9 papers
When Context Bites: Detecting RAG Poisoning via Document-Level Attention Collapse
Yingtao Ren, Ziyi Zhao, Yiwei Fu +3
Retrieval-augmented generation (RAG) is indispensable for enhancing large language models. However, RAGs are increasingly susceptible to poisoning attacks, in which adversarial doc…
iFuzz-Meta: An Interpretable Fuzzy Learning Framework Bridging Top-Down and Bottom-Up Knowledge Integration
Xiaowei Jiang, Daniel Leong, Beining Cao +5
Interpretable representation learning remains a key challenge in modern neural computation, particularly when models are expected not only to perform but also to explain their reas…
DF3DV-1K: A Large-Scale Dataset and Benchmark for Distractor-Free Novel View Synthesis
Cheng-You Lu, Yi-Shan Hung, Wei-Ling Chi +6
Advances in radiance fields have enabled photorealistic novel view synthesis. In several domains, large-scale real-world datasets have been developed to support comprehensive bench…
Hestia: Voxel-Face-Aware Hierarchical Next-Best-View Acquisition for Efficient 3D Reconstruction
Cheng-You Lu, Zhuoli Zhuang, Nguyen Thanh Trung Le +5
Advances in 3D reconstruction and novel view synthesis have enabled efficient and photorealistic rendering. However, images for reconstruction are still either largely manual or co…
Neuro-Cognitive Reward Modeling for Human-Centered Autonomous Vehicle Control
Zhuoli Zhuang, Yu-Cheng Chang, Yu-Kai Wang +2
Recent advancements in computer vision have accelerated the development of autonomous driving. Despite these advancements, training machines to drive in a way that aligns with huma…
Pretraining Large Brain Language Model for Active BCI: Silent Speech
Jinzhao Zhou, Zehong Cao, Yiqun Duan +9
This paper explores silent speech decoding in active brain-computer interface (BCI) systems, which offer more natural and flexible communication than traditional BCI applications.…