Papers by Taeklim Kim
Decoding Dense Embeddings: Sparse Autoencoders for Interpreting and Discretizing Dense Retrieval (2025.emnlp-main)
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| Challenge: | Existing sparse retrieval methods suffer from a lack of interpretability . we propose a new interpretability framework that decomposes dense embeddings into distinct, interpretable latent concepts. |
| Approach: | They propose a new interpretability framework that leveragesSparse Autoencoders to decompose uninterpretable dense embeddings fromDPR models into distinct, interpretable latent concepts. |
| Outcome: | The proposed interpretability framework achieves high index-space and computational efficiency while maintaining robust performance across vocabulary and semantic mismatches. |