4 citations · 5 across the 5 of their papers we have counts for
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OpenUnlearning: Accelerating LLM Unlearning via Unified Benchmarking of Methods and Metrics
Vineeth Dorna, Anmol Mekala, Wenlong Zhao +4
Robust unlearning is crucial for safely deploying large language models (LLMs) in environments where data privacy, model safety, and regulatory compliance must be ensured. Yet the…
Does quantization affect models' performance on long-context tasks?
Anmol Mekala, Anirudh Atmakuru, Yixiao Song +2
Large language models (LLMs) now support context windows exceeding 128K tokens, but this comes with significant memory requirements and high inference latency. Quantization can mit…
Alternate Preference Optimization for Unlearning Factual Knowledge in Large Language Models
Anmol Mekala, Vineeth Dorna, Shreya Dubey +5
Machine unlearning aims to efficiently eliminate the influence of specific training data, known as the forget set, from the model. However, existing unlearning methods for Large La…