activity
20182024
most citedET-BERT: A Contextualized Datagram Representation with Pre-training Transformers for Encrypted Traffic Classification

550 citations · 806 across the 20 of their papers we have counts for

collaborators
Showing 2020Show all

7 papers · 1 filter

cs.LG2020

End-to-End Learning and Intervention in Games

Jiayang Li, Jing Yu, Yu Marco Nie +1

In a social system, the self-interest of agents can be detrimental to the collective good, sometimes leading to social dilemmas. To resolve such a conflict, a central designer may…

eess.SY2020★ 3 cited

Localized and Distributed H2 State Feedback Control

Jing Yu, Yuh-Shyang Wang, James Anderson

Distributed linear control design is crucial for large-scale cyber-physical systems. It is generally desirable to both impose information exchange (communication) constraints on th…

cs.CV2020★ 7 cited

CogTree: Cognition Tree Loss for Unbiased Scene Graph Generation

Jing Yu, Yuan Chai, Yujing Wang +2

Scene graphs are semantic abstraction of images that encourage visual understanding and reasoning. However, the performance of Scene Graph Generation (SGG) is unsatisfactory when f…

cs.AI2020★ 116 cited

Cross-modal Knowledge Reasoning for Knowledge-based Visual Question Answering

Jing Yu, Zihao Zhu, Yujing Wang +3

Knowledge-based Visual Question Answering (KVQA) requires external knowledge beyond the visible content to answer questions about an image. This ability is challenging but indispen…

cs.CV2020★ 2 cited

KBGN: Knowledge-Bridge Graph Network for Adaptive Vision-Text Reasoning in Visual Dialogue

Xiaoze Jiang, Siyi Du, Zengchang Qin +2

Visual dialogue is a challenging task that needs to extract implicit information from both visual (image) and textual (dialogue history) contexts. Classical approaches pay more att…

cs.CV2020

DAM: Deliberation, Abandon and Memory Networks for Generating Detailed and Non-repetitive Responses in Visual Dialogue

Xiaoze Jiang, Jing Yu, Yajing Sun +4

Visual Dialogue task requires an agent to be engaged in a conversation with human about an image. The ability of generating detailed and non-repetitive responses is crucial for the…

cs.CV2020★ 20 cited

Mucko: Multi-Layer Cross-Modal Knowledge Reasoning for Fact-based Visual Question Answering

Zihao Zhu, Jing Yu, Yujing Wang +3

Fact-based Visual Question Answering (FVQA) requires external knowledge beyond visible content to answer questions about an image, which is challenging but indispensable to achieve…