Improve model card: Add `library_name`, update `license`, link paper & code, correct title and citation

#1
by nielsr HF Staff - opened
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  1. README.md +21 -14
README.md CHANGED
@@ -1,19 +1,23 @@
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  ---
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  language: en
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- license: other
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- tags:
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- - finance
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- - risk-relation
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- - retrieval
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- - encoder
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- - feature-extraction
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- - stock-prediction
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  pipeline_tag: feature-extraction
 
 
 
 
 
 
 
 
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  ---
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- # Financial Risk Identification through Dual-view Adaptation — Encoder
 
 
 
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- This repository hosts the pretrained encoder from the work **“Financial Risk Identification through Dual-view Adaptation.”**
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  The model is designed to uncover **inter-firm risk relations** from financial text, supporting downstream tasks such as **retrieval**, **relation mining**, and **stock-signal experiments** where relation strength acts as a feature.
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  > **Files**
@@ -28,7 +32,7 @@ The model is designed to uncover **inter-firm risk relations** from financial te
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  The model aligns two complementary “views” of firm relations and adapts them during training:
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  - **Lexical view (`lex`)** — focuses on token/phrase-level and domain terms common in 10-K and financial news.
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- - **Temporal view (`time`)** — encourages stability/consistency of relations across reporting periods and evolving events.
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  A **two-view combination (“Best”)** integrates both signals and yields stronger retrieval quality and more stable risk-relation estimates. Ablations (`lex`, `time`) are also supported for analysis.
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@@ -82,9 +86,12 @@ print(similarity)
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  If you use this model or the dual-view methodology, please cite:
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  ```bibtex
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  @misc{financial_risk_dualview_2025,
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- title = {Financial Risk Identification through Dual-view Adaptation},
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  author = {Chiu, Wei-Ning and collaborators},
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  year = {2025},
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- note = {Preprint/Project},
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- howpublished = {\url{https://huggingface.co/william0816/Dual_View_Financial_Encoder}}
 
 
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  }
 
 
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  ---
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  language: en
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+ license: apache-2.0
 
 
 
 
 
 
 
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  pipeline_tag: feature-extraction
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+ tags:
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+ - finance
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+ - risk-relation
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+ - retrieval
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+ - encoder
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+ - feature-extraction
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+ - stock-prediction
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+ library_name: transformers
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  ---
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+ # Financial Risk Relation Identification through Dual-view Adaptation — Encoder
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+
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+ **Paper:** [Financial Risk Relation Identification through Dual-view Adaptation](https://huggingface.co/papers/2509.18775)
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+ **Code:** [https://github.com/cnclabs/codes.fin.relation](https://github.com/cnclabs/codes.fin.relation)
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+ This repository hosts the pretrained encoder from the work **“Financial Risk Relation Identification through Dual-view Adaptation.”**
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  The model is designed to uncover **inter-firm risk relations** from financial text, supporting downstream tasks such as **retrieval**, **relation mining**, and **stock-signal experiments** where relation strength acts as a feature.
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  > **Files**
 
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  The model aligns two complementary “views” of firm relations and adapts them during training:
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  - **Lexical view (`lex`)** — focuses on token/phrase-level and domain terms common in 10-K and financial news.
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+ - **Temporal view (`time`) — encourages stability/consistency of relations across reporting periods and evolving events.
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  A **two-view combination (“Best”)** integrates both signals and yields stronger retrieval quality and more stable risk-relation estimates. Ablations (`lex`, `time`) are also supported for analysis.
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  If you use this model or the dual-view methodology, please cite:
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  ```bibtex
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  @misc{financial_risk_dualview_2025,
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+ title = {Financial Risk Relation Identification through Dual-view Adaptation},
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  author = {Chiu, Wei-Ning and collaborators},
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  year = {2025},
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+ eprint={2509.18775},
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+ archivePrefix={arXiv},
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+ primaryClass={cs.CL},
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+ url={https://arxiv.org/abs/2509.18775}
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  }
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+ ```