Generalizing from Limited Resources in the Open World

Efficient Methods for Low-resource Hardware.- Towards Point Cloud Compression for Machine Perception: A Simple and Strong Baseline by Learning the Octree Depth Level Predictor.- Toward Efficient Deep Spiking Neuron Networks: A Survey On Compression.- Towards Efficient Fault Detection of UHV DC Circuit Breakers.- Robust Autonomous Unmanned Aerial Vehicle System for Efficient Tracking of Moving Objects.- Efficient Fintuning with Limited Data.- Entity Augmentation for Efficient Classification of Vertically Partitioned Data with Limited Overlap.-CafeLLM: Context-Aware Fine-Grained Semantic Clustering using Large Language Models.- Adapter-Based Contextualized Meta Embeddings.- Advancements in Multimodal Systems.- MADP: Multi-modal Sequence Learning for Alzheimer's Disease Prediction with Missing Data.- Multi-modal Spatiotemporal Forecasting via Cross-scale Operator Learning and Spatial Representation Aggregation.- Improved VLN-BERT with Reinforcing Endpoint Alignment for Vision-and-Language Navigation.- Bridging the Language Gap: Domain-Specific Dataset Construction for Medical LLMs.- Integrating Text-to-Image and Vision Language Models for Synergistic Dataset Generation: The Creation of Synergy-General-Multimodal Pairs.- Recognition and Reasoning in the Open World.- Semantic-Degrade Learning Framework for Open World Object Detection.- Multi-modal Prompts with Feature Decoupling for Open-Vocabulary Object Detection.- YOLO-FCNET: Enhancing SAR Ship Detection with Fourier Convolution in YOLOv8.