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Arpandeep Khatua

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#artificial intelligence Review Sep 2026

Harbor Adapters and Harbor-Index: Infrastructure and a Curated Meta-Dataset for Large-Scale Agentic Evaluation

Harbor Adapters are developed that port more than 80 benchmarks to evaluate arbitrary agents, and validated through rigorous code review and parity experiments, and Harbor-Index is introduced, a curated set of 82 difficult, diverse, and high-quality tasks spanning 29 benchmarks to support more reliable and comprehensiv...

Lin Shi, Hao-Wei Lin, Zi-Xuan Zhu et al. · 1 citation
Preprint Aug 2026

What to Forget in Unlearning? Forget Set Curation for Language Models

This work introduces CleanSlate, a benchmark for verbatim output suppression over songs and books, with model-specific extraction profiles, content-grounded QA, and capability-retention evaluations, and shows that practical unlearning is not only an optimization problem once a forget set is given, but also what can be...

Animesh Jha, Arpandeep Khatua, Youssef Allouah et al. · 0 citations

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