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[WIP] Update BibTeX citation for CLIBD in project website#40
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Agent-Logs-Url: https://github.com/bioscan-ml/clibd/sessions/d97fcb7c-549a-4286-841d-8d8dd5457c8d Co-authored-by: gwtaylor <993736+gwtaylor@users.noreply.github.com>
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May 11, 2026 19:20
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/docs/index.htmlis still the old arXiv citation/README.md/docs/index.htmlwith the ICLR 2025@inproceedingscitation2025and old arXiv fields are removedmainOriginal prompt
Update the project website BibTeX citation in
docs/index.htmlfor repositorybioscan-ml/clibd.Context:
README.mdalready contains the correct conference citation.Required change:
docs/index.htmland replace the existing CLIBD BibTeX block:@article{gong2024clibd, ...}entryUse this citation content:
Acceptance criteria:
docs/index.htmlis updated.2025.<pre>block.Create a pull request against the
mainbranch.The following is the prior conversation context from the user's chat exploration (may be truncated):
User: ```
@INPROCEEDINGS{Gong2024-wh,
title = "{CLIBD}: Bridging Vision and Genomics for Biodiversity Monitoring
at Scale",
author = "Gong, Zeming and Wang, Austin and Huo, Xiaoliang and Haurum,
Joakim Bruslund and Lowe, Scott C and Taylor, Graham W and Chang,
Angel X",
booktitle = "The Thirteenth International Conference on Learning
Representations",
abstract = "Measuring biodiversity is crucial for understanding ecosystem
health. While prior works have developed machine learning models
for taxonomic classification of photographic images and DNA
separately, in this work, we introduce a multi-modal approach
combining both, using CLIP-style contrastive learning to align
images, barcode DNA, and text-based representations of taxonomic
labels in a unified embedding space. This allows for accurate
classification of both known and unknown insect species without
task-specific fine-tuning, leveraging contrastive learning for
the first time to fuse DNA and image data. Our method surpasses
previous single-modality approaches in accuracy by over 8% on
zero-shot learning tasks, showcasing its effectiveness in
biodiversity studies.",
month = "4~" # oct,
year = 2024,
url = "https://openreview.net/forum?id=d5HUnyByAI"
}
But the website still has the old arXiv preprint BibTeX here:
Recommended replacement: