ICML 2024 Past Large language modelsEfficiency
ICML 2024 Workshop on Efficient and Accessible Foundation Models for Biological Discovery
AccMLBio
- Submission deadline
- May 30, 2024, 12:01 UTC imported from OpenReview — check the website for extensions
- Submission portal
- OpenReview
- Notes
- Auto-imported from the OpenReview venue record on 2026-06-10 — please verify and enrich (topics are keyword-guessed).
Accepted papers (37)
Fetched from OpenReview (v2) on 2026-06-10.
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2Bits of Protein: Efficient Protein Language Models at the Scale of 2-bits
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A generative foundation model for antibody sequence understanding
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ABodyBuilder3: Improved and scalable antibody structure predictions
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Are Protein Language Models Compute Optimal?
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BioinformaticsBench: A collaboratively built large language model benchmark for Bioinformatics reasoning
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Caduceus: Bi-Directional Equivariant Long-Range DNA Sequence Modeling
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Compressing the Latent Space of Single-Sequence Protein Predictors for Multimodal Generation
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Cramming Protein Language Model Training in 24 GPU Hours
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Enhancing Single-Cell VAE Latent Space via Semi-Supervision
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Fine-tuning the ESM2 protein language model to understand the functional impact of missense variants
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FusOn-pLM: A Fusion Oncoprotein-Specific Language Model via Focused Probabilistic Masking
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Generative Model for Small Molecules with Latent Space RL Fine-Tuning to Protein Targets
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Geometric Algebra based encoding for graph prompting
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Graph2Token: Make LLMs Understand Molecule Graphs
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High-Resolution In Silico Painting with Generative Models
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Identifying Biological Priors and Structure in Single-Cell Foundation Models
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Injecting Hierarchical Biological Priors into Graph Neural Networks for Flow Cytometry Prediction
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Interactome-scale comparison of co-immunoprecipitation and yeast two-hybrid assays for protein interaction prediction
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Learning Generative Population Models From Multiple Clinical Datasets Via Probabilistic Programming
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Likelihood-based fine-tuning of protein language models for few-shot fitness prediction and design
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MiniMol: A Parameter-Efficient Foundation Model for Molecular Learning
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MolEval: An Evaluation Toolkit for Molecular Embeddings via LLMs
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MSA Pairing Transfomer: protein interaction partner prediction with few-shot contrastive learning
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Multi-Task Training Increases Native Sequence Recovery of Antigen-Specific T-cell Receptor Sequences
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One-Versus-Others Attention: Scalable Multimodal Integration for Biomedical Data
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PLUTO: Pathology-Universal Transformer
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Pre-training of Single-cell Language Models through Genetic Pathway Learning
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Prot2Token: A multi-task framework for protein language processing using autoregressive language modeling
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ProtMamba: a homology-aware but alignment-free protein state space model
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Rethinking Molecular Design: Integrating Latent Variable and Auto-Regressive Models for Enhanced Goal Directed Generation
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RFamLlama: an efficient conditional language model for RNA sequence generation across diverse structural families
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scTree: Discovering Cellular Hierarchies in the Presence of Batch Effects in scRNA-seq Data
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Simple and Effective Masked Diffusion Language Models
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SWUS: Active Learning with Structure Weighted Uncertainty Score
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Towards Generalizable Particle Picking in Cryo-EM Images by Leveraging Masked AutoEncoder
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Training Compute-Optimal Protein Language Models
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xMINT: A Multimodal Integration Transformer for Xenium Gene Imputation