◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

Shivani Agrawal

3 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author2
  • last author1

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.LG2
  • eess.AS1
same name
  • Shivani Agrawal — 2 papers, h 9

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedProgressive Gradient Flow for Robust N:M Sparsity Training in Transformers

2 citations · 3 across the 3 of their papers we have counts for

collaborators

3 papers

cs.LG2024★ 2 cited

Progressive Gradient Flow for Robust N:M Sparsity Training in Transformers

Abhimanyu Rajeshkumar Bambhaniya, Amir Yazdanbakhsh, Suvinay Subramanian +4

N:M Structured sparsity has garnered significant interest as a result of relatively modest overhead and improved efficiency. Additionally, this form of sparsity holds considerable…

eess.AS2024

USM-Lite: Quantization and Sparsity Aware Fine-tuning for Speech Recognition with Universal Speech Models

Shaojin Ding, David Qiu, David Rim +10

End-to-end automatic speech recognition (ASR) models have seen revolutionary quality gains with the recent development of large-scale universal speech models (USM). However, deploy…

cs.LG2023★ 1 cited

STEP: Learning N:M Structured Sparsity Masks from Scratch with Precondition

Yucheng Lu, Shivani Agrawal, Suvinay Subramanian +3

Recent innovations on hardware (e.g. Nvidia A100) have motivated learning N:M structured sparsity masks from scratch for fast model inference. However, state-of-the-art learning re…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.