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  • Anonymous GitHub
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    KA2L: A Knowledge-Aware Active Learning Framework for LLMs 1 Project Structure 1 Knowledge Distribution Probe main py: Samples hidden states, text outputs, and outputs of various baselines during the training process train py: Trains the MLP classifier based on the sampled data and calculates results for other baselines during the training process inference py: Inference process, uses the
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    Overview The pipeline is intentionally limited to the paper's main method: Load MIRAGE benchmark json Generate an initial hypothesis with hypothesis_formulator Rewrite the hypothesis into three retrieval queries with query_rewriter Retrieve evidence from MIRAGE MedRAG Generate the final answer with generator Judge retrieved context utility with the OpenAI 3-category evaluator Entry Points run
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    🛠️ Environment OS: Ubuntu 20 04 CUDA: 12 2 NVIDIA Driver: 535 161 07 Conda Environments: ReSemAct (Client) m3p2i-aip (Server)





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