Papers by Max Conti
Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings (2025.emnlp-main)
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| Challenge: | Modern document retrieval embedding methods typically encode passages (chunks) from documents independently, often overlooking contextual information from the rest of the document. |
| Approach: | They propose a benchmark to evaluate retrieval models' ability to leverage document-wide context. |
| Outcome: | The proposed method significantly improves retrieval quality on ConTEB without sacrificing base model performance. |