Author

Sagnik Basu

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#artificial intelligence Preprint Oct 2026

SEDATE: Do Large Language Models Share an Aggression Circuit Across Languages?

This work proposes Selective Detection And Targeted Editing (SEDATE), a training-free approach based on detect-edit-verify strategy that achieves substantially superior safety scores across all languages and models over the best-performing baseline while retaining the general capabilities and incurring negligible overh...

Sagnik Basu, Sayan Das, Somnath Banerjee et al. · 0 citations

#natural language process... Preprint Mar 2026

SafeMath: Safe Solutions for Unsafe Math Word Problems

Recent research points toward LLMs being manipulated through adversarial and seemingly benign inputs, resulting in harmful, biased, or policy-violating outputs. In this paper, we study an underexplored issue concerning harmful and toxic mathematical word problems. We show that math questions, particularly those framed...

Sagnik Basu, Subhrajit Mitra, Aman Juneja et al. · 0 citations