Can We Trust In-Distribution Success? Locked Evaluation Reveals Transfer Failure and Sampling-Depth Entanglement in CRISPRi Perturbation Prediction

arXiv:2608.00152 · cs.LG, cs.AI · Submitted 2026-07-31 · Read on arXiv

cs.LG, cs.AI

Submitted: 2026-07-31

Updated: 2026-08-31

Terminology

• Ablation — 14× in this paper · explained in 1 episode
• Alignment — 14× in this paper · explained in 1 episode
• Benchmark — 10× in this paper · explained in 2 episodes
• Foundation Model — 10× in this paper · explained in 3 episodes
• Robustness — 10× in this paper · explained in 5 episodes
• Virtual Cell Challenge — 7× in this paper
• Calibration — 6× in this paper · explained in 7 episodes
• Foundation Models — 6× in this paper · explained in 7 episodes
• Zero-Shot Transfer — 6× in this paper · explained in 3 episodes
• Generalization — 5× in this paper · explained in 13 episodes
• Mode Collapse — 5× in this paper · explained in 2 episodes
• Benchmarking — 4× in this paper · explained in 3 episodes
• Embeddings — 4× in this paper · explained in 2 episodes
• Fine-Tuning — 4× in this paper · explained in 5 episodes
• Regularization — 4× in this paper · explained in 3 episodes
• Verification — 4× in this paper · explained in 2 episodes
• Adam — 3× in this paper · explained in 2 episodes
• Distribution Shift — 3× in this paper · explained in 5 episodes
• Transformer — 3× in this paper · explained in 2 episodes
• Aggregation — 2× in this paper · explained in 1 episode
• Conference on Computer Vision and Pattern Recognition — 2× in this paper
• In International Conference on Learning Representations — 2× in this paper
• In International Conference on Machine Learning — 2× in this paper
• Provenance — 2× in this paper · explained in 3 episodes
• alpha — 2× in this paper · explained in 1 episode
• Causal Inference — 1× in this paper · explained in 4 episodes
• Entanglement — 1× in this paper · explained in 3 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Label Distribution Smoothing — 1× in this paper
• Representation Learning — 1× in this paper · explained in 2 episodes
• Selection Bias — 1× in this paper · explained in 4 episodes
• Transfer Learning — 1× in this paper · explained in 10 episodes

Sources

• Invariant Risk Minimization

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