AINeutralarXiv – CS AI · 18h ago6/10
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ABLE: Representing and Mapping LLMs via Attribution-Based Large-model Embedding
Researchers introduce ABLE, a framework that represents and compares large language models through gradient-based feature attributions rather than parameter analysis or output comparison. The training-free method achieves competitive performance on model comparison tasks across 239 open-source LLMs while providing theoretical stability guarantees.