{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:FXSTSC6VHRQE5UBVASHOCC6ZW2","short_pith_number":"pith:FXSTSC6V","schema_version":"1.0","canonical_sha256":"2de5390bd53c604ed035048ee10bd9b6befcd9b31e1de3cc73d6d63cb3896abc","source":{"kind":"arxiv","id":"2508.20578","version":1},"attestation_state":"computed","paper":{"title":"Human-AI Collaborative Bot Detection in MMORPGs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CR"],"primary_cat":"cs.AI","authors_text":"Hyunsoo Kim, Jaeman Son","submitted_at":"2025-08-28T09:17:35Z","abstract_excerpt":"In Massively Multiplayer Online Role-Playing Games (MMORPGs), auto-leveling bots exploit automated programs to level up characters at scale, undermining gameplay balance and fairness. Detecting such bots is challenging, not only because they mimic human behavior, but also because punitive actions require explainable justification to avoid legal and user experience issues. In this paper, we present a novel framework for detecting auto-leveling bots by leveraging contrastive representation learning and clustering techniques in a fully unsupervised manner to identify groups of characters with sim"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2508.20578","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2025-08-28T09:17:35Z","cross_cats_sorted":["cs.CR"],"title_canon_sha256":"d93a2473ae5e22169fd4a1cfbcefb2f18f8f0aab0d70bf5c5670e0fadef6f70f","abstract_canon_sha256":"0cb71f12ed04f854242da09cbbd8b1e5e0c95f34513eec8fc49347a09a6b06f8"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T12:00:55.259995Z","signature_b64":"9uGhGHvkVt9UpHaYh00GCgxaRIJRr438+sFF8ro6RH//rjZDojCB1hjqjr6SPK6Ww76oHc9pQvszxoA4iu3ECA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2de5390bd53c604ed035048ee10bd9b6befcd9b31e1de3cc73d6d63cb3896abc","last_reissued_at":"2026-07-05T12:00:55.259513Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T12:00:55.259513Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Human-AI Collaborative Bot Detection in MMORPGs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CR"],"primary_cat":"cs.AI","authors_text":"Hyunsoo Kim, Jaeman Son","submitted_at":"2025-08-28T09:17:35Z","abstract_excerpt":"In Massively Multiplayer Online Role-Playing Games (MMORPGs), auto-leveling bots exploit automated programs to level up characters at scale, undermining gameplay balance and fairness. Detecting such bots is challenging, not only because they mimic human behavior, but also because punitive actions require explainable justification to avoid legal and user experience issues. In this paper, we present a novel framework for detecting auto-leveling bots by leveraging contrastive representation learning and clustering techniques in a fully unsupervised manner to identify groups of characters with sim"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.20578","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2508.20578/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2508.20578","created_at":"2026-07-05T12:00:55.259579+00:00"},{"alias_kind":"arxiv_version","alias_value":"2508.20578v1","created_at":"2026-07-05T12:00:55.259579+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.20578","created_at":"2026-07-05T12:00:55.259579+00:00"},{"alias_kind":"pith_short_12","alias_value":"FXSTSC6VHRQE","created_at":"2026-07-05T12:00:55.259579+00:00"},{"alias_kind":"pith_short_16","alias_value":"FXSTSC6VHRQE5UBV","created_at":"2026-07-05T12:00:55.259579+00:00"},{"alias_kind":"pith_short_8","alias_value":"FXSTSC6V","created_at":"2026-07-05T12:00:55.259579+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/FXSTSC6VHRQE5UBVASHOCC6ZW2","json":"https://pith.science/pith/FXSTSC6VHRQE5UBVASHOCC6ZW2.json","graph_json":"https://pith.science/api/pith-number/FXSTSC6VHRQE5UBVASHOCC6ZW2/graph.json","events_json":"https://pith.science/api/pith-number/FXSTSC6VHRQE5UBVASHOCC6ZW2/events.json","paper":"https://pith.science/paper/FXSTSC6V"},"agent_actions":{"view_html":"https://pith.science/pith/FXSTSC6VHRQE5UBVASHOCC6ZW2","download_json":"https://pith.science/pith/FXSTSC6VHRQE5UBVASHOCC6ZW2.json","view_paper":"https://pith.science/paper/FXSTSC6V","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2508.20578&json=true","fetch_graph":"https://pith.science/api/pith-number/FXSTSC6VHRQE5UBVASHOCC6ZW2/graph.json","fetch_events":"https://pith.science/api/pith-number/FXSTSC6VHRQE5UBVASHOCC6ZW2/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/FXSTSC6VHRQE5UBVASHOCC6ZW2/action/timestamp_anchor","attest_storage":"https://pith.science/pith/FXSTSC6VHRQE5UBVASHOCC6ZW2/action/storage_attestation","attest_author":"https://pith.science/pith/FXSTSC6VHRQE5UBVASHOCC6ZW2/action/author_attestation","sign_citation":"https://pith.science/pith/FXSTSC6VHRQE5UBVASHOCC6ZW2/action/citation_signature","submit_replication":"https://pith.science/pith/FXSTSC6VHRQE5UBVASHOCC6ZW2/action/replication_record"}},"created_at":"2026-07-05T12:00:55.259579+00:00","updated_at":"2026-07-05T12:00:55.259579+00:00"}