← Search

Kelu Yao

7 accepted papers

2026

Asymmetric Cross-Modal Knowledge Distillation: Bridging Modalities with Weak Semantic Consistency

AAAI 2026technical

Cross-modal Knowledge Distillation has demonstrated promising performance on paired modalities with strong semantic connections, referred to as Symmetric Cross-modal Knowledge Distillation (SCKD). However, implementing SCKD becomes exceedingly constrained in real-world scenarios due to the limited a

Cited by 0SourcePDFScholar
2025

Forensics-Bench: A Comprehensive Forgery Detection Benchmark Suite for Large Vision Language Models

CVPR 2025poster

Recently, the rapid development of AIGC has significantly boosted the diversities of fake media spread in the Internet, posing unprecedented threats to social security, politics, law, and etc.To detect the ever-increasingly **diverse** malicious fake media in the new era of AIGC, recent studies have…

2024

Diagnosing the Compositional Knowledge of Vision Language Models from a Game-Theoretic View

ICML 2024poster

Compositional reasoning capabilities are usually considered as fundamental skills to characterize human perception. Recent studies show that current Vision Language Models (VLMs) surprisingly lack sufficient knowledge with respect to such capabilities. To this end, we propose to thoroughly diagnose…

2023

AGAIN: Adversarial Training With Attribution Span Enlargement and Hybrid Feature Fusion

CVPR 2023poster

The deep neural networks (DNNs) trained by adversarial training (AT) usually suffered from significant robust generalization gap, i.e., DNNs achieve high training robustness but low test robustness. In this paper, we propose a generic method to boost the robust generalization of AT methods from the…

2023

Towards Understanding the Generalization of Deepfake Detectors from a Game-Theoretical View

ICCV 2023poster

This paper aims to explain the generalization of deepfake detectors from the novel perspective of multi-order interactions among visual concepts. Specifically, we propose three hypotheses: 1. Deepfake detectors encode multi-order interactions among visual concepts, in which the low-order interacti…

Cited by 17PDFScholar
2022

Interpretable Generative Adversarial Networks

AAAI 2022technical

Learning a disentangled representation is still a challenge in the field of the interpretability of generative adversarial networks (GANs). This paper proposes a generic method to modify a traditional GAN into an interpretable GAN, which ensures that filters in an intermediate layer of the generator…