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Found 12 papers, 1 papers with code
MonoBox: Tightness-free Box-supervised Polyp Segmentation using Monotonicity Constraint
We propose MonoBox, an innovative box-supervised segmentation method constrained by monotonicity to liberate its training from the user-unfriendly box-tightness assumption.
ChatGPT Rates Natural Language Explanation Quality Like Humans: But on Which Scales?
Our results show that ChatGPT aligns better with humans in more coarse-grained scales.
Token-Ensemble Text Generation: On Attacking the Automatic AI-Generated Text Detection
The robustness of AI-content detection models against cultivated attacks (e. g., paraphrasing or word switching) remains a significant concern.
Cold & Warm Net: Addressing Cold-Start Users in Recommender Systems
Finally, we evaluate our Cold & Warm Net on public datasets in comparison to models commonly applied in the matching stage and it outperforms other models on all user types.
Random Padding Data Augmentation
Random Padding is parameter-free, simple to construct, and compatible with the majority of CNN-based recognition models.
Is ChatGPT better than Human Annotators? Potential and Limitations of ChatGPT in Explaining Implicit Hate Speech
Recent studies have alarmed that many online hate speeches are implicit.
Chain of Explanation: New Prompting Method to Generate Higher Quality Natural Language Explanation for Implicit Hate Speech
Recent studies have exploited advanced generative language models to generate Natural Language Explanations (NLE) for why a certain text could be hateful.
Multi-Task Fusion via Reinforcement Learning for Long-Term User Satisfaction in Recommender Systems
The mainstream RS ranking framework is composed of two parts: a Multi-Task Learning model (MTL) that predicts various user feedback, i. e., clicks, likes, sharings, and a Multi-Task Fusion model (MTF) that combines the multi-task outputs into one final ranking score with respect to user satisfaction.
Network Activities Recognition and Analysis Based on Supervised Machine Learning Classification Methods Using J48 and Naïve Bayes Algorithm
Network activities recognition has always been a significant component of intrusion detection.
Highlight Timestamp Detection Model for Comedy Videos via Multimodal Sentiment Analysis
In this paper, we analyze the difficulties in abstract understanding of videos and propose a multimodal structure to obtain state-of-the-art performance in this field.
Hierarchical Disentangled Representation Learning for Outdoor Illumination Estimation and Editing
However, naively compressing an outdoor panorama into a low-dimensional latent vector, as existing models have done, causes two major problems.
TFNet: Multi-Semantic Feature Interaction for CTR Prediction
The CTR (Click-Through Rate) prediction plays a central role in the domain of computational advertising and recommender systems.
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Click-Through Rate Prediction
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