Saved in:
| Main Author: | |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2508.17694 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866915461290000384 |
|---|---|
| author | Farivar, Kayla |
| author_facet | Farivar, Kayla |
| contents | Information retrieval systems have progressed notably from lexical techniques such as BM25 and TF-IDF to modern semantic retrievers. This survey provides a brief overview of the BM25 baseline, then discusses the architecture of modern state-of-the-art semantic retrievers. Advancing from BERT, we introduce dense bi-encoders (DPR), late-interaction models (ColBERT), and neural sparse retrieval (SPLADE). Finally, we examine MonoT5, a cross-encoder model. We conclude with common evaluation tactics, pressing challenges, and propositions for future directions. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_17694 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Semantic Search for Information Retrieval Farivar, Kayla Information Retrieval Information retrieval systems have progressed notably from lexical techniques such as BM25 and TF-IDF to modern semantic retrievers. This survey provides a brief overview of the BM25 baseline, then discusses the architecture of modern state-of-the-art semantic retrievers. Advancing from BERT, we introduce dense bi-encoders (DPR), late-interaction models (ColBERT), and neural sparse retrieval (SPLADE). Finally, we examine MonoT5, a cross-encoder model. We conclude with common evaluation tactics, pressing challenges, and propositions for future directions. |
| title | Semantic Search for Information Retrieval |
| topic | Information Retrieval |
| url | https://arxiv.org/abs/2508.17694 |