mlsanityData to 14 Oct 2026

Description-Based Text Similarity

arXiv 2305.12517 ↗First posted 21 May 2023cs.CL cs.IR cs.LGcited by 7

Not on the map. Why?

Abstract (arXiv)

Identifying texts with a given semantics is central for many information seeking scenarios. Similarity search over vector embeddings appear to be central to this ability, yet the similarity reflected in current text embeddings is corpus-driven, and is inconsistent and sub-optimal for many use cases. What, then, is a good notion of similarity for effective retrieval of text? We identify the need to search for texts based on abstract descriptions of their content, and the corresponding notion of description based similarity. We demonstrate the inadequacy of current text embeddings and propose an alternative model that significantly improves when used in standard nearest neighbor search. The model is trained using positive and negative pairs sourced through prompting a LLM, demonstrating how data from LLMs can be used for creating new capabilities not immediately possible using the original model.

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 22 of its 30 references that are in the map. First posted on arXiv 21 May 2023.

Builds on

22 of 30 references.

References · 22

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10 more
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Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 2; 2024: 1; 2025: 3; 2026: 1.

7 papers.

  1. 2023When do Generative Query and Document Expansions Fail? A Comprehensive Study Across Methods, Retrievers, and Datasetscited by 26
  2. 2023DataFinder: Scientific Dataset Recommendation from Natural Language Descriptionscited by 15
  3. 2025QUDsim: Quantifying Discourse Similarities in LLM-Generated Textcited by 13
  4. 2024Onco-Retriever: Generative Classifier for Retrieval of EHR Records in Oncologycited by 3
  5. 2026Prompting Complexity: Shortest Prompts for Texts and Behaviors in LLMscited by 1
  6. 2025ConceptCarve: Dynamic Realization of Evidencecited by 0
  7. 2025Bias Testing and Mitigation in Black Box LLMs using Metamorphic Relationscited by 0