NeuFS selects active few-shot samples for LLMs by representing samples via neuron activation patterns and applying a dual-criteria strategy of diversity and neuron consensus to identify informative examples.
Cold-start active learning through self- supervised language modeling.arXiv preprint arXiv:2010.09535
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BRAL-T uses TrustSet-guided reinforcement learning for batch active learning and reports state-of-the-art results on 10 image classification benchmarks plus 2 fine-tuning tasks.
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Neuron-Aware Active Few-Shot Learning for LLMs
NeuFS selects active few-shot samples for LLMs by representing samples via neuron activation patterns and applying a dual-criteria strategy of diversity and neuron consensus to identify informative examples.
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Labeled TrustSet Guided: Batch Active Learning with Reinforcement Learning
BRAL-T uses TrustSet-guided reinforcement learning for batch active learning and reports state-of-the-art results on 10 image classification benchmarks plus 2 fine-tuning tasks.