Feature Extraction
Transformers
Safetensors
vision-encoder-decoder
custom_code
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@@ -6,13 +6,6 @@ datasets:
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  - StanfordAIMI/interpret-cxr-test-hidden
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  ---
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- <Gallery />
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-
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- widget:
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- - text: "drawing of tintin in a shop"
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- output:
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- url: "tokens.drawio.png"
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-
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  # CXRMate-RRG4: Entropy-Augmented Self-Critical Sequence Training for Radiology Report Generation
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  This is an evolution of https://huggingface.co/aehrc/cxrmate developed for the Radiology Report Generation task of BioNLP @ ACL 2024.
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  EAST was applied to a multimodal language model with RadGraph as the reward. Other features include:
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  - Token type embeddings to differentiate between findings and impression section tokens, as well as image embeddings.
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- - Special tokens (`NF` and `NI`) to handle missing *findings* and *impression* sections.
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  - Non-causal attention masking for the image embeddings and a causal attention masking for the report token embeddings.
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  ## Example:
 
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  - StanfordAIMI/interpret-cxr-test-hidden
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  ---
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  # CXRMate-RRG4: Entropy-Augmented Self-Critical Sequence Training for Radiology Report Generation
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  This is an evolution of https://huggingface.co/aehrc/cxrmate developed for the Radiology Report Generation task of BioNLP @ ACL 2024.
 
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  EAST was applied to a multimodal language model with RadGraph as the reward. Other features include:
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  - Token type embeddings to differentiate between findings and impression section tokens, as well as image embeddings.
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+ - Special tokens (`[NF]` and `[NI]`) to handle missing *findings* and *impression* sections.
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  - Non-causal attention masking for the image embeddings and a causal attention masking for the report token embeddings.
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  ## Example: