Demo Data from VLDB 2026 / reviewers in the wild / expert
Xiuzhen Zhang 0002
dblp:20/2941-2
· DBLP profile ↗
5ranked-venue papers
2as first author
4since 2021 · last 2023
0000-0001-7772-999XORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 4 · 1 first-author · 3 since 2021Graphics, computer vision, multimedia, augmented reality and games · 2 · 1 since 2021Theory of computation · 1 · 1 first-author · 1 since 2021Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Theoretical computer science
2 papers |
Algorithmic game theory and mechanism design · 100% | |
| Human-computer interaction and pervasive computing
1 paper |
Collaborative and social computing · 100% | |
| Artificial intelligence
1 paper |
Question answering and dialogue systems · 100% |
Topics — the 5 heaviest of 6, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Algorithmic game theory and mechanism design
mechanism design |
1.1 | 2 | 2023 | Task Allocation on Networks with Execution Uncertainty (Extended Abstract)∗ · IJCAI 2023 Sybil-proof Answer Querying Mechanism · IJCAI 2020 |
Algorithmic game theory and mechanism design › resource allocation
task allocation |
0.7 | 1 | 2023 | Task Allocation on Networks with Execution Uncertainty (Extended Abstract)∗ · IJCAI 2023 |
Algorithmic game theory and mechanism design › mechanism design › incentive mechanism design
reward mechanisms |
0.4 | 1 | 2020 | Sybil-proof Answer Querying Mechanism · IJCAI 2020 |
Algorithmic game theory and mechanism design › mechanism design
sybil-proof mechanisms |
0.4 | 1 | 2020 | Sybil-proof Answer Querying Mechanism · IJCAI 2020 |
Collaborative and social computing
crowdsourcing |
0.2 | 1 | 2023 | Task Allocation on Networks with Execution Uncertainty (Extended Abstract)∗ · IJCAI 2023 |
Methods — techniques the papers use, named apart from their topics
mechanism design · 2.2dominant strategy · 1.3incentive compatibility · 0.9
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | Task Allocation on Networks with Execution Uncertainty (Extended Abstract)∗abstractWe study a single task allocation problem where each worker connects to some other workers to form a network and the task requester only connects to some of the workers. The goal is to design an allocation mechanism such that each worker is incentivized to invite her neighbours to join the allocation, although they are competing for the task. Moreover, the performance of each worker is uncertain, which is modelled as the quality level of her task execution. The literature has proposed solutions to tackle the uncertainty problem by paying them after verifying their execution. Here, we extend the problem to the network setting. We propose a new mechanism that guarantees that inviting more workers and reporting/performing according to her true ability is a dominant strategy for each worker. We believe that the new solution can be widely applied in the digital economy powered by social connections such as crowdsourcing. Yao Zhang 0011, Xiuzhen Zhang 0002, Dengji Zhao |
IJCAI | 2 |
| 2022 | Maximal Information Propagation with Limited Resources
Xu Ge, Xiuzhen Zhang 0002, Dengji Zhao |
DAI | 2 |
| 2022 | Task Allocation on Networks with Execution Uncertainty
Xiuzhen Zhang 0002, Yao Zhang 0011, Dengji Zhao |
PRIMA | 1 |
| 2021 | Incentive Compatible Mechanism for Influential Agent Selection
Xiuzhen Zhang 0002, Yao Zhang 0011, Dengji Zhao |
SAGT | 1 |
| 2020 | Sybil-proof Answer Querying MechanismabstractWe study a question answering problem on a social network, where a requester is seeking an answer from the agents on the network. The goal is to design reward mechanisms to incentivize the agents to propagate the requester's query to their neighbours if they don't have the answer. Existing mechanisms are vulnerable to Sybil-attacks, i.e., an agent may get more reward by creating fake identities. Hence, we combat this problem by first proving some impossibility results to resolve Sybil-attacks and then characterizing a class of mechanisms which satisfy Sybil-proofness (prevents Sybil-attacks) as well as other desirable properties. Except for Sybil-proofness, we also consider cost minimization for the requester and agents' collusions. Yao Zhang 0011, Xiuzhen Zhang 0002, Dengji Zhao |
IJCAI | 2 |