Rishabh Tiwari

According to our database, Rishabh Tiwari authored at least 25 papers between 2020 and 2026.

Collaborative distances:

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

2026

LoSA: Locality Aware Sparse Attention for Block-Wise Diffusion Language Models.

Haocheng Xi, Harman Singh, Yuezhou Hu, Coleman Hooper, Rishabh Tiwari, Aditya Tomar, Minjae Lee, Wonjun Kang, Michael W. Mahoney, Chenfeng Xu, Kurt Keutzer, Amir Gholami

CoRR, April, 2026

Squeeze Evolve: Unified Multi-Model Orchestration for Verifier-Free Evolution.

Monishwaran Maheswaran, Leon Lakhani, Zhongzhu Zhou, Shijia Yang, Junxiong Wang, Coleman Hooper, Yuezhou Hu, Rishabh Tiwari, Jue Wang, Harman Singh, Qingyang Wu, Yuqing Jian, Ce Zhang, Kurt Keutzer, Tri Dao, Xiaoxia Wu, Ben Athiwaratkun, James Zou, Chenfeng Xu

CoRR, April, 2026

Reward Under Attack: Analyzing the Robustness and Hackability of Process Reward Models.

Rishabh Tiwari, Aditya Tomar, Udbhav Bamba, Monishwaran Maheswaran, Heng Yang, Michael W. Mahoney, Kurt Keutzer, Amir Gholami

CoRR, March, 2026

V₁: Unifying Generation and Self-Verification for Parallel Reasoners.

Harman Singh, Xiuyu Li, Kusha Sareen, Monishwaran Maheswaran, Sijun Tan, Xiaoxia Wu, Junxiong Wang, Alpay Ariyak, Qingyang Wu, Samir Khaki, Rishabh Tiwari, Long Lian, Yucheng Lu, Boyi Li, Alane Suhr, Ben Athiwaratkun, Kurt Keutzer

CoRR, March, 2026

Interleaved Head Attention.

Sai Surya Duvvuri, Chanakya Ekbote, Rachit Bansal, Rishabh Tiwari, Devvrit Khatri, David Brandfonbrener, Paul Pu Liang, Inderjit S. Dhillon, Manzil Zaheer

CoRR, February, 2026

2025

Let's (not) just put things in Context: Test-Time Training for Long-Context LLMs.

Rachit Bansal, Aston Zhang, Rishabh Tiwari, Lovish Madaan, Sai Surya Duvvuri, Devvrit Khatri, David Brandfonbrener, David Alvarez-Melis, Prajjwal Bhargava, Mihir Sanjay Kale, Samy Jelassi

CoRR, December, 2025

Arbitrage: Efficient Reasoning via Advantage-Aware Speculation.

Monishwaran Maheswaran, Rishabh Tiwari, Yuezhou Hu, Kerem Dilmen, Coleman Hooper, Haocheng Xi, Nicholas Lee, Mehrdad Farajtabar, Michael W. Mahoney, Kurt Keutzer, Amir Gholami

CoRR, December, 2025

The Art of Scaling Reinforcement Learning Compute for LLMs.

Devvrit Khatri, Lovish Madaan, Rishabh Tiwari, Rachit Bansal, Sai Surya Duvvuri, Manzil Zaheer, Inderjit S. Dhillon, David Brandfonbrener, Rishabh Agarwal

CoRR, October, 2025

SciML Agents: Write the Solver, Not the Solution.

Saarth Gaonkar, Xiang Zheng, Haocheng Xi, Rishabh Tiwari, Kurt Keutzer, Dmitriy Morozov, Michael W. Mahoney, Amir Gholami

CoRR, September, 2025

XQuant: Breaking the Memory Wall for LLM Inference with KV Cache Rematerialization.

Aditya Tomar, Coleman Hooper, Minjae Lee, Haocheng Xi, Rishabh Tiwari, Wonjun Kang, Luca Manolache, Michael W. Mahoney, Kurt Keutzer, Amir Gholami

CoRR, August, 2025

SPECS: Faster Test-Time Scaling through Speculative Drafts.

Mert Cemri, Nived Rajaraman, Rishabh Tiwari, Xiaoxuan Liu, Kurt Keutzer, Ion Stoica, Kannan Ramchandran, Ahmad Beirami, Ziteng Sun

CoRR, June, 2025

Why Do Multi-Agent LLM Systems Fail?

Mert Cemri, Melissa Z. Pan, Shuyi Yang, Lakshya A. Agrawal, Bhavya Chopra, Rishabh Tiwari, Kurt Keutzer, Aditya G. Parameswaran, Dan Klein, Kannan Ramchandran, Matei Zaharia, Joseph E. Gonzalez, Ion Stoica

CoRR, March, 2025

QuantSpec: Self-Speculative Decoding with Hierarchical Quantized KV Cache.

Rishabh Tiwari, Haocheng Xi, Aditya Tomar, Coleman Richard Charles Hooper, Sehoon Kim, Maxwell Horton, Mahyar Najibi, Michael W. Mahoney, Kurt Keutzer, Amir Gholami

Proceedings of the Forty-second International Conference on Machine Learning, 2025

2024

Using Early Readouts to Mediate Featural Bias in Distillation.

Rishabh Tiwari, Durga Sivasubramanian, Anmol Reddy Mekala, Ganesh Ramakrishnan, Pradeep Shenoy

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

2023

A novel YOLOv4-modified approach for efficient object detection in satellite imagery.

Rishabh Tiwari, Ashwani Kumar Dubey, Álvaro Rocha

Expert Syst. J. Knowl. Eng., June, 2023

Sifer: Overcoming simplicity bias in deep networks using a feature sieve.

Rishabh Tiwari, Pradeep Shenoy

CoRR, 2023

Overcoming Simplicity Bias in Deep Networks using a Feature Sieve.

Rishabh Tiwari, Pradeep Shenoy

Proceedings of the International Conference on Machine Learning, 2023

RCV2023 Challenges: Benchmarking Model Training and Inference for Resource-Constrained Deep Learning.

Rishabh Tiwari, Arnav Chavan, Deepak K. Gupta, Gowreesh Mago, Animesh Gupta, Akash Gupta, Suraj Sharan, Yukun Yang, Shanwei Zhao, Shihao Wang, Youngjun Kwak, Seonghun Jeong, Yunseung Lee, Changick Kim, Subin Kim, Ganzorig Gankhuyag, Ho Jung, Junwhan Ryu, HaeMoon Kim, Byeong Hak Kim, Tu Vo, Sheir Zaheer, Alexander Holston, Chan Y. Park, Dheemant Dixit, Nahush Lele, Kushagra Bhushan, Debjani Bhowmick, Devanshu Arya, Sadaf Gulshad, Amirhossein Habibian, Amir Ghodrati, Babak Ehteshami Bejnordi, Jai Gupta, Zhuang Liu, Jiahui Yu, Dilip K. Prasad, Zhiqiang Shen

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

On Designing Light-Weight Object Trackers Through Network Pruning: Use CNNS or Transformers?

Saksham Aggarwal, Taneesh Gupta, Pawan Kumar Sahu, Arnav Chavan, Rishabh Tiwari, Dilip K. Prasad, Deepak K. Gupta

Proceedings of the IEEE International Conference on Acoustics, 2023

Interactive Concept Bottleneck Models.

Kushal Chauhan, Rishabh Tiwari, Jan Freyberg, Pradeep Shenoy, Krishnamurthy Dvijotham

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

GCR: Gradient Coreset based Replay Buffer Selection for Continual Learning.

Rishabh Tiwari, KrishnaTeja Killamsetty, Rishabh K. Iyer, Pradeep Shenoy

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Dynamic Kernel Selection for Improved Generalization and Memory Efficiency in Meta-learning.

Arnav Chavan, Rishabh Tiwari, Udbhav Bamba, Deepak K. Gupta

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

ChipNet: Budget-Aware Pruning with Heaviside Continuous Approximations.

Rishabh Tiwari, Udbhav Bamba, Arnav Chavan, Deepak K. Gupta

Proceedings of the 9th International Conference on Learning Representations, 2021

Rescaling CNN Through Learnable Repetition of Network Parameters.

Arnav Chavan, Udbhav Bamba, Rishabh Tiwari, Deepak K. Gupta

Proceedings of the 2021 IEEE International Conference on Image Processing, 2021

2020

Multi-plateau Ensemble For Endoscopic Artefact Segmentation And Detection.

Suyog Jadhav, Udbhav Bamba, Arnav Chavan, Rishabh Tiwari, Aryan Raj

Proceedings of the 2nd International Workshop and Challenge on Computer Vision in Endoscopy, 2020