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Hi, thanks for the cool MTEB toolkit.
We are currently preparing to release an embedding model for *universal multimodal retrieval*, along with our compiled evaluations. I noticed that you are also…
izhx updated
16 hours ago
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RAG workflows and/or LLM tasks commonly need to retrieve data. In our case it's often by performing semantic (or hybrid) search against one or multiple ES indices.
Sometimes, those retrieval subtaks…
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Traceback (most recent call last):
File "/home/bqc/project/evalscope/MTEBtest.py", lin…
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For a mixed precision approach, I observed that the query_embeddings for the retrieval task gets cast to the global precision policy while the candidate_embedding preserves its dtype. It causes the li…
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Q1: Novelty of RazorAttention:
Our work is the first to apply induction heads for KV cache compression, and we introduce two essential strategies that go beyond the use of induction heads to achieve …
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jina-embeddings-v3 is a multilingual multi-task text embedding model designed for a variety of NLP applications. Based on the [Jina-XLM-RoBERTa architecture](https://huggingface.co/jinaai/xlm-roberta-…
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We sincerely appreciate your constructive feedback of our paper, and we will make certain updates w.r.t. your concerns in our revised version. Below are our responses to your concerns.
Q1: Comparis…
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### Question Validation
- [X] I have searched both the documentation and discord for an answer.
### Question
As my understanding, using Jina Embedding v3 for RAG,
- use task type "retrieval.que…
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Latest report:
https://compliance.allocator.tech/report/f03018494/1730680343/report.md
Since the allocator has been running, there have been a total of 5 client application requests.
Overall, th…
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Q1: Whether the retrieval pattern holds in general query settings
Thank you for pointing this out. The retrieval patterns remain highly consistent across different input queries, suggesting that they…