Scholars Question Evaluation Standards in Single-Cell Perturbation Prediction
anshulkundaje · x · 2026-07-08
Stanford scholar Anshul Kundaje points out severe flaws in the experimental design and performance metrics of current single-cell perturbation prediction models. He warns that if a model can easily beat those trained on massive datasets, it indicates fundamental deviations in the field's evaluation benchmarks and timeline settings.
More from Research
- Kimi K3 may be strong on cyber, but token efficiency keeps it off UK AISIS — teortaxesTex · 2026-07-27
- ARC AGI 3 should have stayed private, with no examples or public dataset — flowersslop · 2026-07-27
- ExploitGym may have only 60–70% solvable tasks, fueling the OpenAI cheating debate — max_paperclips · 2026-07-27
- RTX 5090 local tests show Qwen Q6 can drop to 15 tok/s at 80k context — LFAdvice7984 · 2026-07-27
- Noahpinion quotes Chollet: intelligence may hit a hard ceiling — binarybits · 2026-07-27
- Paper argues graph topology can become the core operating system for AI agents — theomitsa · 2026-07-27