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Embedding models struggle with retrieval instructions, new paper finds

By PulseAugur Editorial · [2 sources] ·

A new research paper explores the limitations of current embedding models in reliably following detailed retrieval instructions within prompts. The study, published on arXiv and highlighted by Hugging Face, demonstrates that these models can fail even simple instructions when presented with query-side distractors. Researchers hypothesize this is due to the current training setup and propose that fine-tuning with added distractors significantly improves performance without negatively impacting other tasks. AI

IMPACT Highlights a specific limitation in current embedding models, suggesting a path for improved performance in retrieval tasks.

RANK_REASON Research paper detailing findings on embedding model behavior.

Read on Hugging Face Daily Papers →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

Embedding models struggle with retrieval instructions, new paper finds

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Research paper detailing findings on embedding model behavior.
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COVERAGE [2]

  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…

  2. Hugging Face Daily Papers TIER_1 English(EN) ·

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

    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 this setting, showing that the current embedding m…

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