We study the problem of fair sequential decision making given voter
preferences. In each round, a decision rule must choose a decision from a set
of alternatives where each voter reports which of these alternatives they
approve. Instead of going with the most popular choice in each round, we aim
for proportional representation. We formalize this aim using axioms based on
Proportional Justified Representation (PJR), which were proposed in the
literature on multi-winner voting and were recently adapted to multi-issue
decision making. The axioms require that every group of $\alpha\%$ of the
voters, if it agrees in every round (i.e., approves a common alternative), then
those voters must approve at least $\alpha\%$ of the decisions. A stronger
version of the axioms requires that every group of $\alpha\%$ of the voters
that agrees in a $\beta$ fraction of rounds must approve $\beta\cdot\alpha\%$
of the decisions. We show that three attractive voting rules satisfy axioms of
this style. One of them (Sequential Phragm\'en) makes its decisions online, and
the other two satisfy strengthened versions of the axioms but make decisions
semi-online (Method of Equal Shares) or fully offline (Proportional Approval
Voting). The first two are polynomial-time computable, and the latter is based
on an NP-hard optimization, but it admits a polynomial-time local search
algorithm that satisfies the same axiomatic properties. We present empirical
results about the performance of these rules based on synthetic data and U.S.
political elections. We also run experiments where votes are cast by preference
models trained on user responses from the moral machine dataset about ethical
dilemmas.

研究公平的顺序决策问题，提出了三种有吸引力的选举规则，证明它们确实满足基于比例正当理由的公理，包括基于 α 和 β 的增强版本，同时展示了它们在合成数据和美国政治选举中的性能。

序贯决策的比例聚合偏好

Proportional Aggregation of Preferences for Sequential Decision Making

Originally inspired by game-theory, path attribution framework stands out
among the post-hoc model interpretation tools due to its axiomatic nature.
However, recent developments show that this framework can still suffer from
counter-intuitive results. Moreover, specifically for deep visual models, the
existing path-based methods also fall short on conforming to the original
intuitions that are the basis of the claimed axiomatic properties of this
framework. We address these problems with a systematic investigation, and
pinpoint the conditions in which the counter-intuitive results can be avoided
for deep visual model interpretation with the path attribution strategy. We
also devise a scheme to preclude the conditions in which visual model
interpretation can invalidate the axiomatic properties of path attribution.
These insights are combined into a method that enables reliable visual model
interpretation. Our findings are establish empirically with multiple datasets,
models and evaluation metrics. Extensive experiments show a consistent
performance gain of our method over the baselines.

通过系统的研究，我们发现了适用于深度视觉模型的路径归因策略的反直觉结果的条件以及使其不失公理性质的方案，进而提出了一种可靠的视觉模型解释方法并在多个数据集、模型和评估指标上进行了实证验证，表现出与基准方法相比的一致性性能增益。

通过路径归因实现可信的视觉模型解释

Towards credible visual model interpretation with path attribution

The important Kemeny problem, which consists of computing median consensus
rankings of an election with respect to the Kemeny voting rule, admits
important applications in biology and computational social choice and was
generalized recently via an interesting setwise approach by Gilbert et. al. Our
first results establish optimal quantitative extensions of the Unanimity
property and the well-known $3/4$-majority rule of Betzler et al. for the
classical Kemeny median problem. Moreover, by elaborating an exhaustive list of
quantified axiomatic properties (such as the Condorcet and Smith criteria, the
$5/6$-majority rule, etc.) of the $3$-wise Kemeny rule where not only pairwise
comparisons but also the discordance between the winners of subsets of three
candidates are also taken into account, we come to the conclusion that the
$3$-wise Kemeny voting scheme induced by the $3$-wise Kendall-tau distance
presents interesting advantages in comparison with the classical Kemeny rule.
For example, it satisfies several improved manipulation-proof properties. Since
the $3$-wise Kemeny problem is NP-hard, our results also provide some of the
first useful space reduction techniques by determining the relative orders of
pairs of alternatives. Our works suggest similar interesting properties of
higher setwise Kemeny voting schemes which justify and compensate for the more
expensive computational cost than the classical Kemeny scheme.

该论文研究了基于 Kemeny 规则的选举中位数共识排名问题，并通过详细说明各种相对排序的实际应用，提出了解决 $3$-wise Kemeny 问题的一些技术方法，使得该问题具有了许多重要的性质和应用。

集合型 Kemeny 投票方案的最优多数规则和数量化的 Condorcet 特性

Optimal majority rules and quantitative Condorcet properties of setwise  Kemeny voting schemes

We define and study a general framework for approval-based budgeting methods
and compare certain methods within this framework by their axiomatic and
computational properties. Furthermore, we visualize their behavior on certain
Euclidean distributions and analyze them experimentally.

研究批准制预算方法的一般框架，通过公理和计算属性比较了 certain 方法，对其在特定欧几里得分布上的行为进行了可视化和实验分析。