3 citations · 3 across the 2 of their papers we have counts for
3 papers
ReproBAIT: Can coding agents build their own biological AI tools?
Shiv Muthupandiyan, Tolga H. Dur, Mac Walker +8
Large language models are increasingly competent at leveraging scientific knowledge and existing computational tools to execute complex workflows. At present, little information ex…
RepliBench: Evaluating the Autonomous Replication Capabilities of Language Model Agents
Sid Black, Asa Cooper Stickland, Jake Pencharz +7
Uncontrollable autonomous replication of language model agents poses a critical safety risk. To better understand this risk, we introduce RepliBench, a suite of evaluations designe…
From slides (through tiles) to pixels: an explainability framework for weakly supervised models in pre-clinical pathology
Marco Bertolini, Van-Khoa Le, Jake Pencharz +4
In pre-clinical pathology, there is a paradox between the abundance of raw data (whole slide images from many organs of many individual animals) and the lack of pixel-level slide a…