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Found 22 papers, 5 papers with code
RoboRefer: Towards Spatial Referring with Reasoning in Vision-Language Models for Robotics
Spatial referring is a fundamental capability of embodied robots to interact with the 3D physical world.
FinTagging: An LLM-ready Benchmark for Extracting and Structuring Financial Information
We introduce FinTagging, the first full-scope, table-aware XBRL benchmark designed to evaluate the structured information extraction and semantic alignment capabilities of large language models (LLMs) in the context of XBRL-based financial reporting.
AIS Data-Driven Maritime Monitoring Based on Transformer: A Comprehensive Review
Therefore, this paper reviews the research on Transformer-based AIS data-driven maritime monitoring, providing a comprehensive overview of the current applications of Transformer models in the marine field.
Lightweight Defense Against Adversarial Attacks in Time Series Classification
Moreover, the computational resources required for our ensemble are less than one-third of those required for PGD-based AT.
Recommendation System in Advertising and Streaming Media: Unsupervised Data Enhancement Sequence Suggestions
In this context, we introduce a novel framework, Global Unsupervised Data-Augmentation (UDA4SR), which adopts a graph contrastive learning perspective to generate more robust item embeddings for sequential recommendation.
Confidence Diagram of Nonparametric Ranking for Uncertainty Assessment in Large Language Models Evaluation
We consider the inference for the ranking of large language models (LLMs).
The Continuous-Time Weighted-Median Opinion Dynamics
It turns out that the proof methods for the original discrete-time asynchronous model are no longer applicable to the analysis of the continuous-time model.
Through the Lens of Core Competency: Survey on Evaluation of Large Language Models
From pre-trained language model (PLM) to large language model (LLM), the field of natural language processing (NLP) has witnessed steep performance gains and wide practical uses.
Why Don't You Clean Your Glasses? Perception Attacks with Dynamic Optical Perturbations
We demonstrate that the dynamic nature of EvilEye enables attackers to adapt adversarial examples across a variety of objects with a significantly higher ASR compared to state-of-the-art physical world attack frameworks.
Deep Graph-Level Clustering Using Pseudo-Label-Guided Mutual Information Maximization Network
In this work, we study the problem of partitioning a set of graphs into different groups such that the graphs in the same group are similar while the graphs in different groups are dissimilar.
Laplacian-based Cluster-Contractive t-SNE for High Dimensional Data Visualization
Dimensionality reduction techniques aim at representing high-dimensional data in low-dimensional spaces to extract hidden and useful information or facilitate visual understanding and interpretation of the data.
Learning to Rank Rationales for Explainable Recommendation
Seeing this gap, we propose a model named Semantic-Enhanced Bayesian Personalized Explanation Ranking (SE-BPER) to effectively combine the interaction information and semantic information.
Research on facial expression recognition based on Multimodal data fusion and neural network
In this paper, a neural network algorithm of facial expression recognition based on multimodal data fusion is proposed.
Facial Expression Recognition
Facial Expression Recognition (FER)
Deep Reinforcement Learning for Combinatorial Optimization: Covering Salesman Problems
This paper introduces a new deep learning approach to approximately solve the Covering Salesman Problem (CSP).
Example-based Real-time Clothing Synthesis for Virtual Agents
Given a query shape and pose of the virtual agent, we synthesize the resulting clothing deformation by blending the Taylor expansion results of nearby anchoring points.
Graphics
Breaking the Memory Wall for AI Chip with a New Dimension
Recent advancements in deep learning have led to the widespread adoption of artificial intelligence (AI) in applications such as computer vision and natural language processing.
E-commerce Recommendation with Weighted Expected Utility
In this paper, we interpret purchase utility as the satisfaction level a consumer gets from a product and propose a recommendation framework using EU to model consumers' behavioral patterns.
Graph Neural Networks with Continual Learning for Fake News Detection from Social Media
(2) GNNs trained on a given dataset may perform poorly on new, unseen data, and direct incremental training cannot solve the problem---this issue has not been addressed in the previous work that applies GNNs for fake news detection.
Image Analysis Enhanced Event Detection from Geo-tagged Tweet Streams
Events detected from social media streams often include early signs of accidents, crimes or disasters.
Adversarial Reinforcement Learning under Partial Observability in Autonomous Computer Network Defence
Recent studies have demonstrated that reinforcement learning (RL) agents are susceptible to adversarial manipulation, similar to vulnerabilities previously demonstrated in the supervised learning setting.
Reinforcement Learning for Autonomous Defence in Software-Defined Networking
Despite the successful application of machine learning (ML) in a wide range of domains, adaptability---the very property that makes machine learning desirable---can be exploited by adversaries to contaminate training and evade classification.
Adequacy of the Gradient-Descent Method for Classifier Evasion Attacks
Despite the wide use of machine learning in adversarial settings including computer security, recent studies have demonstrated vulnerabilities to evasion attacks---carefully crafted adversarial samples that closely resemble legitimate instances, but cause misclassification.
