Papers by Amitava Datta

2 papers
Can LLM Agents Maintain a Persona in Discourse? (2025.emnlp-main)

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Challenge: Large language models are often subjected to context-shifting behaviour, resulting in a lack of consistent and interpretable personality-aligned interactions.
Approach: They propose to use two conversation agents to generate a discourse with an assigned personality from the OCEAN framework and then use multiple judge agents to infer original traits.
Outcome: The proposed model is based on two conversation agents with a personality assigned from the OCEAN framework and then multiple judge agents to infer the original traits assigned.
Activation-Space Personality Steering: Hybrid Layer Selection for Stable Trait Control in LLMs (2026.eacl-long)

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Challenge: Personality-aware LLMs exhibit implicit personalities in their generation, but reliably controlling or aligning these traits to meet specific needs remains an open challenge.
Approach: They propose a pipeline that extracts hidden state activations from transformer layers using the Big Five Personality Traits framework.
Outcome: The proposed model extracts hidden state activations from transformer layers using the Big Five personality traits (Openness, Conscientiousness, Extraversion, Agreeableness and Neuroticism)

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