Update model card with paper and GitHub links

README.md

@@ -1,9 +1,10 @@
 ---
-license: cc-by-nc-4.0
-language:
-- en
 base_model:
 - Qwen/Qwen3-4B
+language:
+- en
+library_name: sentence-transformers
+license: cc-by-nc-4.0
 pipeline_tag: text-ranking
 tags:
 - finance
@@ -11,20 +12,23 @@ tags:
 - code
 - stem
 - medical
-library_name: sentence-transformers
 ---
 
 <img src="https://i.imgur.com/oxvhvQu.png"/>
 
 # Releasing zeroentropy/zerank-1
 
-In search enginers, [rerankers are crucial](https://www.zeroentropy.dev/blog/what-is-a-reranker-and-do-i-need-one) for improving the accuracy of your retrieval system.
+This model is the `zerank-1` reranker as introduced in the paper [zELO: ELO-inspired Training Method for Rerankers and Embedding Models](https://huggingface.co/papers/2509.12541).
+
+**Code**: [https://github.com/zeroentropy-ai/zbench](https://github.com/zeroentropy-ai/zbench)
+
+In search engines, [rerankers are crucial](https://www.zeroentropy.dev/blog/what-is-a-reranker-and-do_i_need_one) for improving the accuracy of your retrieval system.
 
 However, SOTA rerankers are closed-source and proprietary. At ZeroEntropy, we've trained a SOTA reranker outperforming closed-source competitors, and we're launching our model here on HuggingFace.
 
 This reranker [outperforms proprietary rerankers](https://huggingface.co/zeroentropy/zerank-1#evaluations) such as `cohere-rerank-v3.5` and `Salesforce/LlamaRank-v1` across a wide variety of domains, including finance, legal, code, STEM, medical, and conversational data.
 
-At ZeroEntropy we've developed an innovative multi-stage pipeline that models query-document relevance scores as adjusted [Elo ratings](https://en.wikipedia.org/wiki/Elo_rating_system). See our Technical Report (Coming soon!) for more details.
+At ZeroEntropy we've developed an innovative multi-stage pipeline that models query-document relevance scores as adjusted [Elo ratings](https://en.wikipedia.org/wiki/Elo_rating_system). More details are available in our paper: [zELO: ELO-inspired Training Method for Rerankers and Embedding Models](https://huggingface.co/papers/2509.12541).
 
 Since we're a small company, this model is only released under a non-commercial license. If you'd like a commercial license, please contact us at [email protected] and we'll get you a license ASAP.
 
@@ -53,14 +57,14 @@ The model can also be inferenced using ZeroEntropy's [/models/rerank](https://do
 
 NDCG@10 scores between `zerank-1` and competing closed-source proprietary rerankers. Since we are evaluating rerankers, OpenAI's `text-embedding-3-small` is used as an initial retriever for the Top 100 candidate documents.
 
-| Task           | Embedding | cohere-rerank-v3.5 | Salesforce/Llama-rank-v1 | zerank-1-small | **zerank-1** |
-|----------------|-----------|--------------------|--------------------------|----------------|--------------|
-| Code           |    0.678  |       0.724        |           0.694          |      0.730     |   **0.754**  |
-| Conversational |    0.250  |       0.571        |           0.484          |      0.556     |   **0.596**  |
-| Finance        |    0.839  |       0.824        |           0.828          |      0.861     |   **0.894**  |
-| Legal          |    0.703  |       0.804        |           0.767          |      0.817     |   **0.821**  |
-| Medical        |    0.619  |       0.750        |           0.719          |      0.773     |   **0.796**  |
-| STEM           |    0.401  |       0.510        |           0.595          |      0.680     |   **0.694**  |
+| Task | Embedding | cohere-rerank-v3.5 | Salesforce/Llama-rank-v1 | zerank-1-small | **zerank-1** |
+|---|---|---|---|---|---|
+| Code | 0.678 | 0.724 | 0.694 | 0.730 | **0.754** |
+| Conversational | 0.250 | 0.571 | 0.484 | 0.556 | **0.596** |
+| Finance | 0.839 | 0.824 | 0.828 | 0.861 | **0.894** |
+| Legal | 0.703 | 0.804 | 0.767 | 0.817 | **0.821** |
+| Medical | 0.619 | 0.750 | 0.719 | 0.773 | **0.796** |
+| STEM | 0.401 | 0.510 | 0.595 | 0.680 | **0.694** |
 
 Comparing BM25 and Hybrid Search without and with zerank-1: