{"paper":{"title":"Probabilistic Mechanism Design in Diffusion Auctions","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"The Probabilistic Diffusion Mechanism achieves incentive compatibility, non-negative revenue, and constant-approximation efficiency for diffusion auctions on path graphs and extends to general networks.","cross_cats":[],"primary_cat":"cs.GT","authors_text":"Hanpin Wang, Xinlun Zhang, Yongzhi Cao, Yu Huang, Zhechen Li","submitted_at":"2026-05-17T01:54:28Z","abstract_excerpt":"A diffusion auction refers to a selling process conducted over a social network, where each participant submits a bid and may invite other potential buyers to join the auction. Although various mechanisms have been proposed, none of them can simultaneously achieve incentive compatibility, non-negative revenue, and approximate efficiency with a constant approximation bound. In this paper, we propose the Probabilistic Diffusion Mechanism (PDM), a novel mechanism tailored for path graphs, which satisfies all three desired properties. We further extend PDM to general network structures through a m"},"claims":{"count":4,"items":[{"kind":"strongest_claim","text":"We propose the Probabilistic Diffusion Mechanism (PDM), a novel mechanism tailored for path graphs, which satisfies all three desired properties: incentive compatibility, non-negative revenue, and approximate efficiency with a constant approximation bound.","source":"verdict.strongest_claim","status":"machine_extracted","claim_id":"C1","attestation":"unclaimed"},{"kind":"weakest_assumption","text":"The base mechanism is defined only for path graphs and extensions rely on a map f that preserves key properties when the network is arbitrary; if no such f exists that simultaneously maintains IC, non-negative revenue, and the constant efficiency bound for general graphs, the general claim fails.","source":"verdict.weakest_assumption","status":"machine_extracted","claim_id":"C2","attestation":"unclaimed"},{"kind":"one_line_summary","text":"PDM and f-PDM achieve IC, non-negative revenue, and constant-approximate efficiency in diffusion auctions on paths and general networks, with further variants for Sybil attacks, collusion, and multi-unit cases.","source":"verdict.one_line_summary","status":"machine_extracted","claim_id":"C3","attestation":"unclaimed"},{"kind":"headline","text":"The Probabilistic Diffusion Mechanism achieves incentive compatibility, non-negative revenue, and constant-approximation efficiency for diffusion auctions on path graphs and extends to general networks.","source":"verdict.pith_extraction.headline","status":"machine_extracted","claim_id":"C4","attestation":"unclaimed"}],"snapshot_sha256":"c91ebc1e43fb690c74a5dac6cfdc7a578de373e62cbfb3ba23f0b833a09836e8"},"source":{"id":"2605.17221","kind":"arxiv","version":1},"verdict":{"id":"8fe07f53-7c56-4e51-926b-a7a97a5305c2","model_set":{"reader":"grok-4.3"},"created_at":"2026-05-19T23:18:03.185591Z","strongest_claim":"We propose the Probabilistic Diffusion Mechanism (PDM), a novel mechanism tailored for path graphs, which satisfies all three desired properties: incentive compatibility, non-negative revenue, and approximate efficiency with a constant approximation bound.","one_line_summary":"PDM and f-PDM achieve IC, non-negative revenue, and constant-approximate efficiency in diffusion auctions on paths and general networks, with further variants for Sybil attacks, collusion, and multi-unit cases.","pipeline_version":"pith-pipeline@v0.9.0","weakest_assumption":"The base mechanism is defined only for path graphs and extensions rely on a map f that preserves key properties when the network is arbitrary; 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