6 papers
AdvSplat: Adversarial Attacks on Feed-Forward Gaussian Splatting Models
Yiran Qiao, Yiren Lu, Yunlai Zhou +4
3D Gaussian Splatting (3DGS) is increasingly recognized as a powerful paradigm for real-time, high-fidelity 3D reconstruction. However, its per-scene optimization pipeline limits s…
Counterfactual Visual Explanation via Causally-Guided Adversarial Steering
Yiran Qiao, Disheng Liu, Yiren Lu +3
Recent work on counterfactual visual explanations has contributed to making artificial intelligence models more explainable by providing visual perturbation to flip the prediction.…
When 'YES' Meets 'BUT': Can Large Models Comprehend Contradictory Humor Through Comparative Reasoning?
Tuo Liang, Zhe Hu, Jing Li +8
Understanding humor-particularly when it involves complex, contradictory narratives that require comparative reasoning-remains a significant challenge for large vision-language mod…
Segment then Splat: Unified 3D Open-Vocabulary Segmentation via Gaussian Splatting
Yiren Lu, Yunlai Zhou, Yiran Qiao +5
Open-vocabulary querying in 3D space is crucial for enabling more intelligent perception in applications such as robotics, autonomous systems, and augmented reality. However, most…
CAUSAL3D: A Comprehensive Benchmark for Causal Learning from Visual Data
Disheng Liu, Yiran Qiao, Wuche Liu +5
True intelligence hinges on the ability to uncover and leverage hidden causal relations. Despite significant progress in AI and computer vision (CV), there remains a lack of benchm…
SAIF: A Sparse Autoencoder Framework for Interpreting and Steering Instruction Following of Language Models
Zirui He, Haiyan Zhao, Yiran Qiao +4
The ability of large language models (LLMs) to follow instructions is crucial for their practical applications, yet the underlying mechanisms remain poorly understood. This paper p…