384 citations · 1.2k across the 32 of their papers we have counts for
8 papers · 1 filter
Achieving Human Parity on Visual Question Answering
Ming Yan, Haiyang Xu, Chenliang Li +14
The Visual Question Answering (VQA) task utilizes both visual image and language analysis to answer a textual question with respect to an image. It has been a popular research topi…
Improving Prosody for Unseen Texts in Speech Synthesis by Utilizing Linguistic Information and Noisy Data
Zhu Li, Yuqing Zhang, Mengxi Nie +4
Recent advancements in end-to-end speech synthesis have made it possible to generate highly natural speech. However, training these models typically requires a large amount of high…
Grid-VLP: Revisiting Grid Features for Vision-Language Pre-training
Ming Yan, Haiyang Xu, Chenliang Li +4
Existing approaches to vision-language pre-training (VLP) heavily rely on an object detector based on bounding boxes (regions), where salient objects are first detected from images…
ErrorCompensatedX: error compensation for variance reduced algorithms
Hanlin Tang, Yao Li, Ji Liu +1
Communication cost is one major bottleneck for the scalability for distributed learning. One approach to reduce the communication cost is to compress the gradient during communicat…
E2E-VLP: End-to-End Vision-Language Pre-training Enhanced by Visual Learning
Haiyang Xu, Ming Yan, Chenliang Li +4
Vision-language pre-training (VLP) on large-scale image-text pairs has achieved huge success for the cross-modal downstream tasks. The most existing pre-training methods mainly ado…
StructuralLM: Structural Pre-training for Form Understanding
Chenliang Li, Bin Bi, Ming Yan +4
Large pre-trained language models achieve state-of-the-art results when fine-tuned on downstream NLP tasks. However, they almost exclusively focus on text-only representation, whil…