Multimodal Cross-Lingual Summarization for Videos: A Revisit in Knowledge Distillation Induced Triple-Stage Training Method.

Multimodal summarization (MS) for videos aims to generate summaries from multi-source information (e.g., video and text transcript), showing promising progress recently.

Tackling higher-order relations and heterogeneity: Dynamic heterogeneous hypergraph network for spatiotemporal activity prediction.

Spatiotemporal activity prediction aims to predict user activities at a particular time and location, which is applicable in city planning, activity recommendations, and other domains. The fundamental endeavor in spatiotemporal activity prediction is to model the intricate interaction patterns among users, locations, time, and activities, which is characterized by higher-order relations and heterogeneity. Recently, graph-based methods have gained popularity due to the advancements in graph neural networks.

Modeling High-Order Relationships: Brain-Inspired Hypergraph-Induced Multimodal-Multitask Framework for Semantic Comprehension.

Semantic comprehension aims to reasonably reproduce people's real intentions or thoughts, e.g., sentiment, humor, sarcasm, motivation, and offensiveness, from multiple modalities.

Multi-Modal Remote Sensing Image Segmentation with Intuition-Inspired Hypergraph Modeling.

Multi-modal remote sensing (RS) image segmentation aims to comprehensively utilize multiple RS modalities to assign pixel-level semantics to the studied scenes, which can provide a new perspective for global city understanding. Multi-modal segmentation inevitably encounters the challenge of modeling intra- and inter-modal relationships, i.e.

M2DCapsN: Multimodal, Multichannel, and Dual-Step Capsule Network for Natural Language Moment Localization.

Natural language moment localization aims to localize the target moment that matches a given natural language query in an untrimmed video. The key to this challenging task is to capture fine-grained video-language correlations to establish the alignment between the query and target moment. Most existing works establish a single-pass interaction schema to capture correlations between queries and moments.

Revealing influencing factors on global waste distribution via deep-learning based dumpsite detection from satellite imagery.

With the advancement of global civilisation, monitoring and managing dumpsites have become essential parts of environmental governance in various countries. Dumpsite locations are difficult to obtain in a timely manner by local government agencies and environmental groups. The World Bank shows that governments need to spend massive labour and economic costs to collect illegal dumpsites to implement management.

Mimicking the Brain's Cognition of Sarcasm From Multidisciplines for Twitter Sarcasm Detection.

Sarcasm is a sophisticated construct to express contempt or ridicule. It is well-studied in multiple disciplines (e.g.

Niacin analogue, 6-Aminonicotinamide, a novel inhibitor of hepatitis B virus replication and HBsAg production.

Background: Hepatitis B surface antigen (HBsAg) is one of the important clinical indexes for hepatitis B virus (HBV) infection diagnosis and sustained seroconversion of HBsAg is an indicator for functional cure. However, the level of HBsAg could not be reduced by interferons and nucleoside analogs effectively. Therefore, identification of a new drug targeting HBsAg is urgently needed.