Papers with pseudo-relevance feedback
Somali Information Retrieval Corpus: Bridging the Gap between Query Translation and Dedicated Language Resources (2023.emnlp-main)
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| Challenge: | Existing research on the Somali language information retrieval relies on query translation . lack of digital resources is key obstacle to advancing language technologies . |
| Approach: | They develop an annotated corpus for Somali information retrieval using query expansion technique. |
| Outcome: | The proposed corpus comprises 2335 documents collected from well-known online sites . it can be used for text classification-related tasks and question-answering research purposes. |
Decoding a Neural Retriever’s Latent Space for Query Suggestion (2022.emnlp-main)
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Leonard Adolphs, Michelle Chen Huebscher, Christian Buck, Sertan Girgin, Olivier Bachem, Massimiliano Ciaramita, Thomas Hofmann
| Challenge: | Neural retrieval models have replaced bag-of-words methods for document retrieval . however, they lack the interpretability of bag-off-word models . |
| Approach: | They train a query decoder that generates a meaningful query from a latent representation of a neural search engine. |
| Outcome: | The proposed model outperforms both query reformulation and PRF information retrieval baselines. |
Learning to Select: Query-Aware Adaptive Dimension Selection for Dense Retrieval (2026.acl-long)
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| Challenge: | Existing methods for dense retrieval use pseudo-relevance feedback to model dimension importance . however, they learn global transformations shared across queries and do not model dimension-aware dimension importance. |
| Approach: | They propose a Query-Aware Adaptive Dimension Selection framework that learns to predict per-dimension importance directly from query embedding. |
| Outcome: | The proposed framework improves retrieval effectiveness over the full-dimensional and PRF-based models. |