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cs.LG2026
Detecting Diffusion-Generated Time Series Under Generator Shift
Zhi Wen Soi, Aditya Shankar, Gert Lek +4
The boundary between real and diffusion-generated time series is becoming increasingly difficult to draw, yet detection in this domain remains underexplored, especially when the ge…
cs.CV2026
TMPDiff: Temporal Mixed-Precision for Diffusion Models
Basile Lewandowski, Simon Kurz, Aditya Shankar +3
Diffusion models are the go-to method for Text-to-Image generation, but their iterative denoising processes has high inference latency. Quantization reduces compute time by using l…
cs.LG2026
Harpoon: Generalised Manifold Guidance for Conditional Tabular Diffusion
Aditya Shankar, Yuandou Wang, Rihan Hai +1
Generating tabular data under conditions is critical to applications requiring precise control over the generative process. Existing methods rely on training-time strategies that d…