Paper Citation Record · LEDGER

Explanation Design in Strategic Learning: Sufficient Explanations that Induce Non-harmful Responses

As of 11 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 0 inbound Pith citation observations for arXiv:2502.04058.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2502.04058 v2

Coverage vector

measured 47 of 47 reference resolution

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Pith citing papers itemized under the disclosed page cap.

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Reference resolution

47 of 47 outbound references displayed

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External citation measurements

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Outbound references

Observation 1b79c855-dc73-4501-b8ec-1b031534b097 · outbound

This paper cites The strategic perceptron.

Explanation Design in Strategic Learning: Sufficient Explanations that Induce Non-harmful Responses The strategic perceptron

Reference 1

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This paper cites Fundamental bounds on online strategic classifi- cation.

Explanation Design in Strategic Learning: Sufficient Explanations that Induce Non-harmful Responses Fundamental bounds on online strategic classifi- cation

Reference 2

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This paper cites Information discrepancy in strategic learning.

Explanation Design in Strategic Learning: Sufficient Explanations that Induce Non-harmful Responses Information discrepancy in strategic learning

Reference 3

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This paper cites Information design: A unified perspective.

Explanation Design in Strategic Learning: Sufficient Explanations that Induce Non-harmful Responses Information design: A unified perspective

Reference 4

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This paper cites Static prediction games for adversar- ial learning problems.

Explanation Design in Strategic Learning: Sufficient Explanations that Induce Non-harmful Responses Static prediction games for adversar- ial learning problems

Reference 5

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Observation c5fde00d-a1b6-491b-b650-f2d95d640983 · outbound

This paper cites Rkhs-shap: Shapley values for kernel methods.

Explanation Design in Strategic Learning: Sufficient Explanations that Induce Non-harmful Responses Rkhs-shap: Shapley values for kernel methods

Reference 6

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This paper cites Explaining the uncertain: Stochastic shapley values for gaussian process models.

Explanation Design in Strategic Learning: Sufficient Explanations that Induce Non-harmful Responses Explaining the uncertain: Stochastic shapley values for gaussian process models

Reference 7

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Observation 2bd4a4cc-8b1b-4b2a-bfa7-6c3c297ff59d · outbound

This paper cites Interpretable machine learning: A guide for making black box models explainable.

Explanation Design in Strategic Learning: Sufficient Explanations that Induce Non-harmful Responses Interpretable machine learning: A guide for making black box models explainable

Reference 8

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This paper cites Sequential strategic screening.

Explanation Design in Strategic Learning: Sufficient Explanations that Induce Non-harmful Responses Sequential strategic screening

Reference 9

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Observation 7e692bef-d9bc-4031-8fc7-56a2e82bbc11 · outbound

This paper cites Bayesian Strategic Classification.

Explanation Design in Strategic Learning: Sufficient Explanations that Induce Non-harmful Responses Bayesian Strategic Classification

Reference 10

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Observation 114dde4d-888b-4716-8e89-b432d278515f · outbound

This paper cites Council regulation (EU) no 679/2016, 2016.

Explanation Design in Strategic Learning: Sufficient Explanations that Induce Non-harmful Responses Council regulation (EU) no 679/2016, 2016

Reference 11

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Observation e3d947e0-45ab-4e34-be6c-9377fcaa7d0e · outbound

This paper cites Strategic classification from revealed preferences.

Explanation Design in Strategic Learning: Sufficient Explanations that Induce Non-harmful Responses Strategic classification from revealed preferences

Reference 12

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Observation 2805bcd7-8b2a-423f-9f03-5b3cabbd6324 · outbound

This paper cites Strategic classification in the dark.

Explanation Design in Strategic Learning: Sufficient Explanations that Induce Non-harmful Responses Strategic classification in the dark

Reference 13

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This paper cites right to explanation.

Explanation Design in Strategic Learning: Sufficient Explanations that Induce Non-harmful Responses right to explanation

Reference 14

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Observation a4fba312-782e-40ca-8aa5-873b37c7794f · outbound

This paper cites Calibrated stackelberg games: Learning optimal commitments against calibrated agents.

Explanation Design in Strategic Learning: Sufficient Explanations that Induce Non-harmful Responses Calibrated stackelberg games: Learning optimal commitments against calibrated agents

Reference 15

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This paper cites Strategic classifi- cation.

Explanation Design in Strategic Learning: Sufficient Explanations that Induce Non-harmful Responses Strategic classifi- cation

Reference 16

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This paper cites Stateful strategic regression.

Explanation Design in Strategic Learning: Sufficient Explanations that Induce Non-harmful Responses Stateful strategic regression

Reference 17

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This paper cites Bayesian persuasion for algorithmic recourse.Advances in Neural Information Processing Systems, 35:11131–11144, 2022.

Explanation Design in Strategic Learning: Sufficient Explanations that Induce Non-harmful Responses Bayesian persuasion for algorithmic recourse.Advances in Neural Information Processing Systems, 35:11131–11144, 2022

Reference 18

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Observation 5f4f3d12-fd12-40e8-8351-3abd5d878c3b · outbound

This paper cites Strategic instrumental variable regression: Recovering causal relationships from strategic responses.

Explanation Design in Strategic Learning: Sufficient Explanations that Induce Non-harmful Responses Strategic instrumental variable regression: Recovering causal relationships from strategic responses

Reference 19

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This paper cites Statlog (German Credit Data).

Explanation Design in Strategic Learning: Sufficient Explanations that Induce Non-harmful Responses Statlog (German Credit Data)

Reference 20

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This paper cites The Disparate Effects of Strategic Manipulation.

Explanation Design in Strategic Learning: Sufficient Explanations that Induce Non-harmful Responses The Disparate Effects of Strategic Manipulation

Reference 21

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This paper cites Alternative microfoundations for strategic classification.

Explanation Design in Strategic Learning: Sufficient Explanations that Induce Non-harmful Responses Alternative microfoundations for strategic classification

Reference 22

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Explanation Design in Strategic Learning: Sufficient Explanations that Induce Non-harmful Responses Bayesian persuasion

Reference 23

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This paper cites Algorithmic recourse: from counterfactual explanations to interventions.

Explanation Design in Strategic Learning: Sufficient Explanations that Induce Non-harmful Responses Algorithmic recourse: from counterfactual explanations to interventions

Reference 24

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This paper cites A survey of algorithmic recourse: contrastive explanations and consequential recommendations.

Explanation Design in Strategic Learning: Sufficient Explanations that Induce Non-harmful Responses A survey of algorithmic recourse: contrastive explanations and consequential recommendations

Reference 25

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This paper cites How do classifiers induce agents to invest effort strategi- cally? ACM Transactions on Economics and Computation (TEAC), 8(4):1–23, 2020.

Explanation Design in Strategic Learning: Sufficient Explanations that Induce Non-harmful Responses How do classifiers induce agents to invest effort strategi- cally? ACM Transactions on Economics and Computation (TEAC), 8(4):1–23, 2020

Reference 26

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This paper cites Strategic classification made practical.

Explanation Design in Strategic Learning: Sufficient Explanations that Induce Non-harmful Responses Strategic classification made practical

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This paper cites A Unified Approach to Interpreting Model Predictions.

Explanation Design in Strategic Learning: Sufficient Explanations that Induce Non-harmful Responses A Unified Approach to Interpreting Model Predictions

Reference 28

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Explanation Design in Strategic Learning: Sufficient Explanations that Induce Non-harmful Responses Strategic classification is causal modeling in disguise

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Explanation Design in Strategic Learning: Sufficient Explanations that Induce Non-harmful Responses The social cost of strategic classification

Reference 30

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Explanation Design in Strategic Learning: Sufficient Explanations that Induce Non-harmful Responses Interpretable machine learning

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Explanation Design in Strategic Learning: Sufficient Explanations that Induce Non-harmful Responses Performative prediction

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Explanation Design in Strategic Learning: Sufficient Explanations that Induce Non-harmful Responses why should i trust you?

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Explanation Design in Strategic Learning: Sufficient Explanations that Induce Non-harmful Responses From predictions to decisions: Using lookahead regularization

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Explanation Design in Strategic Learning: Sufficient Explanations that Induce Non-harmful Responses Meaningful information and the right to explanation

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Explanation Design in Strategic Learning: Sufficient Explanations that Induce Non-harmful Responses Strategic classification under unknown person- alized manipulation

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Explanation Design in Strategic Learning: Sufficient Explanations that Induce Non-harmful Responses Causal strategic linear regression

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Explanation Design in Strategic Learning: Sufficient Explanations that Induce Non-harmful Responses Pac-learning for strategic classifica- tion

Reference 38

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Explanation Design in Strategic Learning: Sufficient Explanations that Induce Non-harmful Responses Decisions, counterfactual explanations and strategic behavior

Reference 39

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Explanation Design in Strategic Learning: Sufficient Explanations that Induce Non-harmful Responses Causal strategic learning with competitive selection

Reference 40

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This paper cites Why a right to explanation of auto- mated decision-making does not exist in the general data protection regulation.

Explanation Design in Strategic Learning: Sufficient Explanations that Induce Non-harmful Responses Why a right to explanation of auto- mated decision-making does not exist in the general data protection regulation

Reference 41

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Explanation Design in Strategic Learning: Sufficient Explanations that Induce Non-harmful Responses Counterfactual explanations without opening the black box: Automated decisions and the gdpr

Reference 42

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Explanation Design in Strategic Learning: Sufficient Explanations that Induce Non-harmful Responses Non-linear Welfare-Aware Strategic Learning

Reference 43

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Observation c6b06ac7-91c3-4d4a-bc82-d413a73583a7 · outbound

This paper cites Learning under Imitative Strategic Behavior with Unforeseeable Outcomes.

Explanation Design in Strategic Learning: Sufficient Explanations that Induce Non-harmful Responses Learning under Imitative Strategic Behavior with Unforeseeable Outcomes

Reference 44

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Explanation Design in Strategic Learning: Sufficient Explanations that Induce Non-harmful Responses Modeling tabular data using conditional gan

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Explanation Design in Strategic Learning: Sufficient Explanations that Induce Non-harmful Responses Computational details

Reference 46

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This paper cites Then, we interact with the next 106 agents to collect another data setD2 ={ ¨xt,⃗ xt,wt, ∆⃗ gt}t∈[106].

Explanation Design in Strategic Learning: Sufficient Explanations that Induce Non-harmful Responses Then, we interact with the next 106 agents to collect another data setD2 ={ ¨xt,⃗ xt,wt, ∆⃗ gt}t∈[106]

Reference 47

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Pith citing papers

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