Demo Data from SIGIR 2026 / reviewers in the wild / expert
Zixin Gu
dblp:391/3761
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2026
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 first-author · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 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
1 paper |
Algorithmic game theory and mechanism design · 100% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Algorithmic game theory and mechanism design › mechanism design
auction design |
1.0 | 1 | 2026 | Fair Diffusion Auctions · AAAI 2026 |
Algorithmic game theory and mechanism design › auction theory › auction mechanism
diffusion auction |
1.0 | 1 | 2026 | Fair Diffusion Auctions · AAAI 2026 |
Algorithmic game theory and mechanism design › mechanism design
incentive compatibility |
0.3 | 1 | 2026 | Fair Diffusion Auctions · AAAI 2026 |
Methods — techniques the papers use, named apart from their topics
shapley value · 1.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | Fair Diffusion AuctionsabstractDiffusion auction design is a new trend in mechanism design which extends the original incentive compatibility property to include buyers' private connection report. Reporting connections is equivalent to inviting their neighbors to join the auction in practice. Then, the social welfare is collectively accumulated by all participants: reporting high valuations or inviting high-valuation neighbors. Hence, we can measure each participant's contribution by the marginal social welfare increase due to her participation. Therefore, in this paper, we introduce a new property called Shapley fairness to capture participants' social welfare contribution and use it as a benchmark to guide our auction design for a fairer utility allocation. Not surprisingly, none of the existing diffusion auctions has ever approximated the fairness, because Shapley fairness depends on each buyer's own valuation and this dependence can easily violate incentive compatibility. Thus, we combat this challenge by proposing a new diffusion auction called Permutation Diffusion Auction (PDA) for selling k homogeneous items, which is the first diffusion auction satisfying 1/(k+1)-Shapley fairness, incentive compatibility and individual rationality. Moreover, PDA can be extended to the general combinatorial auction setting where the literature did not discover meaningful diffusion auctions yet. Zixin Gu, Yaoxin Ge, Yao Zhang 0011, Dengji Zhao |
AAAI | 1 |