2 papers
cs.AI2026
When Terminal-Agent Training Stalls: Demystifying Data Generation and Verification Challenge
Xi Qin, Isabel Kurth, Xin Cui +3
Using a frontier model like Claude Opus as a meta-agent to generate terminal tasks and verifiers for RL training is increasingly common. Yet a runnable Docker image and executable…
cs.LG2026
Evaluating Post-hoc Explanations of the Transformer-based Genome Language Model DNABERT-2
Isabel Kurth, Paulo Yanez Sarmiento, Bernhard Y. Renard
Explaining deep neural network predictions on genome sequences enables biological insight and hypothesis generation-often of greater interest than predictive performance alone. Whi…