3 papers
cs.LG2026
Autonomous mechanistic discovery of colorectal cancer vulnerabilities via multi-scale AI swarms
Christopher Baker, Tianyu Ren, Karen Rafferty +2
The acceleration of automated scientific discovery has been fundamentally bottlenecked by the epistemic gap between the semantic reasoning of large language models (LLMs) and the d…
cs.LG2026
Latent World Recovery for Multimodal Learning with Missing Modalities
Hui Wang, Tianyu Ren, Joseph Butler +3
We study multimodal learning under missing modalities, with particular motivation from bioscience applications in which heterogeneous modalities are often only partially available…
q-bio.QM2026
Contextual Invertible World Models: A Neuro-Symbolic Agentic Framework for Colorectal Cancer Drug Response
Christopher Baker, Tianyu Ren, Karen Rafferty +1
Precision oncology is currently limited by the small-N, large-P paradox, where high-dimensional genomic data is abundant but pharmacological response samples are sparse. While deep…