9 citations · 10 across the 4 of their papers we have counts for
7 papers · 1 filter
Do LLMs Use Cultural Knowledge Without Being Told? A Multilingual Evaluation of Implicit Pragmatic Adaptation
Mehwish Nasim, Sanjeevan Selvaganapathy, Neel Ganapathi Sabhahit +6
Many benchmarks show that large language models can answer direct questions about culture. We study a different question: do they also change how they speak when culture is only im…
Bias Beyond Borders: Political Ideology Evaluation and Steering in Multilingual LLMs
Afrozah Nadeem, Agrima Seth, Mehwish Nasim +1
Large Language Models (LLMs) increasingly shape global discourse, making fairness and ideological neutrality essential for responsible AI deployment. Despite growing attention to p…
They Said Memes Were Harmless-We Found the Ones That Hurt: Decoding Jokes, Symbols, and Cultural References
Sahil Tripathi, Gautam Siddharth Kashyap, Mehwish Nasim +3
Meme-based social abuse detection is challenging because harmful intent often relies on implicit cultural symbolism and subtle cross-modal incongruence. Prior approaches, from fusi…
Do Personality Traits Interfere? Geometric Limitations of Steering in Large Language Models
Pranav Bhandari, Usman Naseem, Mehwish Nasim
Personality steering in large language models (LLMs) commonly relies on injecting trait-specific steering vectors, implicitly assuming that personality traits can be controlled ind…
Activation-Space Personality Steering: Hybrid Layer Selection for Stable Trait Control in LLMs
Pranav Bhandari, Nicolas Fay, Sanjeevan Selvaganapathy +3
Large Language Models exhibit implicit personalities in their generation, but reliably controlling or aligning these traits to meet specific needs remains an open challenge. The ne…
Can LLM Agents Maintain a Persona in Discourse?
Pranav Bhandari, Nicolas Fay, Michael Wise +4
Large Language Models (LLMs) are widely used as conversational agents, exploiting their capabilities in various sectors such as education, law, medicine, and more. However, LLMs ar…