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2,343 notes from my AI research vault, mapped by topic. Pick a topic to see its notes, or search.

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Notes on active learning

5 notes

  1. Neuron-Aware Active Few-Shot Learning for LLMs

    Source note · Jul 2, 2026 · language model, active learning

    The paper introduces a new method called NeuFS for Active Few-Shot Learning (AFSL) in Language Models (LLMs). Instead of relying on output-level signals to identify valuable unlabeled samples, it focuses on the…

  2. Neuron-Aware Active Few-Shot Learning for LLMs

    Source note · Jul 2, 2026 · artificial intelligence, active learning

    The research presents NeuFS, a new approach for Active Few-Shot Learning (AFSL) that focuses on using a model's internal dynamics to identify valuable unlabeled samples for annotation. This method is designed to reduce…

  3. Detecting the Undetectable: Enhancing Unsupervised time series Anomaly Detection via Active Learning

    Source note · Jul 1, 2026 · anomaly detection, active learning

    The authors propose a novel framework using active learning to enhance unsupervised time series anomaly detection in complex data. The framework aims to improve the ability of models to detect subtle and noisy…

  4. Hierarchical Reinforcement Learning for Neural Network Compression (HiReLC): Pruning and Quantization

    Source note · Jun 24, 2026 · reinforcement learning, quantization, active learning

    The paper presents HiReLC, a framework that uses reinforcement learning to compress deep neural networks by pruning and quantizing them. The framework divides the compression search into two levels: low-level agents…

  5. Hierarchical Reinforcement Learning for Neural Network Compression (HiReLC): Pruning and Quantization

    Source note · Jun 24, 2026 · reinforcement learning, quantization, active learning

    The paper introduces HiReLC, a hierarchical reinforcement learning framework that automates the joint quantization and structured pruning of deep neural networks. It operates at two levels: low-level agents (LLAs)…

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