ProteinJEPA: Latent prediction improves protein language model pretraining
cs.LG, cs.AI, q-bio.BM, stat.ML
Submitted: 2026-05-08
Updated: 2026-09-23
Code: https://github.com/nadavbra/protein_bert
Terminology
Sources
- Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture
- LeJEPA: Provable and Scalable Self-Supervised Learning Without the Heuristics
- Revisiting Feature Prediction for Learning Visual Representations from Video
- FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning
- LLM-JEPA: Large Language Models Meet Joint Embedding Predictive Architectures
- JEPA-DNA: Grounding Genomic Foundation Models through Joint-Embedding Predictive Architectures
- LeWorldModel: Stable End-to-End Joint-Embedding Predictive Architecture from Pixels
- ProGen2: Exploring the Boundaries of Protein Language Models
- Evaluating Protein Transfer Learning with TAPE
- Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference
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