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Found 12 papers, 1 papers with code
Adversarial Semantic Decoupling for Recognizing Open-Vocabulary Slots
Open-vocabulary slots, such as file name, album name, or schedule title, significantly degrade the performance of neural-based slot filling models since these slots can take on values from a virtually unlimited set and have no semantic restriction nor a length limit.
Look, Listen, and Answer: Overcoming Biases for Audio-Visual Question Answering
The former leads to a large, diverse test space, while the latter results in a comprehensive robustness evaluation on rare, frequent, and overall questions.
Audio-visual Question Answering
Audio-Visual Question Answering (AVQA)
+3
AR Visualization System for Ship Detection and Recognition Based on AI
The combination of artificial intelligence and augmented reality technology has also become a future development trend.
Adaptive loose optimization for robust question answering
Question answering methods are well-known for leveraging data bias, such as the language prior in visual question answering and the position bias in machine reading comprehension (extractive question answering).
Extractive Question-Answering
Machine Reading Comprehension
+2
Futures Quantitative Investment with Heterogeneous Continual Graph Neural Network
This study aims to address the challenges of futures price prediction in high-frequency trading (HFT) by proposing a continuous learning factor predictor based on graph neural networks.
Speaker Change Detection for Transformer Transducer ASR
Speaker change detection (SCD) is an important feature that improves the readability of the recognized words from an automatic speech recognition (ASR) system by breaking the word sequence into paragraphs at speaker change points.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Robust Anomaly Detection for Time-series Data
The experiments showed that in benchmark datasets RADTD possessed higher accuracy and robustness than recurrence qualification analysis and extreme learning machine autoencoder, respectively, and that RADTD accurately detected the occurrence of tunneling settlement accidents, indicating its remarkable performance in accuracy and robustness.
A structure-enhanced graph convolutional network for sentiment analysis
Syntactic information is essential for both sentiment analysis(SA) and aspect-based sentiment analysis(ABSA).
Aspect-Based Sentiment Analysis
Aspect-Based Sentiment Analysis (ABSA)
+2
Meta-Reinforced Multi-Domain State Generator for Dialogue Systems
The state-of-the-art accuracy for DST is below 50{\%} for a multi-domain dialogue task.
Lossless Attention in Convolutional Networks for Facial Expression Recognition in the Wild
And we validate our method on the Aff-Wild2 datasets released by the Challenge.
Facial Expression Recognition
Facial Expression Recognition (FER)
Two-level Attention with Two-stage Multi-task Learning for Facial Emotion Recognition
In this paper, a two-level attention with two-stage multi-task learning (2Att-2Mt) framework is proposed for facial emotion estimation on only static images.
