◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

Prashant Singh

9 papers hereh-index 315 citations13 works total

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

author position
  • middle author2
  • last author6

Across the 8 of 9 papers where every author was matched, so the position is known.

fields
  • cs.LG6
  • cs.CV1
  • cs.IR1
  • stat.ML1
same name
  • Prashant Singh — 15 papers, h 12
  • Prashant Singh — 7 papers, h 4
  • Prashant Singh — 5 papers, h 12
  • Prashant Singh — 5 papers, h 3
  • Prashant Singh — 4 papers, h 7
  • Prashant Singh — 3 papers, h 1

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

activity
20242026
most citedEnterpriseEM: Fine-tuned Embeddings for Enterprise Semantic Search

2 citations · 2 across the 8 of their papers we have counts for

collaborators
Showing 2026Show all

4 papers · 1 filter

cs.LG2026

Squeeze-Release: Iterative Pruning with Exact Structural Minimization

Roman Denkin, Ida Akerholm, Prashant Singh +1

Unstructured pruning produces sparse weight tensors, but the standard implementation keeps tensor shapes unchanged so the deployed model is no smaller than before pruning. We prese…

cs.LG2026

GeoFlowVLM: Geometry-Aware Joint Uncertainty for Frozen Vision-Language Embedding

Mayank Nautiyal, Li Ju, Andreas Hellander +2

Standard dual-encoder vision-language models that map images and text to deterministic points on a shared unit hypersphere through ℓ2​ normalization typically expose neither \…

stat.ML2026

OneFlowSBI: One Model, Many Queries for Simulation-Based Inference

Mayank Nautiyal, Li Ju, Melker Ernfors +5

Simulation-based inference (SBI) methods typically amortize a single query, usually the posterior, so each further conditional or marginal needs its own model. Existing generalists…

cs.LG2026

Epistemic Uncertainty Quantification for Pre-trained VLMs via Riemannian Flow Matching

Li Ju, Mayank Nautiyal, Andreas Hellander +2

Vision-Language Models (VLMs) are typically deterministic in nature and lack intrinsic mechanisms to quantify epistemic uncertainty, which reflects the model's lack of knowledge or…

◍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.