collaborators

10 papers

q-bio.GN2026

scBench-Long: Verifiable Benchmarking of Long-Horizon Single-Cell Biology

Ian Diks, Zhen Yang, Arjun Banerjee +2

Single-cell studies require analysts to convert raw measurements into specific biological claims through multi-step workflows and integration of metadata, assay context, and auxili…

cs.AI2026

TxBench-PP: Analyzing AI Agent Performance on Small-Molecule Preclinical Pharmacology

Hannah Le, Ramesh Ramasamy, Alex Urrutia +3

Artificial intelligence (AI) agents promise to accelerate drug discovery by compressing interpretation and decision-making loops, but practical deployment requires trusted evaluati…

cs.AI2026

EpiBench: Verifiable Evaluation of AI Agents on Epigenomics Analysis

Harihara Muralidharan, Reema Baskar, Soo Hee Lee +2

We introduce EpiBench, a verifiable benchmark for short-horizon epigenomics analysis. EpiBench evaluates whether agents can make well-defined analysis decisions from realistic work…

cs.AI2026

Verifiable Benchmarking of Long-Horizon Spatial Biology

Ian Diks, Harihara Muralidharan, Tim Proctor +1

AI agents are increasingly useful for biological data analysis, but existing benchmarks mostly test broad biological knowledge, executable workflows, or localized analysis steps ra…

quant-ph2026

Scalable linearized gate set tomography

Ashe Miller, Corey Ostrove, Jordan Hines +4

Characterizing errors on many-qubit quantum computers remains a key challenge to understanding and improving the performance of these devices. Current characterization methods eith…

quant-ph2026

Simulating Quantum Error Correction beyond Pauli Stochastic Errors

Jordan Hines, Corey Ostrove, Kenneth Rudinger +4

Quantum error correction (QEC), the lynchpin of fault-tolerant quantum computing (FTQC), is designed and validated against well-behaved Pauli stochastic error models. But in real-w…