Search Results for author:
Found 14 papers, 3 papers with code
Graph-Aware Language Model Pre-Training on a Large Graph Corpus Can Help Multiple Graph Applications
Model pre-training on large text corpora has been demonstrated effective for various downstream applications in the NLP domain.
Understanding and Constructing Latent Modality Structures in Multi-modal Representation Learning
Hence we advocate that the key of better performance lies in meaningful latent modality structures instead of perfect modality alignment.
A Multi-level Alignment Training Scheme for Video-and-Language Grounding
To solve video-and-language grounding tasks, the key is for the network to understand the connection between the two modalities.
Privacy Preserving Visual Question Answering
We introduce a novel privacy-preserving methodology for performing Visual Question Answering on the edge.
A Thousand Words Are Worth More Than a Picture: Natural Language-Centric Outside-Knowledge Visual Question Answering
Outside-knowledge visual question answering (OK-VQA) requires the agent to comprehend the image, make use of relevant knowledge from the entire web, and digest all the information to answer the question.
Transform-Retrieve-Generate: Natural Language-Centric Outside-Knowledge Visual Question Answering
Most previous works address the problem by first fusing the image and question in the multi-modal space, which is inflexible for further fusion with a vast amount of external knowledge.
Ranked #19 on
Visual Question Answering (VQA)
on OK-VQA
Learning Better Visual Dialog Agents with Pretrained Visual-Linguistic Representation
Most existing work for Guesser encode the dialog history as a whole and train the Guesser models from scratch on the GuessWhat?!
Interactive Teaching for Conversational AI
Current conversational AI systems aim to understand a set of pre-designed requests and execute related actions, which limits them to evolve naturally and adapt based on human interactions.
Adversarial Code Learning for Image Generation
We conduct the learning in an adversarial learning process, which bears a close resemblance to the original GAN but again shifts the learning from image spaces to prior and latent code spaces.
Convolutional Quantum-Like Language Model with Mutual-Attention for Product Rating Prediction
With the attention weights learned from the mutual-attention layer, final representations of a user and an item absorb information from both itself and its counterparts for making rating prediction.
Fashion-AttGAN: Attribute-Aware Fashion Editing with Multi-Objective GAN
In this paper, we introduce attribute-aware fashion-editing, a novel task, to the fashion domain.
Video Highlights Detection and Summarization with Lag-Calibration based on Concept-Emotion Mapping of Crowdsourced Time-Sync Comments
With the prevalence of video sharing, there are increasing demands for automatic video digestion such as highlight detection.
Video Highlights Detection and Summarization with Lag-Calibration based on Concept-Emotion Mapping of Crowd-sourced Time-Sync Comments
With the prevalence of video sharing, there are increasing demands for automatic video digestion such as highlight detection.
LitStoryTeller: An Interactive System for Visual Exploration of Scientific Papers Leveraging Named entities and Comparative Sentences
Such storylines help to preserve the semantic structure and logical thinking process of a scientific paper.
