Anshuman Chhabra
13 papers · 2020–2025 · 8 conferences · across top CS/AI conferences
Achievements
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π Interdisciplinary Bridge π Renaissance Researcher (7) π Academic Marathon (5) π Conference Polyglot (8) πΊοΈ Taxonomy Completionist (24)
π§
Keyword Pioneer
π
Conference Polyglot
(8)
π
Grand Slam
π
Keyword Champion
(2)
β‘
Prolific Year
(7)
π
Century Club
(12)
β
The Questioner
(2)
Conferences
NAACL (3)
AACL (2)
ICLR (2)
IJCNLP (2)
AAAI (1)
ACL (1)
ICML (1)
NIPS (1)
Top co-authors
Keywords
large language model
(8)
emotion attribution
(2)
adversarial attack
(2)
political ideology
(2)
content moderation
(2)
text classification
(2)
cultural norm
(2)
cross-cultural framework
(2)
few-shot learning
(2)
robustness analysis
(2)
abstractive summarization
(2)
in-context learning
(2)
zero-shot learning
(2)
demographic parity
(1)
social bia
(1)
cross-cultural analysis
(1)
demonstration selection
(1)
nationality persona
(1)
emotional stereotype
(1)
zero-shot summarization
(1)
Papers
βWhose Side Are You On?β Estimating Ideology of Political and News Content Using Large Language Models and Few-shot Demonstration Selection
AACL 2025
Outlier Gradient Analysis: Efficiently Identifying Detrimental Training Samples for Deep Learning Models
ICML 2025
From Anger to Joy: How Nationality Personas Shape Emotion Attribution in Large Language Models
IJCNLP 2025
βWhose Side Are You On?β Estimating Ideology of Political and News Content Using Large Language Models and Few-shot Demonstration Selection
IJCNLP 2025
Watching the AI Watchdogs: A Fairness and Robustness Analysis of AI Safety Moderation Classifiers
NAACL 2025
Assessing LLMs for Zero-shot Abstractive Summarization Through the Lens of Relevance Paraphrasing
NAACL 2025
From Anger to Joy: How Nationality Personas Shape Emotion Attribution in Large Language Models
AACL 2025
Re-ranking Using Large Language Models for Mitigating Exposure to Harmful Content on Social Media Platforms
ACL 2025
Revisiting Zero-Shot Abstractive Summarization in the Era of Large Language Models from the Perspective of Position Bias
NAACL 2024
"What Data Benefits My Classifier?" Enhancing Model Performance and Interpretability through Influence-Based Data Selection
ICLR 2024
Robust Fair Clustering: A Novel Fairness Attack and Defense Framework
ICLR 2023
On the Robustness of Deep Clustering Models: Adversarial Attacks and Defenses
NIPS 2022
Suspicion-Free Adversarial Attacks on Clustering Algorithms
AAAI 2020