activity
20202022
most citedUNIMO: Towards Unified-Modal Understanding and Generation via Cross-Modal Contrastive Learning

32 citations · 124 across the 14 of their papers we have counts for

collaborators

14 papers

cs.CV2022★ 11 cited

UPainting: Unified Text-to-Image Diffusion Generation with Cross-modal Guidance

Wei Li, Xue Xu, Xinyan Xiao +8

Diffusion generative models have recently greatly improved the power of text-conditioned image generation. Existing image generation models mainly include text conditional diffusio…

cs.CL2022★ 2 cited

FRSUM: Towards Faithful Abstractive Summarization via Enhancing Factual Robustness

Wenhao Wu, Wei Li, Jiachen Liu +4

Despite being able to generate fluent and grammatical text, current Seq2Seq summarization models still suffering from the unfaithful generation problem. In this paper, we study the…

cs.CL2022

Precisely the Point: Adversarial Augmentations for Faithful and Informative Text Generation

Wenhao Wu, Wei Li, Jiachen Liu +3

Though model robustness has been extensively studied in language understanding, the robustness of Seq2Seq generation remains understudied. In this paper, we conduct the first quant…

cs.AI2022★ 3 cited

HiSMatch: Historical Structure Matching based Temporal Knowledge Graph Reasoning

Zixuan Li, Zhongni Hou, Saiping Guan +7

A Temporal Knowledge Graph (TKG) is a sequence of KGs with respective timestamps, which adopts quadruples in the form of (\emph{subject}, \emph{relation}, \emph{object}, \emph{time…

cs.AI2022★ 8 cited

Complex Evolutional Pattern Learning for Temporal Knowledge Graph Reasoning

Zixuan Li, Saiping Guan, Xiaolong Jin +7

A Temporal Knowledge Graph (TKG) is a sequence of KGs corresponding to different timestamps. TKG reasoning aims to predict potential facts in the future given the historical KG seq…

cs.CV2022★ 2 cited

UNIMO-2: End-to-End Unified Vision-Language Grounded Learning

Wei Li, Can Gao, Guocheng Niu +5

Vision-Language Pre-training (VLP) has achieved impressive performance on various cross-modal downstream tasks. However, most existing methods can only learn from aligned image-cap…