◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

Sajib Biswas

4 papers hereh-index 220 citations5 works total

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

author position
  • first author3
  • middle author1

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.LG4

identity via Semantic Scholar / OpenAlex

collaborators

4 papers

cs.LG2025

Efficient Extractive Text Summarization for Online News Articles Using Machine Learning

Sajib Biswas, Milon Biswas, Arunima Mandal +2

In the age of information overload, content management for online news articles relies on efficient summarization to enhance accessibility and user engagement. This article address…

cs.LG2025

Universal and Transferable Adversarial Attack on Large Language Models Using Exponentiated Gradient Descent

Sajib Biswas, Mao Nishino, Samuel Jacob Chacko +1

As large language models (LLMs) are increasingly deployed in critical applications, ensuring their robustness and safety alignment remains a major challenge. Despite the overall su…

cs.LG2025

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent

Sajib Biswas, Mao Nishino, Samuel Jacob Chacko +1

As Large Language Models (LLMs) are widely used, understanding them systematically is key to improving their safety and realizing their full potential. Although many models are ali…

cs.LG2024

Adversarial Attacks on Large Language Models Using Regularized Relaxation

Samuel Jacob Chacko, Sajib Biswas, Chashi Mahiul Islam +2

As powerful Large Language Models (LLMs) are now widely used for numerous practical applications, their safety is of critical importance. While alignment techniques have significan…

◍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.