Author

Anvesh Rao Vijjini

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#natural language process... Jun 2026

SHARD: Safe and Helpful Alignment via Self-Reframing Distillation

SHARD is introduced, a self-reframing distillation method to improve safe-helpfulness in large language models that first rewrites sensitive prompts to surface benign intent using philosophical guidelines, then reframes its original responses into safe, more helpful ones, and finally fine-tunes the model on its self-re...

Viswonathan Manoranjan, Amogh Gupta, Anvesh Rao Vijjini et al. · arXiv.org · 0 citations

#natural language process... Conference Open access May 2026

Do LLM Agents Mirror Socio-Cognitive Effects in Power-Asymmetric Conversations?

This work examines whether large language models exhibit similar behaviors when assigned high or low status personas, and shows that LLMs show key socio-cognitive effects of power, albeit with nuances and variability, linking simulated interactions to both desirable and unsafe behaviors.

Anvesh Rao Vijjini, S. Manjunath, Snigdha Chaturvedi · Annual Meeting of the Associ... · 0 citations