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Paper Citation Record · LEDGER

Learning Truthful Mechanisms without Discretization

As of 7 August 2026, this Paper Citation Record lists 100 of 136 outbound references and 0 inbound Pith citation observations for arXiv:2506.22911.

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

pith.paper-citation-record.v1
2506.22911 v1

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measured 100 of 136 reference resolution

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Reference resolution

100 of 136 outbound references displayed

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Outbound references

Observation 57102e47-07a0-4150-8eb0-e73ed813ea3f · outbound

This paper cites Towards data auctions with externalities.

Learning Truthful Mechanisms without Discretization Towards data auctions with externalities

Reference 1

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Observation 9933a6d4-892f-4799-86d6-1176d1d1c0df · outbound

This paper cites Automated design of robust mecha- nisms.

Learning Truthful Mechanisms without Discretization Automated design of robust mecha- nisms

Reference 2

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Observation e04777cb-c2ce-4239-9eb0-fe2f499edff1 · outbound

This paper cites Backpropagation and stochastic gradient descent method.

Learning Truthful Mechanisms without Discretization Backpropagation and stochastic gradient descent method

Reference 3

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Observation 27f2512e-4196-4d47-a2e8-3b638cc35e98 · outbound

This paper cites Input convex neural networks.

Learning Truthful Mechanisms without Discretization Input convex neural networks

Reference 4

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Observation 5031d63b-1d47-4060-ae5c-ccfc2b3b9abd · outbound

This paper cites Near-optimal max-affine estimators for convex regression.

Learning Truthful Mechanisms without Discretization Near-optimal max-affine estimators for convex regression

Reference 5

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Observation 8553bc7d-2a80-4436-a6cf-61a9501db2a9 · outbound

This paper cites Sample complexity of automated mechanism design.

Learning Truthful Mechanisms without Discretization Sample complexity of automated mechanism design

Reference 6

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Observation 109808fa-8a06-40e7-9045-fb8d3d6ba908 · outbound

This paper cites MAC advice for facility loca- tion mechanism design.

Learning Truthful Mechanisms without Discretization MAC advice for facility loca- tion mechanism design

Reference 7

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Observation 2a448ba1-bc40-4b43-a573-dda93216307d · outbound

This paper cites Universal approximation bounds for superpositions of a sigmoidal func- tion.

Learning Truthful Mechanisms without Discretization Universal approximation bounds for superpositions of a sigmoidal func- tion

Reference 8

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Observation f65c3bde-f4cd-403b-add1-4002e1c19551 · outbound

This paper cites Dynamic programming.

Learning Truthful Mechanisms without Discretization Dynamic programming

Reference 9

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Observation d953f4b1-0dd5-4c79-9876-9989801436de · outbound

This paper cites The curse of highly variable functions for local kernel machines.

Learning Truthful Mechanisms without Discretization The curse of highly variable functions for local kernel machines

Reference 10

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Observation e1183996-5e50-488f-864d-c615b7cb428c · outbound

This paper cites Methodology for Designing Reasonably Expressive Mechanisms with Application to Ad Auctions.

Learning Truthful Mechanisms without Discretization Methodology for Designing Reasonably Expressive Mechanisms with Application to Ad Auctions

Reference 11

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Observation e4e44873-e310-4d4e-b341-be7af078900c · outbound

This paper cites Welfare and profit maximization with production costs.

Learning Truthful Mechanisms without Discretization Welfare and profit maximization with production costs

Reference 12

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Observation 91a7bd91-eeb2-4b90-bce6-4db9e5840b61 · outbound

This paper cites Large-scale machine learning with stochastic gradient descent.

Learning Truthful Mechanisms without Discretization Large-scale machine learning with stochastic gradient descent

Reference 13

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Observation a268b65a-2737-4803-923b-0480759fab43 · outbound

This paper cites Convex optimization.

Learning Truthful Mechanisms without Discretization Convex optimization

Reference 14

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Observation 77f8dc4a-f05d-4cbc-936d-bedddeb73354 · outbound

This paper cites An Introduction to the Theory of Mechanism Design.

Learning Truthful Mechanisms without Discretization An Introduction to the Theory of Mechanism Design

Reference 15

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Observation dfed6679-c798-470e-a0fa-d9e12598583c · outbound

This paper cites Optimal multi-dimensional mechanism design: Reducing revenue to welfare maximization.

Learning Truthful Mechanisms without Discretization Optimal multi-dimensional mechanism design: Reducing revenue to welfare maximization

Reference 16

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Observation 2600b9bb-d826-4f35-a4b8-65c1de008c94 · outbound

This paper cites Log-sum-exp neural net- works and posynomial models for convex and log-log-convex data.

Learning Truthful Mechanisms without Discretization Log-sum-exp neural net- works and posynomial models for convex and log-log-convex data

Reference 17

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Observation 83ee5b39-2457-4835-b4bd-7a3e02fa8e76 · outbound

This paper cites Truthful implementation and preference aggregation in restricted domains.

Learning Truthful Mechanisms without Discretization Truthful implementation and preference aggregation in restricted domains

Reference 18

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Observation 26e51296-4403-45eb-be76-3b432c48ae5a · outbound

This paper cites Mechanism Design for Facility Location Problem: A Survey.

Learning Truthful Mechanisms without Discretization Mechanism Design for Facility Location Problem: A Survey

Reference 19

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Observation 4cb9130e-c0d3-4f25-8b56-daf5ce4dbf21 · outbound

This paper cites Optimal competitive auctions.

Learning Truthful Mechanisms without Discretization Optimal competitive auctions

Reference 20

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Observation 275b6d4c-3646-4ed6-a04c-d72eee03310a · outbound

This paper cites The complexity of optimal multidimensional pricing.

Learning Truthful Mechanisms without Discretization The complexity of optimal multidimensional pricing

Reference 21

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Observation 55ce1b74-2f13-484f-afc0-3c207d50aa03 · outbound

This paper cites Strategy-proofness and “median voters.

Learning Truthful Mechanisms without Discretization Strategy-proofness and “median voters

Reference 22

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Observation b1fd6a1c-c126-4930-aa9c-ba6a4d72022c · outbound

This paper cites Multipart pricing of public goods.

Learning Truthful Mechanisms without Discretization Multipart pricing of public goods

Reference 23

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Observation 01c0499f-e87b-4c8b-96d8-aa4199122453 · outbound

This paper cites Incremental mechanism design.

Learning Truthful Mechanisms without Discretization Incremental mechanism design

Reference 24

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Observation b76e8258-4412-4a13-adc5-8924536a4684 · outbound

This paper cites Differentiable economics for ran- domized affine maximizer auctions.

Learning Truthful Mechanisms without Discretization Differentiable economics for ran- domized affine maximizer auctions

Reference 25

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Observation f0e9e74b-79ab-4245-b973-2e161f84e9b3 · outbound

This paper cites Automated design of affine maximizer mechanisms in dynamic set- tings.

Learning Truthful Mechanisms without Discretization Automated design of affine maximizer mechanisms in dynamic set- tings

Reference 26

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Observation 5613cbca-513d-4b88-8b74-d0e13ce3cba1 · outbound

This paper cites Certifying strategyproof auction networks.

Learning Truthful Mechanisms without Discretization Certifying strategyproof auction networks

Reference 27

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Observation 7588f277-fe1b-430a-ad32-3d5119eb6689 · outbound

This paper cites Optimal Automated Market Makers: Differentiable Economics and Strong Duality.

Learning Truthful Mechanisms without Discretization Optimal Automated Market Makers: Differentiable Economics and Strong Duality

Reference 28

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Observation 7a6a0215-c7fb-4f2a-9b89-9d0434edc277 · outbound

This paper cites Learning revenue-maximizing auctions with differentiable matching.

Learning Truthful Mechanisms without Discretization Learning revenue-maximizing auctions with differentiable matching

Reference 29

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Observation 42c4d617-3a1b-463f-8413-df0558621710 · outbound

This paper cites Approximation by superpositions of a sigmoidal function.

Learning Truthful Mechanisms without Discretization Approximation by superpositions of a sigmoidal function

Reference 30

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Observation 76620333-305d-4373-adb3-29141635fb82 · outbound

This paper cites Strong duality for a multiple-good monopolist.

Learning Truthful Mechanisms without Discretization Strong duality for a multiple-good monopolist

Reference 31

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Observation e987b88f-bc1b-4c00-90fd-52b24a4b26fc · outbound

This paper cites Identifying and attacking the saddle point problem in high-dimensional non-convex optimization.

Learning Truthful Mechanisms without Discretization Identifying and attacking the saddle point problem in high-dimensional non-convex optimization

Reference 32

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Observation 5febc184-bc6a-48e4-ac69-01484fdfa0eb · outbound

This paper cites Continuity properties of Paretian utility.

Learning Truthful Mechanisms without Discretization Continuity properties of Paretian utility

Reference 33

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Observation 53a96779-0ea2-4f5e-a62a-5df93b8c06ca · outbound

This paper cites Procurement Auctions via Approximately Optimal Submodular Optimization.

Learning Truthful Mechanisms without Discretization Procurement Auctions via Approximately Optimal Submodular Optimization

Reference 34

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Observation c07f3f6d-e474-47af-a2d0-4bfb2607c753 · outbound

This paper cites A context-integrated transformer-based neural network for auction design.

Learning Truthful Mechanisms without Discretization A context-integrated transformer-based neural network for auction design

Reference 35

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Observation 59b4249d-e197-4cbc-97e2-c298546c9a81 · outbound

This paper cites A scalable neural network for DSIC affine maximizer auction design.

Learning Truthful Mechanisms without Discretization A scalable neural network for DSIC affine maximizer auction design

Reference 36

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Observation e1831598-7d6a-4973-8bf6-5e3c3d231c81 · outbound

This paper cites Mechanism design for large language models.

Learning Truthful Mechanisms without Discretization Mechanism design for large language models

Reference 37

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Observation 5bb7bc22-329b-4af5-9955-cbcbd679854f · outbound

This paper cites Deep Reinforcement Learning in Large Discrete Action Spaces.

Learning Truthful Mechanisms without Discretization Deep Reinforcement Learning in Large Discrete Action Spaces

Reference 38

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Observation d546b0d9-6032-477a-bca6-82cbeb7e0c03 · outbound

This paper cites Optimal auctions through deep learning.

Learning Truthful Mechanisms without Discretization Optimal auctions through deep learning

Reference 39

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Observation 97a7b71f-2bc1-4e33-9d7c-14f1a296e33a · outbound

This paper cites Optimal auctions through deep learning: Advances in differentiable economics.

Learning Truthful Mechanisms without Discretization Optimal auctions through deep learning: Advances in differentiable economics

Reference 40

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source=pdf_text observed=2026-08-06T22:03:21.549822Z digest=sha256:f9ca174b7f1cfcde01b0edd14db540d40f83c0f5659f9cd7d80eb3196be64295

Observation a60fa36e-4ebe-4c74-9521-8f9a523d43d3 · outbound

This paper cites Reverse Auction Relinquishing Broadcast Spectrum Rights.

Learning Truthful Mechanisms without Discretization Reverse Auction Relinquishing Broadcast Spectrum Rights

Reference 41

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source=pdf_text observed=2026-08-06T22:03:21.659417Z digest=sha256:d7c85025814e194b21a24fe6e1a59c9cdaf7b35db31076f177d3add1be98b0eb

Observation 314d7992-7345-49b6-8d83-d00c9eaf0c1c · outbound

This paper cites College admissions and the stability of marriage.

Learning Truthful Mechanisms without Discretization College admissions and the stability of marriage

Reference 42

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source=pdf_text observed=2026-08-06T22:03:21.693297Z digest=sha256:626eccd8ef18cee61dd1d51b90724e4516ecdff77dc57666454f671ec25f5522

Observation 13352a68-0fef-48ae-8a52-170c61b4fdb8 · outbound

This paper cites Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images.

Learning Truthful Mechanisms without Discretization Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images

Reference 43

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source=pdf_text observed=2026-08-06T22:03:21.800313Z digest=sha256:fe9ac3759eb920d5efb4dd054a74a07efc76ececea55a0bc58617139f6d4fdbc

Observation f4752200-7fb1-4a3b-9de7-49d4f04aba6c · outbound

This paper cites Reverse auctions are different from auctions.

Learning Truthful Mechanisms without Discretization Reverse auctions are different from auctions

Reference 44

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malformed identifier
no resolver link, observed 2026-08-06T22:03:21.873613Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T22:03:21.873613Z digest=sha256:534724b9c76f82a8e1a5270ae738a53d6538aa6f380634a21f0493e75ef9b844

Observation b4ef0632-2829-4f5b-a63a-6bb49d99a0f8 · outbound

This paper cites Duality and optimality of auctions for uniform distributions.

Learning Truthful Mechanisms without Discretization Duality and optimality of auctions for uniform distributions

Reference 45

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source=pdf_text observed=2026-08-06T22:03:21.977981Z digest=sha256:e707d662bf087522b1cfb5f3d2626a98ae40f75f3f29b2aba151563ce6ab1a1c

Observation e7414f70-2694-49ea-837c-15fdf3deb8f1 · outbound

This paper cites Manipulation of voting schemes: a general result.

Learning Truthful Mechanisms without Discretization Manipulation of voting schemes: a general result

Reference 46

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source=pdf_text observed=2026-08-06T22:03:22.053658Z digest=sha256:59ac9381a8078c8ae089de5e96d420976bab7ccddc8ad8caad9757a654ffa425

Observation 4f6ccd96-8f13-46aa-a718-e21bcd3f6e4d · outbound

This paper cites Competitive auctions for multiple digital goods.

Learning Truthful Mechanisms without Discretization Competitive auctions for multiple digital goods

Reference 47

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source=pdf_text observed=2026-08-06T22:03:22.141193Z digest=sha256:2e09ca365cbde5d03430123d90559c8a912de09940cc229ed47effd25bded11f

Observation d14259cb-9f59-43cb-b941-dd063be670ac · outbound

This paper cites A lower bound on the competitive ratio of truthful auctions.

Learning Truthful Mechanisms without Discretization A lower bound on the competitive ratio of truthful auctions

Reference 48

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source=pdf_text observed=2026-08-06T22:03:22.234620Z digest=sha256:834070a2328642c28cf7e0e14b3de5c3a663981acbdc70e51e6eefb676f3a20a

Observation 3bdab74b-647e-45b8-afdd-e110217df94f · outbound

This paper cites Deep learning for multi- facility location mechanism design.

Learning Truthful Mechanisms without Discretization Deep learning for multi- facility location mechanism design

Reference 49

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source=pdf_text observed=2026-08-06T22:03:22.347124Z digest=sha256:5f536febf980849619bef92e6de30d8f118617be1a0bee4cff11893d9885d243

Observation 5258b0e7-45c0-4eae-8435-5a85d04d4104 · outbound

This paper cites Deep Learning.

Learning Truthful Mechanisms without Discretization Deep Learning

Reference 50

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:03:22.436303Z digest=sha256:aaca8d8cd8d4fd549817a9eece8708067b5f341430ff24299916d6ada3532d40

Observation 430a34aa-c9f5-40f1-aa13-124151e7bb41 · outbound

This paper cites Approximation guarantees of Median Mechanism in Rd.

Learning Truthful Mechanisms without Discretization Approximation guarantees of Median Mechanism in Rd

Reference 51

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source=pdf_text observed=2026-08-06T22:03:22.507627Z digest=sha256:f49a223d3515fd79778875d613ff822454d8e6c5a10cbe7b4da290f0da055940

Observation f63f7dfb-eb01-40bf-9a17-dab415e51199 · outbound

This paper cites Incentives in teams.

Learning Truthful Mechanisms without Discretization Incentives in teams

Reference 52

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source=pdf_text observed=2026-08-06T22:03:22.617858Z digest=sha256:36d2027ba8ef6108aefd098eef7cd5a76ae10193df9685ce303c2cb5f98b3ae0

Observation 5b914a3f-312f-4460-9a8d-42c26db8f75e · outbound

This paper cites Settling the sample complexity of single- parameter revenue maximization.

Learning Truthful Mechanisms without Discretization Settling the sample complexity of single- parameter revenue maximization

Reference 53

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source=pdf_text observed=2026-08-06T22:03:22.704343Z digest=sha256:d9acf9f985c65f430e5066bda2f34f3aeaf274f05563376d97cd0a87778c2c4b

Observation 8fbd5680-4c7b-44cb-a8ed-70b816e838a4 · outbound

This paper cites Computationally feasible automated mechanism design: General approach and case studies.

Learning Truthful Mechanisms without Discretization Computationally feasible automated mechanism design: General approach and case studies

Reference 54

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source=pdf_text observed=2026-08-06T22:03:22.817309Z digest=sha256:30383cb89a859e63123a41f96b3db247c8b85786ea665f58ec133ee0256a49c9

Observation 0586909e-08ae-4f0e-aada-cd315e926e80 · outbound

This paper cites Optimizing affine maximizer auctions via linear programming: an application to revenue maximizing mechanism design for zero-day exploits markets.

Learning Truthful Mechanisms without Discretization Optimizing affine maximizer auctions via linear programming: an application to revenue maximizing mechanism design for zero-day exploits markets

Reference 55

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source=pdf_text observed=2026-08-06T22:03:22.955541Z digest=sha256:619925e5a956972b6c6a8981d357c391262c9c46d9eb2218c2c5712d0e5a8647

Observation 53fa4dae-a350-472e-a315-c5362b82f2df · outbound

This paper cites Prior-Independent Auctions for Heterogeneous Bidders.

Learning Truthful Mechanisms without Discretization Prior-Independent Auctions for Heterogeneous Bidders

Reference 56

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source=pdf_text observed=2026-08-06T22:03:23.091781Z digest=sha256:2e8cd527b834acf10559e7cc6a113cc03e6afa0bda421fd568f3c37182628543

Observation 5df34d58-7e08-49f6-b8d3-172eb45dd3b4 · outbound

This paper cites Automated on- line mechanism design and prophet inequalities.

Learning Truthful Mechanisms without Discretization Automated on- line mechanism design and prophet inequalities

Reference 57

Resolution
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source=pdf_text observed=2026-08-06T22:03:23.190298Z digest=sha256:343d11b0ed170f5a51eefc507dcd543129a5ed4987ac31aaa8001e630354745f

Observation 8c8728d7-f23c-4dfa-878e-28e301d9d615 · outbound

This paper cites Straightforward individual incentive compatibility in large economies.

Learning Truthful Mechanisms without Discretization Straightforward individual incentive compatibility in large economies

Reference 58

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source=pdf_text observed=2026-08-06T22:03:23.297814Z digest=sha256:73538cd62204da528d3de292c3069c3ed19db315ab9667b3f0224a4ac845c7d6

Observation 51ebbfde-645c-43b3-b4f2-1fa159cf288b · outbound

This paper cites Universal approximation of symmetric and anti-symmetric functions.

Learning Truthful Mechanisms without Discretization Universal approximation of symmetric and anti-symmetric functions

Reference 59

Resolution
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source=pdf_text observed=2026-08-06T22:03:23.404589Z digest=sha256:a593276c326281d5e477e02d7e10e1ed1bee78dc9943982a13bdbf76a1365145

Observation 6e4510f6-f578-4c5e-8924-2381b24ff546 · outbound

This paper cites Profit maximization in mechanism design.

Learning Truthful Mechanisms without Discretization Profit maximization in mechanism design

Reference 60

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source=pdf_text observed=2026-08-06T22:03:23.514389Z digest=sha256:883eaf401df35979a4edea2ef8cbf1367dd6b2ee5a07dc75ad8d8017ed97aa39

Observation 6bb739bb-d0f9-4d5a-9f8d-febfb358d084 · outbound

This paper cites Gaussian Error Linear Units (GELUs).

Learning Truthful Mechanisms without Discretization Gaussian Error Linear Units (GELUs)

Reference 61

Resolution
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source=pdf_text observed=2026-08-06T22:03:23.631653Z digest=sha256:f9407d1296e927d6e744cec737d3f998c7af7cc128778b71b790c85097c2ce8f

Observation b25b6e4d-f007-4bda-a621-4500af4b4706 · outbound

This paper cites Welfare maximization with production costs: A primal dual approach.

Learning Truthful Mechanisms without Discretization Welfare maximization with production costs: A primal dual approach

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:03:49.863067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:03:23.734138Z digest=sha256:7c1a3717d38074021a7acf8754dbb09c406b9d3d27a5be85ec4ddc7126412e72

Observation c6721c6f-079b-4441-a05c-4af4b738fa13 · outbound

This paper cites Optimal-er auctions through attention.

Learning Truthful Mechanisms without Discretization Optimal-er auctions through attention

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:03:49.636386Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:03:23.804975Z digest=sha256:7bb65689beb99c73f235992278392a6c6829ddda6d4b531fc584ea0f11c71010

Observation ef2e18dc-215a-47bb-8d47-37c859266f96 · outbound

This paper cites Posted Price Mechanisms for Online Allocation with Disec- onomies of Scale.

Learning Truthful Mechanisms without Discretization Posted Price Mechanisms for Online Allocation with Disec- onomies of Scale

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:03:49.379759Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:03:23.913680Z digest=sha256:51f336e6d091eee50765f0c5172212c323708392eb360148fef21ff4ce986e81

Observation e34f5530-84c6-4701-8182-bb20ba1223dc · outbound

This paper cites An Online Intelligent Task Pricing Mechanism Based on Reverse Auction in Mobile Crowdsensing Networks for the Internet of Things.

Learning Truthful Mechanisms without Discretization An Online Intelligent Task Pricing Mechanism Based on Reverse Auction in Mobile Crowdsensing Networks for the Internet of Things

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:03:49.112564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:03:23.992501Z digest=sha256:3b5e6cc749b53700fea94e3ea0da413dd31af7b3b936f4fe240bbf1a20cb3ada

Observation e17d3687-e1d4-423b-bfe6-549cc9bf8502 · outbound

This paper cites Estimation of particle transmission by random sampling.

Learning Truthful Mechanisms without Discretization Estimation of particle transmission by random sampling

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:03:48.880579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:03:24.073807Z digest=sha256:cc2e402260e89ccb200daa216d700c20c0201266832d55c5f3b55c195f81c6ea

Observation c93494be-dc5e-429e-973b-0ed2e68c4b29 · outbound

This paper cites Parameterized convex universal approximators for decision- making problems.

Learning Truthful Mechanisms without Discretization Parameterized convex universal approximators for decision- making problems

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:03:48.590802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:03:24.140249Z digest=sha256:307906daee02aa9230fbedd2a762d9b83094bb81aac90b1664322461ca351ce0

Observation b8ed81b5-07d6-4219-8ef8-0d51daa396ec · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Learning Truthful Mechanisms without Discretization Adam: A Method for Stochastic Optimization

Reference 68

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source=pdf_text observed=2026-08-06T22:03:24.218228Z digest=sha256:c6821c2a008bfb93e1d995d9e1ae7da94c809a344ca2431262388432ac1de746

Observation 4cb63ce5-d980-4203-b61a-bf9aea8f1d68 · outbound

This paper cites Bayesian estimates of equation system parameters: an application of integration by Monte Carlo.

Learning Truthful Mechanisms without Discretization Bayesian estimates of equation system parameters: an application of integration by Monte Carlo

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:03:48.340250Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:03:24.303036Z digest=sha256:25f6d75d2d4fafcdd89efab7fc32e29db434c774bc8f7baed8021aa9ea57ab9b

Observation 1b0f7ec0-904c-4c77-9e65-1ad33ea11f51 · outbound

This paper cites Total-cost procurement auctions: Impact of suppliers’ cost adjustments on auction format choice.

Learning Truthful Mechanisms without Discretization Total-cost procurement auctions: Impact of suppliers’ cost adjustments on auction format choice

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:03:48.012487Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:03:24.371591Z digest=sha256:a16600c437cd58f8cc74909bc272f8c80ee4461f18a7745e479765eee618c46b

Observation 6cc72ebd-f118-4784-b233-1d7c8b37a6a4 · outbound

This paper cites Faster first-order methods for extensive-form game solving.

Learning Truthful Mechanisms without Discretization Faster first-order methods for extensive-form game solving

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:03:47.710679Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:03:24.473727Z digest=sha256:14f2178cce2574955aa693dd67fdd6d9a3c004e6938aa3226c33cd2acb535fb3

Observation cfbfe6c9-4b61-4b4a-831f-16d4759af485 · outbound

This paper cites Towards a characterization of truthful combi- natorial auctions.

Learning Truthful Mechanisms without Discretization Towards a characterization of truthful combi- natorial auctions

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:03:47.388967Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:03:24.565841Z digest=sha256:3ae9916e2478a500c2be87de4196bf71c34ad6f4156937488376ee6887f1bf13

Observation f949a3ae-ef4f-41e1-a9d3-6d93edba9319 · outbound

This paper cites Two simplified proofs for Roberts’ theorem.

Learning Truthful Mechanisms without Discretization Two simplified proofs for Roberts’ theorem

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:03:46.824269Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:03:24.741994Z digest=sha256:8194c1a57a14d75c601b6dc10120c5cf04f96ce794964c22974387f0c8bf046d

Observation 4e8a7139-734b-4a8f-9c46-c232d294cfff · outbound

This paper cites Truthful and near-optimal mechanism design via linear programming.

Learning Truthful Mechanisms without Discretization Truthful and near-optimal mechanism design via linear programming

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:03:46.502859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:03:24.834317Z digest=sha256:1bf9b8b96cb4448f56412e0ec1a9c20285c9a0072633ccef07ed05fdd9598127

Observation 6676b129-9c08-4de0-b955-0c7148d22cef · outbound

This paper cites Deep learning.

Learning Truthful Mechanisms without Discretization Deep learning

Reference 75

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:03:46.175708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:03:24.917310Z digest=sha256:bcf22bee4bed62a3acf5eb31ed1d38fa200fc4879b6811c161847662f6eeb0b5

Observation def9fba6-91ba-4c11-acbb-bdb14e4c8d72 · outbound

This paper cites Set transformer: A framework for attention-based permutation-invariant neural networks.

Learning Truthful Mechanisms without Discretization Set transformer: A framework for attention-based permutation-invariant neural networks

Reference 76

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:03:45.916232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:03:25.028023Z digest=sha256:d85d021b8225b73f380cda420e6cb1f8c815eb030e72b2faa6c51fbbe2a54b65

Observation 189d8397-9c54-440c-80d6-452f0a2f6dcf · outbound

This paper cites Approximating revenue-maximizing combi- natorial auctions.

Learning Truthful Mechanisms without Discretization Approximating revenue-maximizing combi- natorial auctions

Reference 77

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:03:45.606448Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:03:25.081299Z digest=sha256:d06477b4073b118ebd7b83582b3525bf75b78575338ef4efdd7dc98695512a6b

Observation 9c840a5e-5613-4f26-adda-3703ae0cf455 · outbound

This paper cites Bundling as an optimal selling mechanism for a multiple-good monopolist.

Learning Truthful Mechanisms without Discretization Bundling as an optimal selling mechanism for a multiple-good monopolist

Reference 78

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:03:45.356308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:03:25.157008Z digest=sha256:dfc39843cec2aec1773223d056997ff2c5fd6835fa8deec05e420d4579e0e124

Observation 3bac1c1f-ec92-4795-b0fe-9f625261225a · outbound

This paper cites Microeconomic theory.

Learning Truthful Mechanisms without Discretization Microeconomic theory

Reference 79

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:03:45.061301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:03:25.236568Z digest=sha256:de224a68e1ecc25ed61a755d13aeffcb4f8e9b950810b2b5966a674b22ef44ee

Observation dabb16a4-eaf4-4589-b730-b4d29409548a · outbound

This paper cites The maximum numbers of faces of a convex polytope.

Learning Truthful Mechanisms without Discretization The maximum numbers of faces of a convex polytope

Reference 80

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:03:44.643715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:03:25.327173Z digest=sha256:203d406967547028aa89cce3143545325aece2051184b59f616b2e249a1200ec

Observation 0cd149c2-179c-4d44-9637-867c465d9bf9 · outbound

This paper cites Equation of state calculations by fast computing machines.

Learning Truthful Mechanisms without Discretization Equation of state calculations by fast computing machines

Reference 81

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:03:44.336076Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:03:25.414799Z digest=sha256:49320ff421b849130c444f75b75ee51c07affeeabef09db31010c82756fd2c53

Observation e8c13b39-5543-46f1-b6b7-529825804047 · outbound

This paper cites Envelope theorems for arbitrary choice sets.

Learning Truthful Mechanisms without Discretization Envelope theorems for arbitrary choice sets

Reference 82

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:03:43.988280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:03:25.512515Z digest=sha256:79fc569f971f34ff45190e9646a41fc4ce314423922486e79b562b7d9161f038

Observation b17486ce-7d8f-4ce7-bc77-89b29dbb995b · outbound

This paper cites A theory of auctions and competitive bidding.

Learning Truthful Mechanisms without Discretization A theory of auctions and competitive bidding

Reference 83

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:03:43.707633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:03:25.598799Z digest=sha256:9865132d15fb824c26d41b5c37c4af011daac8f80f8e90b82960c31770d7c52c

Observation 148936be-4ad2-4267-9c81-c8221ea77ed9 · outbound

This paper cites On strategy-proofness and single peakedness.

Learning Truthful Mechanisms without Discretization On strategy-proofness and single peakedness

Reference 84

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:03:43.365450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:03:25.732090Z digest=sha256:e96bd6133c5ed2b21e742960f0f0e306748e356a7633b43a4fc98fd9465d6f3f

Observation 58fa8d15-8c99-4df3-87d2-03f4913cc44b · outbound

This paper cites Incentive compatibility and the bargaining problem.

Learning Truthful Mechanisms without Discretization Incentive compatibility and the bargaining problem

Reference 85

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:03:42.996823Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:03:25.832642Z digest=sha256:0d7be1df3c5835359364bc8051ca9be640c389512e625a2b412c09b2e6a4420d

Observation 57ca2496-7631-4420-b933-b92d5a39b709 · outbound

This paper cites Optimal auction design.

Learning Truthful Mechanisms without Discretization Optimal auction design

Reference 86

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:03:42.688261Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:03:25.916118Z digest=sha256:99c31a0fe517cbaebc6497bd7be8f8a5b7f4e726b6968cc6ff5ed02e81ae1c0b

Observation f2b62b12-b57e-47c7-830a-277b7ff65739 · outbound

This paper cites Automated mech- anism design without money via machine learning.

Learning Truthful Mechanisms without Discretization Automated mech- anism design without money via machine learning

Reference 87

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:03:42.454373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:03:25.996076Z digest=sha256:89e09a5e26b64c29d02bbba6f1ab26e3b0b18cf701372c2e92764a254ad6bad8

Observation 9674d893-5d9d-43dd-8d93-c6757ff486d7 · outbound

This paper cites Affine maximizers in domains with selfish valuations.

Learning Truthful Mechanisms without Discretization Affine maximizers in domains with selfish valuations

Reference 88

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:03:42.091491Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:03:26.076449Z digest=sha256:61cfd6482b561d597b80f2aa289ffa52311ae89509d13d77f10ab004755b0505

Observation dc29035f-6744-45f0-9f23-49ba1daf3d17 · outbound

This paper cites Sur une g´ en´ eralisation des int´ egrales de MJ Radon.

Learning Truthful Mechanisms without Discretization Sur une g´ en´ eralisation des int´ egrales de MJ Radon

Reference 89

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:03:41.773789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:03:26.185405Z digest=sha256:4b79c9e0c989d780983a1c2f796c9d2d38403f8359963a7a918ec53c10cb23d3

Observation 886d0fed-c6d9-41f4-8abf-cbd2ed2e02e6 · outbound

This paper cites Algorithmic Game Theory.

Learning Truthful Mechanisms without Discretization Algorithmic Game Theory

Reference 90

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:03:41.505796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:03:26.267657Z digest=sha256:db5b802ff7f863d7e10045e04f98d55c7280ae85165e9dd905fbad2ddfe50fc1

Observation 584dfe81-c43c-4761-9d89-371c69d6dab0 · outbound

This paper cites Optimal mechanism for selling two goods.

Learning Truthful Mechanisms without Discretization Optimal mechanism for selling two goods

Reference 91

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:03:41.250654Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:03:26.353455Z digest=sha256:3c0dd3e07ae28a354f53893fd6a2761dc744a2830b2b14cf105887b423d7c373

Observation 4ade873e-8565-4a46-8267-555bbb49dee5 · outbound

This paper cites Preferencenet: Encoding human preferences in auction design with deep learning.

Learning Truthful Mechanisms without Discretization Preferencenet: Encoding human preferences in auction design with deep learning

Reference 92

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:03:40.960148Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:03:26.426354Z digest=sha256:738c4278ad8dc94d6797d4c38996f83c3619ecb8c004a0c34088a60e027dcf4a

Observation 8f190efa-73b7-485b-9f5a-9aee51abc9f1 · outbound

This paper cites Why and when can deep-but not shallow-networks avoid the curse of dimensionality: a review.

Learning Truthful Mechanisms without Discretization Why and when can deep-but not shallow-networks avoid the curse of dimensionality: a review

Reference 93

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:03:40.680453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:03:26.541082Z digest=sha256:8be2e711739998aaa22e3a51308fb29e1a0863992279c2ce9ed87ac6c35dff2d

Observation 250766bd-ad59-429f-a75a-a76cbf2c58ef · outbound

This paper cites Benefits of permutation-equivariance in auction mechanisms.

Learning Truthful Mechanisms without Discretization Benefits of permutation-equivariance in auction mechanisms

Reference 94

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:03:40.393667Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:03:26.623014Z digest=sha256:6411a616bbbbb76609a059fa8cdb87297ba9395c1c353d148bfe042442b27884

Observation e6e161fe-97aa-4d86-93a2-98695f067020 · outbound

This paper cites Auction learning as a two-player game.

Learning Truthful Mechanisms without Discretization Auction learning as a two-player game

Reference 95

Resolution
verified exact
local_arxiv, observed 2026-08-06T22:03:31.531506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:03:26.709583Z digest=sha256:098289c6960e2e9d4b339c7b4a6dafc69a88a3e8e5a841cd683dffe1a560f5b9

Observation a0ce2fd4-f2b8-4ae2-a153-8258c0f7feb3 · outbound

This paper cites Auction Learning as a Two-Player Game.

Learning Truthful Mechanisms without Discretization Auction Learning as a Two-Player Game

Reference 96

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:03:40.116497Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:03:26.805352Z digest=sha256:197d313ca59da9ffb05f3b27dd5730f314ba499424590f541614f178aad55ef8

Observation facaccac-745d-49ea-8e6b-e1271ad372ca · outbound

This paper cites A permutation-equivariant neural network architecture for auction de- sign.

Learning Truthful Mechanisms without Discretization A permutation-equivariant neural network architecture for auction de- sign

Reference 97

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:03:39.764959Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:03:26.922879Z digest=sha256:c08bf424516fa43cb91a84a209693295b38ada430fe870725033557c58c95093

Observation 65e9af19-9bff-4393-8d4d-8560418118eb · outbound

This paper cites Deep Learning for Two-Sided Matching.

Learning Truthful Mechanisms without Discretization Deep Learning for Two-Sided Matching

Reference 98

Resolution
unresolved
no resolver link, observed 2026-08-06T22:03:27.031927Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:03:27.031927Z digest=sha256:633d3f33314c170740195f20d955108e2c5819bc76d395dbb851b16e068f915e

Observation 599a11f6-2c2b-4caa-a647-cb7e23cee919 · outbound

This paper cites url: https : / / www.

Learning Truthful Mechanisms without Discretization url: https : / / www

Reference 99

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:03:39.412386Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:03:27.126296Z digest=sha256:41c6621ca2fdab6d9a7523fc8649d1afb4028e8aa6156552a76fb2405d41f62d

Observation 54e00091-90d5-43f5-ae17-08c186330608 · outbound

This paper cites Exponential convergence of Langevin distribu- tions and their discrete approximations.

Learning Truthful Mechanisms without Discretization Exponential convergence of Langevin distribu- tions and their discrete approximations

Reference 100

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:03:39.156536Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:03:27.213453Z digest=sha256:32f9affa9783797c1c31821515a4b581a079b8eda61678b3497bae0872a136d8

Pith citing papers

No inbound Pith citation observations are available.