arXiv AI

TheBioCollection: Unified Pre-Training Scale LLM Corpus for Biology

arXiv:2607. 08803v1 Announce Type: cross Abstract: The push toward large language models for biology (BioLM) has created a need for training corpora that can endow models with a genuine understanding of biology.

arXiv AI

Aug 3

Can Large Language Models Derive New Knowledge? A Dynamic Benchmark for Biological Knowledge Discovery

arXiv:2603. 03322v2 Announce Type: replace-cross Abstract: Recent advancements in Large Language Model (LLM) agents have demonstrated remarkable potential in automatic knowledge discovery.

By Chaoqun Yang, Xinyu Lin, Shulin Li, Wenjie Wang, Ruihan Guo, Fuli Feng, Tat-Seng Chua

llms agents benchmarks

arXiv AI

Jun 30

A Large-Scale Dataset for Molecular Structure-Language Description via a Rule-Regularized Method

arXiv:2602. 02320v4 Announce Type: replace-cross Abstract: Molecular function is largely determined by structure.

By Feiyang Cai, Guijuan He, Yi Hu, Jingjing Wang, Joshua Luo, Tianyu Zhu, Srikanth Pilla, Gang Li, Ling Liu, Feng Luo

llms safety

arXiv AI

Jun 16

Few-Shot Biomedical Relation Extraction with Large Language Models: A Viable Alternative to Supervised Learning?

arXiv:2606. 15412v1 Announce Type: cross Abstract: Biomedical relation extraction (BioRE) is a key step in transforming biomedical literature into structured knowledge.

By Jakob Mraz, Toma\v{z} Curk, Bla\v{z} Zupan

llms

arXiv Machine Learning

Jul 31

PlantBGC: Transformer for Plant BGC Discovery via Label-Free Domain Adaptation and Weak Supervision

arXiv:2607. 27258v1 Announce Type: cross Abstract: Plant biosynthetic gene clusters (BGCs) encode specialized-metabolite pathways, yet curated plant BGC labels remain scarce, hindering supervised discovery at genome scale.

By Yuhan Zhao, Nidhi Grover, Zhishan Guo, Ning Sui

llms fine-tuning benchmarks

arXiv AI

Aug 10

bioMoR: Biology-Guided Mixture-of-Recursions for Effective Genomic Learning

arXiv:2608. 06727v1 Announce Type: new Abstract: Transformer models for high-dimensional omics analysis process thousands of genes or pathways, although only a subset requires deep computation.

By Koushik Howlader, Tirtho Roy, Md Tauhidul Islam, Wei Le

llms rag benchmarks safety

arXiv AI

Aug 12

JEPA-DNA: Grounding Genomic Foundation Models through Joint-Embedding Predictive Architectures

arXiv:2602. 17162v3 Announce Type: replace Abstract: Genomic Foundation Models (GFMs) typically rely on Masked Language Modeling (MLM) or Next-Token Prediction (NTP) to learn the "Laws of Nature".

By Ariel Larey, Elay Dahan, Amit Bleiweiss, Raizy Kellerman, Guy Leib, Omri Nayshool, Dan Ofer, Tal Zinger, Dan Dominissini, Gideon Rechavi, Nicole Bussola, Simon Lee, Shane O'Connell, Dung Hoang, Marissa Wirth, Alexander W. Charney, Nati Daniel, Yoli Shavit

rag diffusion benchmarks safety

Hugging Face Trending Papers

Jul 29

PlantBGC: Transformer for Plant BGC Discovery via Label-Free Domain Adaptation and Weak Supervision

Plant biosynthetic gene clusters (BGCs) encode specialized-metabolite pathways, yet curated plant BGC labels remain scarce, hindering supervised discovery at genome scale. Existing plant BGC mining tools are largely signature- and rule-driven and do not fully leverage recent advances in contextual representation learning for modeling long-range domain context and controlling false positives under strong domain shift.

llms fine-tuning benchmarks

arXiv AI

Aug 6

AutoProteinEngine: A Large Language Model Driven Agent Framework for Multimodal AutoML in Protein Engineering

arXiv:2411. 04440v1 Announce Type: cross Abstract: Protein engineering is important for biomedical applications, but conventional approaches are often inefficient and resource-intensive.

By Yungeng Liu, Zan Chen, Yu Guang Wang, Yiqing Shen

llms agents fine-tuning multimodal

arXiv Machine Learning

Jun 18

Contextualizing Biological Language Models across Modalities via Logit-Space Contrastive Alignment

arXiv:2606. 18703v1 Announce Type: new Abstract: Pretrained biological language models expose per-token probability distributions through masked-token prediction, providing the likelihood interface central to sequence design, variant scoring, and mechanistic interpretation.

By Yanjun Shao, Yundi Chen, Yashvi Patel, Aurelien Pelissier, Mar\'ia Rodr\'iguez Mart\'inez

llms rag nlp multimodal benchmarks safety

arXiv Machine Learning

Aug 5

Bi-semantic Chemical Embedder for Joint Representation Learning of SMILES and Natural Language

arXiv:2608. 03855v1 Announce Type: new Abstract: Transformer models have revolutionized natural language processing (NLP), and text-based molecular representations like SMILES have successfully extended these architectures to chemistry.

By David Ming Segura, Jeremy Goumaz, Joshua W. Sin, Bojana Rankovi\'c, Philippe Schwaller

llms rag nlp

Hugging Face Trending Papers

Aug 7

bioMoR: Biology-Guided Mixture-of-Recursions for Effective Genomic Learning

Transformer models for high-dimensional omics analysis process thousands of genes or pathways, although only a subset requires deep computation. Mixture-of-Recursions (MoR) improves efficiency through adaptive token-choice or expert-choice routing.

llms rag benchmarks safety

arXiv Machine Learning

Aug 4

SIGMA: Semantic Identifier Grouping for Molecular Autoregression

arXiv:2603. 25062v2 Announce Type: replace Abstract: Autoregressive molecular models assign probability to molecular serializations even though chemical identity is invariant to serialization.

By Xinyu Wang, Fei Dou, Jinbo Bi, Minghu Song

benchmarks safety

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