169 citations · 349 across the 11 of their papers we have counts for
12 papers
SegCLIP: Patch Aggregation with Learnable Centers for Open-Vocabulary Semantic Segmentation
Huaishao Luo, Junwei Bao, Youzheng Wu +2
Recently, the contrastive language-image pre-training, e.g., CLIP, has demonstrated promising results on various downstream tasks. The pre-trained model can capture enriched visual…
CSS: Combining Self-training and Self-supervised Learning for Few-shot Dialogue State Tracking
Haoning Zhang, Junwei Bao, Haipeng Sun +3
Few-shot dialogue state tracking (DST) is a realistic problem that trains the DST model with limited labeled data. Existing few-shot methods mainly transfer knowledge learned from…
ScaleVLAD: Improving Multimodal Sentiment Analysis via Multi-Scale Fusion of Locally Descriptors
Huaishao Luo, Lei Ji, Yanyong Huang +3
Fusion technique is a key research topic in multimodal sentiment analysis. The recent attention-based fusion demonstrates advances over simple operation-based fusion. However, thes…
GEM: A General Evaluation Benchmark for Multimodal Tasks
Lin Su, Nan Duan, Edward Cui +7
In this paper, we present GEM as a General Evaluation benchmark for Multimodal tasks. Different from existing datasets such as GLUE, SuperGLUE, XGLUE and XTREME that mainly focus o…
CLIP4Clip: An Empirical Study of CLIP for End to End Video Clip Retrieval
Huaishao Luo, Lei Ji, Ming Zhong +4
Video-text retrieval plays an essential role in multi-modal research and has been widely used in many real-world web applications. The CLIP (Contrastive Language-Image Pre-training…
MaP: A Matrix-based Prediction Approach to Improve Span Extraction in Machine Reading Comprehension
Huaishao Luo, Yu Shi, Ming Gong +2
Span extraction is an essential problem in machine reading comprehension. Most of the existing algorithms predict the start and end positions of an answer span in the given corresp…
GRACE: Gradient Harmonized and Cascaded Labeling for Aspect-based Sentiment Analysis
Huaishao Luo, Lei Ji, Tianrui Li +2
In this paper, we focus on the imbalance issue, which is rarely studied in aspect term extraction and aspect sentiment classification when regarding them as sequence labeling tasks…
ReAD: A Regional Anomaly Detection Framework Based on Dynamic Partition
Huaishao Luo, Chuishi Meng, Bowen Wu +3
The detection of the abnormal area from urban data is a significant research problem. However, to the best of our knowledge, previous methods designed on spatio-temporal anomalies…
UniVL: A Unified Video and Language Pre-Training Model for Multimodal Understanding and Generation
Huaishao Luo, Lei Ji, Botian Shi +6
With the recent success of the pre-training technique for NLP and image-linguistic tasks, some video-linguistic pre-training works are gradually developed to improve video-text rel…
DOER: Dual Cross-Shared RNN for Aspect Term-Polarity Co-Extraction
Huaishao Luo, Tianrui Li, Bing Liu +1
This paper focuses on two related subtasks of aspect-based sentiment analysis, namely aspect term extraction and aspect sentiment classification, which we call aspect term-polarity…
Deep Uncertainty Quantification: A Machine Learning Approach for Weather Forecasting
Bin Wang, Jie Lu, Zheng Yan +4
Weather forecasting is usually solved through numerical weather prediction (NWP), which can sometimes lead to unsatisfactory performance due to inappropriate setting of the initial…
Improving Aspect Term Extraction with Bidirectional Dependency Tree Representation
Huaishao Luo, Tianrui Li, Bing Liu +2
Aspect term extraction is one of the important subtasks in aspect-based sentiment analysis. Previous studies have shown that using dependency tree structure representation is promi…