3 papers
cs.AI2026
SynthPert: Enhancing LLM Biological Reasoning via Synthetic Reasoning Traces for Cellular Perturbation Prediction
Lawrence Phillips, Marc Boubnovski Martell, Aditya Misra +4
Predicting cellular responses to genetic perturbations represents a fundamental challenge in systems biology, critical for advancing therapeutic discovery and virtual cell modeling…
cs.LG2026
MechPert: Mechanistic Consensus as an Inductive Bias for Unseen Perturbation Prediction
Marc Boubnovski Martell, Josefa Lia Stoisser, Lawrence Phillips +6
Predicting transcriptional responses to unseen genetic perturbations is essential for understanding gene regulation and prioritizing large-scale perturbation experiments. Existing…
cs.AI2025
Towards Label-Free Biological Reasoning Synthetic Dataset Creation via Uncertainty Filtering
Josefa Lia Stoisser, Lawrence Phillips, Aditya Misra +5
Synthetic chain-of-thought (CoT) traces are widely used to train large reasoning models (LRMs), improving generalization by providing step-level supervision. Yet most approaches re…