🏢 Hong Kong Baptist University

New uncertainty estimation method for 3D Gaussian Splatting improves scene reconstruction quality by leveraging variational multi-scale representation and efficiently removing noisy data.

CoPA improves cross-domain few-shot learning by adapting separate transformations for prototype and image embeddings, significantly enhancing performance and revealing better representation clusters.

Deterministically shaping in-distribution feature space solves OOD detection’s distributional assumption challenge, leading to superior performance.

Geometry Cloak embeds invisible perturbations in images to thwart AI-based 3D reconstruction, forcing the AI to generate identifiable patterns that act as watermarks to assert copyright.

FuseFL achieves superior one-shot federated learning performance by leveraging a causal view of data heterogeneity and progressively fusing model blocks, significantly outperforming existing methods w…

COAT leverages LLMs to identify high-level causal factors from unstructured data, enabling causal discovery in real-world scenarios where well-defined variables are lacking.

LLMs struggle with noisy rationales in chain-of-thought prompting. This paper introduces the NoRa dataset, showing that existing methods struggle. A new method, CD-CoT, significantly improves accura…

CounterAnimal: a new dataset exposes CLIP’s reliance on spurious correlations, challenging its perceived robustness and highlighting the need for more comprehensive evaluation benchmarks in vision-lan…