Deep Learning
bit2bit: 1-bit quanta video reconstruction by self-supervised photon location prediction
This leads to the proposal of a novel self-supervised solution based on a masked loss function. We evaluate our method using both simulated and real data. On simulated data from a conventional video, we achieve 34.35 mean PSNR with extremely photon-sparse binary input (<0.06 photons per pixel per frame).
DeTeCtive: Detecting AI-generated T e xt via Multi-Level Contrastive Learning
These methodologies typically lead to performance bottlenecks and unsatisfactory generalizability.
Finding NeMo: Localizing Neurons Responsible For Memorization in Diffusion Models
Diffusion models (DMs) produce very detailed and high-quality images.
DAGER: Exact Gradient Inversion for Large Language Models
However, prior work has shown that the data can actually be recovered by the server using so-called gradient inversion attacks.
DuQuant: Distributing Outliers via Dual Transformation Makes Stronger Quantized LLMs
Quantization of large language models (LLMs) faces significant challenges, particularly due to the presence of outlier activations that impede efficient low-bit representation.
