activity
20232026
most citedTricking LLMs into Disobedience: Formalizing, Analyzing, and Detecting Jailbreaks

16 citations · 16 across the 9 of their papers we have counts for

collaborators

9 papers

cs.AI2026

The Failure Happens Before the Drift: The Social Dynamics of Values in LLM Agent Societies

Farah Atif, Sougata Saha, Monojit Choudhury

Large Language Model (LLM)-based agents are increasingly used as proxies for human participants in social science research, yet it remains unclear whether they can faithfully simul…

cs.AI2026

The Shape of Power: A Multilingual Framework for Social Power Reasoning in Dialogues

Farah Atif, Sougata Saha, Monojit Choudhury

Social power plays a fundamental role in shaping human interaction, yet computational studies of power remain limited to narrow linguistic and cultural settings. Existing datasets…

cs.CL2026

To Generate or Discriminate? Methodological Considerations for Measuring Cultural Alignment in LLMs

Saurabh Kumar Pandey, Sougata Saha, Monojit Choudhury

Socio-demographic prompting (SDP) - prompting Large Language Models (LLMs) using demographic proxies to generate culturally aligned outputs - often shows LLM responses as stereotyp…

cs.CL2025

User Behavior Prediction as a Generic, Robust, Scalable, and Low-Cost Evaluation Strategy for Estimating Generalization in LLMs

Sougata Saha, Monojit Choudhury

Measuring the generalization ability of Large Language Models (LLMs) is challenging due to data contamination. As models grow and computation becomes cheaper, ensuring tasks and te…

cs.CL2025

SMAB: MAB based word Sensitivity Estimation Framework and its Applications in Adversarial Text Generation

Saurabh Kumar Pandey, Sachin Vashistha, Debrup Das +2

To understand the complexity of sequence classification tasks, Hahn et al. (2021) proposed sensitivity as the number of disjoint subsets of the input sequence that can each be indi…

cs.CY2025

Meta-Cultural Competence: Climbing the Right Hill of Cultural Awareness

Sougata Saha, Saurabh Kumar Pandey, Monojit Choudhury

Numerous recent studies have shown that Large Language Models (LLMs) are biased towards a Western and Anglo-centric worldview, which compromises their usefulness in non-Western cul…

cs.CL2025

Women, Infamous, and Exotic Beings: A Comparative Study of Honorific Usages in Wikipedia and LLMs for Bengali and Hindi

Sourabrata Mukherjee, Atharva Mehta, Sougata Saha +2

The obligatory use of third-person honorifics is a distinctive feature of several South Asian languages, encoding nuanced socio-pragmatic cues such as power, age, gender, fame, and…

cs.CL2024

[WIP] Jailbreak Paradox: The Achilles' Heel of LLMs

Abhinav Rao, Monojit Choudhury, Somak Aditya

We introduce two paradoxes concerning jailbreak of foundation models: First, it is impossible to construct a perfect jailbreak classifier, and second, a weaker model cannot consist…

cs.CL2023★ 16 cited

Tricking LLMs into Disobedience: Formalizing, Analyzing, and Detecting Jailbreaks

Abhinav Rao, Sachin Vashistha, Atharva Naik +2

Recent explorations with commercial Large Language Models (LLMs) have shown that non-expert users can jailbreak LLMs by simply manipulating their prompts; resulting in degenerate o…