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Research paper reveals embedding models struggle with retrieval instructions

By PulseAugur Editorial · [1 sources] ·

A new research paper explores how embedding models respond to detailed retrieval instructions, finding that current models often fail to reliably follow these instructions, especially when query-side distractors are present. The study hypothesizes that this issue stems from the training setup and evaluation methods of these models. Researchers demonstrated that fine-tuning embedding models with added query-side distractors significantly improves their ability to follow instructions without negatively impacting performance on other tasks. AI

IMPACT This research highlights a key limitation in current embedding models, suggesting that improved training methodologies are needed for reliable instruction following in retrieval tasks.

RANK_REASON The cluster contains a research paper published on arXiv. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Research paper reveals embedding models struggle with retrieval instructions

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The cluster contains a research paper published on arXiv. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Amanda Myntti, Jenna Kanerva, Veronika Laippala, Filip Ginter ·

    Your Prompt Should Do More: Effects of Retrieval Instructions in Embedding Models

    arXiv:2610.10508v1 Announce Type: new Abstract: Prompted embedding models have recently received increasing attention, particularly for retrieval, where detailed retrieval instructions are provided as part of the retrieval prompt. Several new datasets and studies have examined th…

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