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LLMs4Bio 2024 : 1st AAAI Workshop on Large Language Models for Biological Discoveries | |||||||||||||
Link: https://llms4science-community.github.io/aaai2024.html | |||||||||||||
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Call For Papers | |||||||||||||
1st AAAI Workshop on Large Language Models for Biological Discoveries (LLMs4Bio)
Rapid advances in large language models (LLMs) provide an unprecedented opportunity to further scientific inquiry across scientific disciplines. The potential of LLMs beyond natural language has started attracting attention in various scientific disciplines. One representative area is biology, where the potential of employing LLMs to investigate the “language of life” is evident in a rapidly-growing body of research. This workshop brings together diverse researchers from computer and information science (e.g., artificial intelligence, informatics, human-AI interaction, etc.), and life science (e.g., molecular, cellular, and systems biology) to focus on unique challenges to LLMs for advancing biological discoveries. Objectives include formulating new problem spaces, technical advancements in foundation models, standardized datasets, community-accepted benchmarks, accounting for experimental error and quantifying uncertainty, injecting prior biological knowledge, etc. The workshop will additionally address the purchase of progress by scale, which leaves many academic researchers out from important discoveries. We will ask important questions about how we can make such research accessible and inclusive to power innovation at the intersection of LLMs and biology. Topics of Interest The workshop will be organized around three research themes: ● Foundational Models o Technical advances in pretraining, fine-tuning, prompting, and in-context learning of LLMs as motivated by biological problems. o Accessible, lightweight models, including beyond-attention paradigms. o Biological-inspired LLMs. o Interrogation mechanisms, interpretation, uncertainty quantification, etc. ● Bridging the gap: LLMs for Biological Problems o Recent trends in adopting and adapting LLMs for biological research o Multi-modal foundational models that integrate unstructured and structured (e.g., sequence or structure) data in biology. ● Next Scientific Breakthroughs o New problems addressed with LLMs. o Benchmarking LLMs on biological problems, such as standardizing biological datasets and metrics for LLM evaluation. o Vision and investigation of risks and caveats for LLMs in biology. General Co-Chairs ● Amarda Shehu, George Mason University (ashehu@gmu.edu) ● Yana Bromberg, Emory University (yana.bromberg@emory.edu) ● Liang Zhao, Emory University (liang.zhao@emory.edu) Paper submission instructions: To reflect the diversity of disciplines and perspectives, we encourage submissions of varying length: ● 1-page highlight papers ● 2-page position papers ● 4-page papers focusing on breaking results, datasets, benchmarks ● 6-8-page papers for novel methodology and/or more detailed investigations. Each manuscript should be submitted in a single PDF file, including all content, figures, tables, and references, following the format of AAAI conference papers. Paper submissions need to include author information (reviews are not double-blinded). Papers should be submitted at: https://easychair.org/my/conference?conf=llms4bio24 Concurrent submissions to other journals and conferences are acceptable. Accepted papers will be presented as posters or short talks during the workshop and published on the workshop website at https://llms4science-community.github.io/aaai2024.html. We encourage authors of accepted papers to submit datasets at https://github.com/LLMs4Science-Community. A small number of accepted papers may be selected to be presented as contributed talks. As a tradition, accepted workshop papers are NOT included in the ACM Digital Library. The authors maintain the copyright of their papers. Author enquiries should be directed at llms4science@gmail.com. Important Dates: Following are the key dates for the workshop. All deadlines are “anywhere on earth” (UTC-12). • Paper submission deadline: November 24, 2023 • Notification of decision: December 11, 2023 • Early Registration Deadline: December 20, 2023 • Workshop Day: February 26, 2024 Attendance For each accepted paper, at least one author must attend the conference and present their work. Authors of all accepted papers must prepare a final version for publication, a poster, and a three-minute short video presentation (details will be provided in the acceptance notification). |
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