NeurIPS 2025PastLarge language modelsAI for scienceMultimodal
NeurIPS 2025 2nd Workshop on Multi-modal Foundation Models and Large Language Models for Life Sciences
NeurIPS 2025 2nd Workshop FM4LS
- Submission deadline
- Sep 7, 2025, 12:00 UTCimported from OpenReview — check the website for extensions
- Submission portal
- OpenReview
- Notes
- Topics were auto-suggested and may be imprecise — edits welcome.
Accepted papers (53)
Fetched from OpenReview (v2) on 2026-06-10.
A Comparative Study of Semi-supervised Deep Anomaly Detection and LLMs for Monitoring Patients with Severe Health Status Undergoing Radiotherapy
A multi-domain EHR foundation model for predicting Hepatitis B liver disease: a clinical perspective
A Multi-Modal Deep Learning Model for Drug Potency Prediction: Leveraging Features from Physics-Based Docking and Advanced Co-Folding Methods
A Multi-Modal Foundation Model Across Species for Interpreting Gene Functions
Aligning Protein Language Models to Stability Preferences using 1M+ Experimental Mutant Effects
BaggingCPP: An Inductive PU-Learning Framework for Discovering Cell-Penetrating Peptides
Benchmarking Biomolecular Foundation Models for Cross-Modal Genomics-Proteomics
Beyond Labels: Explanatory Collapse due to Instruction Tuning in Protein LLMs
BiDoRA: Bi-level Optimization-Based Weight-Decomposed Low-Rank Adaptation for Overfitting-Resilient Fine-Tuning of Biological Foundation Models
BioCLIP 2: Emergent Properties from Scaling Hierarchical Contrastive Learning
Boundary Guidance for Efficient 3D CT Vision–Language Reasoning
CellSpliceNet: Explainable Multimodal Transformers for Splicing in C. elegans Neurons
Challenges in Leveraging Functional Information to Evaluate Predicted Protein-Ligand Interactions
CHEMSETS: How Capable Are Chemistry LLMs?
Decoding Histone Modification Signatures of Non-Coding RNAs via Foundation Models
DeepSpot2Cell: Predicting Virtual Single-Cell Spatial Transcriptomics from H&E images using Spot-Level Supervision
Disentangling Protein Family Signals in Protein Language Models: Composition or Motifs?
Explainable Insulin Pump Control with LLM Controllers for Type 1 Diabetes
FlashRNA: an efficient model for regulatory genomics
From Base Pairs to Functions: Rich RNA Representations via Multimodal Language Modeling
g-DPO: Scalable Preference Optimization for Protein Language Models
GLM-Prior: A Genomic Language Model for Sequence-Derived Prior Knowledge in GRN Inference
GRAM-DTI: Adaptive Multimodal Representation Learning for Drug–Target Interaction Prediction
Harnessing biomedical foundation models for genomic feature engineering to investigate patient drug response
HIP-HOP: Invariants for 2D Tilings with Biomedical Case Study
Horizon-Aware Vision–Language Forecasting of Diabetic Retinopathy with Text Prototypes
Hyperbolic Multimodal Representation Learning for Biological Taxonomies
Improved Therapeutic Antibody Reformatting through Multimodal Machine Learning
Learning In-Silico Maps of Transcription Factor Binding and Cooperativity interactions
Learning monosemantic features in multitask DNA regulatory sequence models via sparse autoencoder decomposition
Learning to Align Molecules and Proteins: A Geometry-Aware Approach to Binding Affinity
LINKER: Learning Interactions Between Functional Groups and Residues With Chemical Knowledge-Enhanced Reasoning and Explainability
LLM-Integrated Representative Path Selection for Context-Aware Drug Repurposing on Biomedical Knowledge Graphs
LLMGEN: Evolving Interpretable Surrogate Programs for Genomics with LLMs
Mechanistic Interpretability of Semantic Abstraction in Biomedical Texts
MoAgent: A Hypothesis-Driven Multi-Agent Framework for Drug Mechanism of Action Discovery
MolVision: Molecular Property Prediction with Vision Language Models
Motif-aware Tokenization of the Genome: Towards Interpretable Modeling of Gene Regulation
Multi-Modal Foundation Models for Computational Pathology: A Survey
Multimodal Alignment Reveals Interpretable Gene–Morphology Links in Perineuronal Net Pathology
Multimodal Survival Analysis with Locally Deployable Large Language Models
Multitask Asynchronous Bidirectional Multimodal Agent for Personalized Treatment Companions
Not all representations are equal: Comparing protein language models for antibody thermostability prediction
Position: Adjacent Technologies Are the Key Enablers of Scalable and Safe Clinical MLLM Deployment
Predicting and generating antibiotics against future pathogens with ApexOracle
Predicting cellular responses to perturbation across diverse contexts with State
Predicting Influenza Reassortment Potential Using Foundation Models and Genetic Algorithms for Pandemic Preparedness
Quantifying the Role of OpenFold Components in Protein Structure Prediction
Revealing bias in antibody language models through systematic training data processing with OAS-explore
The Exposome Interpreter: A Multi-Modal Framework for Personalized Autoimmune Care
Thin Bridges for Drug Text Alignment: Lightweight Contrastive Learning for Target Specific Drug Retrieval
Token-Level Guided Discrete Diffusion for Membrane Protein Design
Uncertainty-Guided Model Selection for Tabular Foundation Models in Biomolecule Efficacy Prediction