idopinto/ot-aspire-biomed-recon

Model Card for Model ID

otAspire model included in a paper for modeling fine-grained similarity between documents in the biomedical domain fine-tuned from Specter.

Title: "Multi-Vector Models with Textual Guidance for Fine-Grained Scientific Document Similarity"

Authors: Sheshera Mysore, Arman Cohan, Tom Hope

Paper: https://arxiv.org/abs/2111.08366

Github: https://github.com/allenai/aspire

Note: In the context of the paper, this model is referred to as otAspire and represents the papers proposed multi-vector model for fine-grained scientific document similarity.

Refer to https://huggingface.co/allenai/aspire-contextualsentence-multim-biomed for more details and usage.

Evaluation Results

Differences might be in co-citations training data which constructed from scratch from different release of S2ORC (originaly, 2019-09-28, which I didn't have access to.)

Model	TRECCOVID-MAP	TRECCOVID-NDCG%20	RELISH-MAP	RELISH-NDCG%20
specter	28.24	59.28	60.62	77.2
aspire-contextualsentence-multim-biomed*	30.92	62.23	62.57	78.95
aspire-contextualsentence-multim-biomed	31.25	62.99	62.24	78.65
ot-aspire-biomed-recon	26.65	57.44	61.36	78.28
os-aspire-biomed-specter2	31.05	61.52	62.68	79.32