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Prayag Tiwari

14 papers hereh-index 27 citations15 works total

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

author position
  • middle author12

Across the 12 of 14 papers where every author was matched, so the position is known.

fields
  • cs.CL5
  • cs.CV4
  • cs.AI2
  • cs.LG2
  • cs.SD1
same name
  • Prayag Tiwari — 9 papers, h 4
  • Prayag Tiwari — 8 papers, h 6
  • Prayag Tiwari — 8 papers, h 3
  • Prayag Tiwari — 7 papers, h 4
  • Prayag Tiwari — 3 papers, h 5
  • Prayag Tiwari — 2 papers, h 30

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

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2026

Mags-RL: Wearing Multimodal LLMs a Magnifying Glass via Agentic Reinforcement Learning For Complex Scene Reasoning

Xuanzhao Dong, Wenhui Zhu, Peijie Qiu +11

Despite their popularity and success, Multimodal Large Language Models (MLLMs) often struggle to interpret images accurately, which limits their reasoning capability in complex sce…

cs.CV2026

Closed-Loop Bidirectional Prompting for Adversarial Robustness of Vision Language Models

Xiao Liu, Jiaxiang Liu, Boci Peng +6

Vision Language Models adapt well to downstream tasks but are highly vulnerable to adversarial perturbations that disrupt cross-modal semantic alignment. Existing defenses are larg…

cs.CV2026

Attribution Upsampling should Redistribute, Not Interpolate

Vincenzo Buono, Peyman Sheikholharam Mashhadi, Mahmoud Rahat +2

Attribution methods in explainable AI rely on upsampling techniques that were designed for natural images, not saliency maps. Standard bilinear and bicubic interpolation systematic…

cs.CV2025

FinCriticalED: A Visual Benchmark for Financial Fact-Level OCR

Yueru He, Xueqing Peng, Yupeng Cao +13

Recent progress in multimodal large language models (MLLMs) has substantially improved document understanding, yet strong optical character recognition (OCR) performance on surface…

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