[Blog] OpenSearch v3 Neural Sparse Models #3918
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Signed-off-by: yIwEN0713 <[email protected]>
yIwEN0713
requested review from
elfisher,
AMoo-Miki,
nknize,
krisfreedain,
peterzhuamazon,
CEHENKLE,
kolchfa-aws,
nateynateynate and
natebower
as code owners
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Hi @yIwEN0713, It looks like you're adding a new blog post but don't have an issue mentioned. Please link this PR to an open issue using one of these keywords in the PR description:
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pls take a ref at this PR to add your author information. And fix the render problem
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| ## Behind the improvements: Technology highlights | ||
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| ### $L_0$-based sparsification |
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L_0 doesn't get rendered correctly. same below
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| Similar to the tests described in our previous blog post, we evaluated the search relevance of the models on BEIR benchmark. The search relevance results are shown in the table below. All v3‑series models outperform their v2 and v1 counterparts, with v3‑gte achieving the highest relevance scores across all tests and setting a new record for OpenSearch neural sparse retrieval models. Notably, v3-gte sets a new state-of-the-art among publicly available sparse models. | ||
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This table also doesn't get rendered correctly
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Signed-off-by: yIwEN0713 <[email protected]>
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@natebower - Including you for technical review on this blog. |
@pajuric It looks like this one may already be under tech review (also, I'm not able to provide tech reviews). |
Signed-off-by: yIwEN0713 <[email protected]>
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LGTM. @pajuric I think we're good to move forward to the next review phase
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@natebower - Thanks for letting me know. We'll leave this one for Fanit when she returned early next week. |
Signed-off-by: Fanit Kolchina <[email protected]>
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Hey @yIwEN0713, doc review complete - nice job! Moving on to editorial review. |
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New blog
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Signed-off-by: Nathan Bower <[email protected]>
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Thanks @yIwEN0713! LGTM
@pajuric This should be ready to publish.
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Done and ready to publish
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| date: 2025-08-25 | ||
| meta_keywords: search relevance, neural sparse search, OpenSearch semantic search | ||
| meta_description: Enhancing OpenSearch neural sparse models with GTE and LLM teachers. |
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Updated meta:
meta_keywords: Neural sparse search, semantic search, OpenSearch sparse retrievers, search relevance, vector search, neural sparse models, GTE architecture, search relevance benchmarks, multilingual sparse retrieval, OpenSearch forum
meta_description: Discover OpenSearch v3's advanced neural sparse models and new multilingual retrieval capabilities, offering improved search relevance while maintaining efficient, inference-free performance
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| - technical-posts | ||
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| date: 2025-08-25 |
Description
Blog about OpenSearch v3 Neural Sparse Models.
Issues Resolved
Resolve #3912
Check List
By submitting this pull request, I confirm that my contribution is made under the terms of the BSD-3-Clause License.