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11/27/2022
SegCLIP: Patch Aggregation with Learnable Centers for Open-Vocabulary Semantic Segmentation
Recently, the contrastive language-image pre-training, e.g., CLIP, has d...
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10/11/2022
CSS: Combining Self-training and Self-supervised Learning for Few-shot Dialogue State Tracking
Few-shot dialogue state tracking (DST) is a realistic problem that train...
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12/02/2021
ScaleVLAD: Improving Multimodal Sentiment Analysis via Multi-Scale Fusion of Locally Descriptors
Fusion technique is a key research topic in multimodal sentiment analysi...
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06/18/2021
GEM: A General Evaluation Benchmark for Multimodal Tasks
In this paper, we present GEM as a General Evaluation benchmark for Mult...
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04/18/2021
CLIP4Clip: An Empirical Study of CLIP for End to End Video Clip Retrieval
Video-text retrieval plays an essential role in multi-modal research and...
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09/29/2020
MaP: A Matrix-based Prediction Approach to Improve Span Extraction in Machine Reading Comprehension
Span extraction is an essential problem in machine reading comprehension...
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09/22/2020
GRACE: Gradient Harmonized and Cascaded Labeling for Aspect-based Sentiment Analysis
In this paper, we focus on the imbalance issue, which is rarely studied ...
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02/15/2020
UniViLM: A Unified Video and Language Pre-Training Model for Multimodal Understanding and Generation
We propose UniViLM: a Unified Video and Language pre-training Model for ...
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06/05/2019
DOER: Dual Cross-Shared RNN for Aspect Term-Polarity Co-Extraction
This paper focuses on two related subtasks of aspect-based sentiment ana...
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12/22/2018
Deep Uncertainty Learning: A Machine Learning Approach for Weather Forecasting
This paper uses the weather forecasting as an application background to ...
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12/22/2018
Deep Prediction Interval for Weather Forecasting
Currently there exists a gap between deep learning and the techniques re...
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05/21/2018