Search Results for author: Mukul Gagrani

Found 7 papers, 0 papers with code

On Speculative Decoding for Multimodal Large Language Models

no code implementations13 Apr 2024 Mukul Gagrani, Raghavv Goel, Wonseok Jeon, Junyoung Park, Mingu Lee, Christopher Lott

We show that a language-only model can serve as a good draft model for speculative decoding with LLaVA 7B, bypassing the need for image tokens and their associated processing components from the draft model.

Image Captioning Language Modelling +1

Recursive Speculative Decoding: Accelerating LLM Inference via Sampling Without Replacement

no code implementations21 Feb 2024 Wonseok Jeon, Mukul Gagrani, Raghavv Goel, Junyoung Park, Mingu Lee, Christopher Lott

We empirically evaluate RSD with Llama 2 and OPT models, showing that RSD outperforms the baseline methods, consistently for fixed draft sequence length and in most cases for fixed computational budgets at LLM.

Language Modelling

Neural Topological Ordering for Computation Graphs

no code implementations13 Jul 2022 Mukul Gagrani, Corrado Rainone, Yang Yang, Harris Teague, Wonseok Jeon, Herke van Hoof, Weiliang Will Zeng, Piero Zappi, Christopher Lott, Roberto Bondesan

Recent works on machine learning for combinatorial optimization have shown that learning based approaches can outperform heuristic methods in terms of speed and performance.

2k BIG-bench Machine Learning +1

Thompson sampling for linear quadratic mean-field teams

no code implementations9 Nov 2020 Mukul Gagrani, Sagar Sudhakara, Aditya Mahajan, Ashutosh Nayyar, Yi Ouyang

We consider optimal control of an unknown multi-agent linear quadratic (LQ) system where the dynamics and the cost are coupled across the agents through the mean-field (i. e., empirical mean) of the states and controls.

Thompson Sampling

Cannot find the paper you are looking for? You can Submit a new open access paper.