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Rethinking Dataset Distillation: Hard Truths about Soft Labels
Priyam Dey, Aditya Sahdev, Sunny Bhati +2
Despite the perceived success of large-scale dataset distillation (DD) methods, recent evidence finds that simple random image baselines perform on-par with state-of-theart DD meth…
A Granular Study of Safety Pretraining under Model Abliteration
Shashank Agnihotri, Jonas Jakubassa, Priyam Dey +4
Open-weight LLMs can be modified at inference time with simple activation edits, which raises a practical question for safety: do common safety interventions like refusal training…
ProFeAT: Projected Feature Adversarial Training for Self-Supervised Learning of Robust Representations
Sravanti Addepalli, Priyam Dey, R. Venkatesh Babu
The need for abundant labelled data in supervised Adversarial Training (AT) has prompted the use of Self-Supervised Learning (SSL) techniques with AT. However, the direct applicati…