathan Balaji, Joseph Gonzalez, Ion Stoica

CoRR, December, 2025

Pillar-0: A New Frontier for Radiology Foundation Models.

Kumar Krishna Agrawal, Longchao Liu, Long Lian, Michael Nercessian, Natalia Harguindeguy, Yufu Wu, Peter Mikhael, Gigin Lin, Lecia V. Sequist, Florian Fintelmann, Trevor Darrell, Yutong Bai, Maggie Chung, Adam Yala

CoRR, November, 2025

vAttention: Verified Sparse Attention.

Aditya Desai, Kumar Krishna Agrawal, Shuo Yang, Alejandro Cuadron, Luis Gaspar Schroeder, Matei Zaharia, Joseph E. Gonzalez, Ion Stoica

CoRR, October, 2025

Tracing the Representation Geometry of Language Models from Pretraining to Post-training.

Melody Zixuan Li, Kumar Krishna Agrawal, Arna Ghosh, Komal Kumar Teru, Adam Santoro, Guillaume Lajoie, Blake A. Richards

CoRR, September, 2025

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, March, 2025

2024

Harnessing small projectors and multiple views for efficient vision pretraining.

Arna Ghosh, Kumar Krishna Agrawal, Shagun Sodhani, Adam Oberman, Blake A. Richards

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Attribute Diversity Determines the Systematicity Gap in VQA.

Ian Berlot-Attwell, Kumar Krishna Agrawal, Annabelle Michael Carrell, Yash Sharma, Naomi Saphra

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

2023

Addressing Sample Inefficiency in Multi-View Representation Learning.

Kumar Krishna Agrawal, Arna Ghosh, Adam Oberman, Blake A. Richards

CoRR, 2023

2022

Investigating Power laws in Deep Representation Learning.

Arna Ghosh, Arnab Kumar Mondal, Kumar Krishna Agrawal, Blake A. Richards

CoRR, 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

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 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, Bharathan Balaji, Joseph Gonzalez, Ion Stoica

Proceedings of the Computer Vision - ECCV 2022, 2022

Learning from an Exploring Demonstrator: Optimal Reward Estimation for Bandits.

Wenshuo Guo, Kumar Krishna Agrawal, Aditya Grover, Vidya K. Muthukumar, Ashwin Pananjady

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2020

Model AI Assignments 2020.

Todd W. Neller, Stephen Keeley, Michael Guerzhoy, Wolfgang Hönig, Jiaoyang Li, Sven Koenig, Ameet Soni, Krista Thomason, Lisa Zhang, Bibin Sebastian, Cinjon Resnick, Avital Oliver, Surya Bhupatiraju, Kumar Krishna Agrawal, James Allingham, Sejong Yoon, Jonathan Chen, Tom Larsen, Marion Neumann, Narges Norouzi, Ryan Hausen, Matthew Evett

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Discrete Flows: Invertible Generative Models of Discrete Data.

Dustin Tran, Keyon Vafa, Kumar Krishna Agrawal, Laurent Dinh, Ben Poole

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 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

Proceedings of the 7th International Conference on Learning Representations, 2019

GANSynth: Adversarial Neural Audio Synthesis.

Jesse H. Engel, Kumar Krishna Agrawal, Shuo Chen, Ishaan Gulrajani, Chris Donahue, Adam Roberts

Proceedings of the 7th International Conference on Learning Representations, 2019

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, Nate Derbinsky, Elena Strange, Marion Neumann, Jonathan Chen, Zac Christensen, Michael Wollowski, Oscar Youngquist

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Addressing Sample Inefficiency and Reward Bias in Inverse Reinforcement Learning.

Ilya Kostrikov, Kumar Krishna Agrawal, Sergey Levine, Jonathan Tompson

CoRR, 2018

Towards Mixed Optimization for Reinforcement Learning with Program Synthesis.

Surya Bhupatiraju, Kumar Krishna Agrawal, Rishabh Singh

CoRR, 2018

2017

Playing with Embeddings : Evaluating embeddings for Robot Language Learning through MUD Games.

Anmol Gulati, Kumar Krishna Agrawal

Proceedings of the 2nd Workshop on Evaluating Vector Space Representations for NLP, 2017

Recurrent Memory Addressing for Describing Videos.

Arnav Kumar Jain, Abhinav Agarwalla, Kumar Krishna Agrawal, Pabitra Mitra

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2017