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Foundation Models for Trajectory Planning in Autonomous Driving: A Review of Progress and Open Challenges
Kemal Oksuz, Alexandru Buburuzan, Anthony Knittel +2
The emergence of multi-modal foundation models has markedly transformed the technology for autonomous driving, shifting away from conventional and mostly hand-crafted design choice…
Modeling Gene Expression Distributional Shifts for Unseen Genetic Perturbations
Kalyan Ramakrishnan, Jonathan G. Hedley, Sisi Qu +5
We train a neural network to predict distributional responses in gene expression following genetic perturbations. This is an essential task in early-stage drug discovery, where suc…
Mixture of Experts Made Intrinsically Interpretable
Xingyi Yang, Constantin Venhoff, Ashkan Khakzar +4
Neurons in large language models often exhibit \emph{polysemanticity}, simultaneously encoding multiple unrelated concepts and obscuring interpretability. Instead of relying on pos…
AnnoCaseLaw: Legal Annotation Benchmark of Civil Negligence
Magnus Sesodia, Rilton Franzone, Alina Petrova +7
Language models offer a way to scale costly, labour-intensive expert annotation, but their ability to reproduce expert judgements remains uncertain. This is particularly challengin…
MObI: Multimodal Object Inpainting Using Diffusion Models
Alexandru Buburuzan, Anuj Sharma, John Redford +2
Safety-critical applications, such as autonomous driving, require extensive multimodal data for rigorous testing. Methods based on synthetic data are gaining prominence due to the…