8 papers
Probing for Reading Times
Eleftheria Tsipidi, Samuel Kiegeland, Francesco Ignazio Re +4
Probing has shown that language model representations encode rich linguistic information, but it remains unclear whether they also capture cognitive signals about human processing.…
NTIRE 2026 Challenge on Video Saliency Prediction: Methods and Results
Andrey Moskalenko, Alexey Bryncev, Ivan Kosmynin +40
This paper presents an overview of the NTIRE 2026 Challenge on Video Saliency Prediction. The goal of the challenge participants was to develop automatic saliency map prediction me…
Bidirectional Channel-selective Semantic Interaction for Semi-Supervised Medical Segmentation
Kaiwen Huang, Yizhe Zhang, Yi Zhou +2
Semi-supervised medical image segmentation is an effective method for addressing scenarios with limited labeled data. Existing methods mainly rely on frameworks such as mean teache…
Learning Topology-Driven Multi-Subspace Fusion for Grassmannian Deep Network
Xuan Yu, Tianyang Xu
Grassmannian manifold offers a powerful carrier for geometric representation learning by modelling high-dimensional data as low-dimensional subspaces. However, existing approaches…
OKBench: Democratizing LLM Evaluation with Fully Automated, On-Demand, Open Knowledge Benchmarking
Yanhong Li, Tianyang Xu, Kenan Tang +3
Knowledge-intensive question answering is central to large language models (LLMs) and is typically assessed using static benchmarks derived from sources like Wikipedia and textbook…
Verification-Aware Planning for Multi-Agent Systems
Tianyang Xu, Dan Zhang, Kushan Mitra +1
Large language model (LLM) agents are increasingly deployed to tackle complex tasks, often necessitating collaboration among multiple specialized agents. However, multi-agent colla…
Serial Over Parallel: Learning Continual Unification for Multi-Modal Visual Object Tracking and Benchmarking
Zhangyong Tang, Tianyang Xu, Xuefeng Zhu +4
Unifying multiple multi-modal visual object tracking (MMVOT) tasks draws increasing attention due to the complementary nature of different modalities in building robust tracking sy…
Adaptive Hyper-Graph Convolution Network for Skeleton-based Human Action Recognition with Virtual Connections
Youwei Zhou, Tianyang Xu, Cong Wu +2
The shared topology of human skeletons motivated the recent investigation of graph convolutional network (GCN) solutions for action recognition. However, most of the existing GCNs…