most citedSynthPert: Enhancing LLM Biological Reasoning via Synthetic Reasoning Traces for Cellular Perturbation Prediction

1 citations · 1 across the 3 of their papers we have counts for

collaborators

8 papers

cs.AI2026

Ambig-DS: A Benchmark for Task-Framing Ambiguity in Data-Science Agents

Josefa Lia Stoisser, Marc Boubnovski Martell, Sidsel Boldsen +2

As data-science agents shift from co-pilots to auto-pilots, silent misframing becomes a critical failure mode. Agents quietly commit to plausible but unintended task framings, prod…

cs.AI2026

Measuring Black-Box Confidence via Reasoning Trajectories: Geometry, Coverage, and Verbalization

Marc Boubnovski Martell, Josefa Lia Stoisser, Kaspar Märtens +4

Reliable confidence estimation enables safe deployment of chain-of-thought (CoT) reasoning through text-only APIs. Yet the dominant black-box baseline, self-consistency over K samp…

cs.AI20261 cited

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…

cs.DB2025

Query, Don't Train: Privacy-Preserving Tabular Prediction from EHR Data via SQL Queries

Josefa Lia Stoisser, Marc Boubnovski Martell, Kaspar Märtens +4

Electronic health records (EHRs) contain richly structured, longitudinal data essential for predictive modeling, yet stringent privacy regulations (e.g., HIPAA, GDPR) often restric…