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researcher

S. Bashir

12 papers hereh-index 6220 citations23 works total

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

author position
  • first author4
  • middle author5
  • last author2

Across the 11 of 12 papers where every author was matched, so the position is known.

fields
  • cs.CL4
  • cs.IR3
  • cs.LG3
  • cs.CR1
  • cs.CY1
same name
  • S. Bashir — 88 papers, h 4
  • S. Bashir — 57 papers, h 17
  • S. Bashir — 6 papers, h 14
  • S. Bashir — 5 papers, h 3
  • S. Bashir — 3 papers, h 2
  • S. Bashir — 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
20212025
most citedNBIAS: A Natural Language Processing Framework for Bias Identification in Text

5 citations · 8 across the 10 of their papers we have counts for

collaborators
Showing cs.CLShow all

4 papers · 1 filter

cs.CL2025

VLDBench Evaluating Multimodal Disinformation with Regulatory Alignment

Shaina Raza, Ashmal Vayani, Aditya Jain +8

Detecting disinformation that blends manipulated text and images has become increasingly challenging, as AI tools make synthetic content easy to generate and disseminate. While mos…

cs.CL2023★ 5 cited

NBIAS: A Natural Language Processing Framework for Bias Identification in Text

Shaina Raza, Muskan Garg, Deepak John Reji +2

Bias in textual data can lead to skewed interpretations and outcomes when the data is used. These biases could perpetuate stereotypes, discrimination, or other forms of unfair trea…

cs.CL2023

Leveraging Foundation Models for Clinical Text Analysis

Shaina Raza, Syed Raza Bashir

Infectious diseases are a significant public health concern globally, and extracting relevant information from scientific literature can facilitate the development of effective pre…

cs.CL2023

Addressing Biases in the Texts using an End-to-End Pipeline Approach

Shaina Raza, Syed Raza Bashir, Sneha +1

The concept of fairness is gaining popularity in academia and industry. Social media is especially vulnerable to media biases and toxic language and comments. We propose a fair ML…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.