ML Research Hub
32.6K subscribers
3.39K photos
133 videos
23 files
3.62K links
Advancing research in Machine Learning – practical insights, tools, and techniques for researchers.

Admin: @HusseinSheikho
Download Telegram
BiCA: Effective Biomedical Dense Retrieval with Citation-Aware Hard Negatives

📝 Summary:
BiCA improves biomedical dense retrieval by using citation links as hard negatives. This leverages document structure to enhance performance with minimal fine-tuning, enabling data-efficient domain adaptation.

🔹 Publication Date: Published on Nov 11

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.08029
• PDF: https://arxiv.org/pdf/2511.08029
• Github: https://github.com/NiravBhattLab/BiCA

🔹 Models citing this paper:
https://huggingface.co/bisectgroup/BiCA-small
https://huggingface.co/bisectgroup/BiCA-base

Datasets citing this paper:
https://huggingface.co/datasets/bisectgroup/2hop-citation-graphs
https://huggingface.co/datasets/bisectgroup/hard-negatives-traversal

==================================

For more data science resources:
https://t.iss.one/DataScienceT

#BiomedicalAI #DenseRetrieval #NLP #MachineLearning #InformationRetrieval