{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:OLIZEFOCHQWMA5W4XGNAKG2YQB","short_pith_number":"pith:OLIZEFOC","canonical_record":{"source":{"id":"2411.14264","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.NI","submitted_at":"2024-11-21T16:20:31Z","cross_cats_sorted":[],"title_canon_sha256":"aadae95bda40cc2a1dccc63684835855fc51f325d4c1e7334c1d07608b99e4e2","abstract_canon_sha256":"7c80c624f51fd15cd948961efd8640220004c8459c556b0b1322ff94c034eb02"},"schema_version":"1.0"},"canonical_sha256":"72d19215c23c2cc076dcb99a051b5880432a43aee26e8f34e741a703d4f6399f","source":{"kind":"arxiv","id":"2411.14264","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.14264","created_at":"2026-07-05T09:38:44Z"},{"alias_kind":"arxiv_version","alias_value":"2411.14264v1","created_at":"2026-07-05T09:38:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.14264","created_at":"2026-07-05T09:38:44Z"},{"alias_kind":"pith_short_12","alias_value":"OLIZEFOCHQWM","created_at":"2026-07-05T09:38:44Z"},{"alias_kind":"pith_short_16","alias_value":"OLIZEFOCHQWMA5W4","created_at":"2026-07-05T09:38:44Z"},{"alias_kind":"pith_short_8","alias_value":"OLIZEFOC","created_at":"2026-07-05T09:38:44Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:OLIZEFOCHQWMA5W4XGNAKG2YQB","target":"record","payload":{"canonical_record":{"source":{"id":"2411.14264","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.NI","submitted_at":"2024-11-21T16:20:31Z","cross_cats_sorted":[],"title_canon_sha256":"aadae95bda40cc2a1dccc63684835855fc51f325d4c1e7334c1d07608b99e4e2","abstract_canon_sha256":"7c80c624f51fd15cd948961efd8640220004c8459c556b0b1322ff94c034eb02"},"schema_version":"1.0"},"canonical_sha256":"72d19215c23c2cc076dcb99a051b5880432a43aee26e8f34e741a703d4f6399f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:38:44.351109Z","signature_b64":"Qc3UuCN6PoT7wXPpNdAGuHufdx1N38WovHGJLduPEaNEYkloJL2AW7d3aVl5i2U1Kjsi32xUfPX4xmN5mPe6BA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"72d19215c23c2cc076dcb99a051b5880432a43aee26e8f34e741a703d4f6399f","last_reissued_at":"2026-07-05T09:38:44.350581Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:38:44.350581Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2411.14264","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:38:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7CwzI8mh0/oPxvb7pjhZOodr043Byq79izo2Z7GE0tOQV0C0KJRChODVPAfgpyfInRj3kZGyIXxInjrlnZQTAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-12T23:16:52.798317Z"},"content_sha256":"2ccacb77ac3acfa8525fe629f68ce4545aba3f19c8726303b79d5cea7d27c821","schema_version":"1.0","event_id":"sha256:2ccacb77ac3acfa8525fe629f68ce4545aba3f19c8726303b79d5cea7d27c821"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:OLIZEFOCHQWMA5W4XGNAKG2YQB","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Explainable Multi-Agent Reinforcement Learning for Extended Reality Codec Adaptation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.NI","authors_text":"Majid Bavand, Medhat Elsayed, Melike Erol-Kantarci, Pedro Enrique Iturria-Rivera, Raimundas Gaigalas, Yigit Ozcan","submitted_at":"2024-11-21T16:20:31Z","abstract_excerpt":"Extended Reality (XR) services are set to transform applications over 5th and 6th generation wireless networks, delivering immersive experiences. Concurrently, Artificial Intelligence (AI) advancements have expanded their role in wireless networks, however, trust and transparency in AI remain to be strengthened. Thus, providing explanations for AI-enabled systems can enhance trust. We introduce Value Function Factorization (VFF)-based Explainable (X) Multi-Agent Reinforcement Learning (MARL) algorithms, explaining reward design in XR codec adaptation through reward decomposition. We contribute"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.14264","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/2411.14264/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:38:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PtKAvHe9tTkxJDqofLTSW9cJwrApEgloX6L/b/hhGWxG3PqfSCX5sYLDGFZJln2qw9CcRDg9xlG2Pa75ptxxBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-12T23:16:52.798841Z"},"content_sha256":"ce0c2920c4542f279d41523d2613c93eee0b985b9ccc7e147254c4a006af07fa","schema_version":"1.0","event_id":"sha256:ce0c2920c4542f279d41523d2613c93eee0b985b9ccc7e147254c4a006af07fa"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/OLIZEFOCHQWMA5W4XGNAKG2YQB/bundle.json","state_url":"https://pith.science/pith/OLIZEFOCHQWMA5W4XGNAKG2YQB/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/OLIZEFOCHQWMA5W4XGNAKG2YQB/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-12T23:16:52Z","links":{"resolver":"https://pith.science/pith/OLIZEFOCHQWMA5W4XGNAKG2YQB","bundle":"https://pith.science/pith/OLIZEFOCHQWMA5W4XGNAKG2YQB/bundle.json","state":"https://pith.science/pith/OLIZEFOCHQWMA5W4XGNAKG2YQB/state.json","well_known_bundle":"https://pith.science/.well-known/pith/OLIZEFOCHQWMA5W4XGNAKG2YQB/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:OLIZEFOCHQWMA5W4XGNAKG2YQB","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"7c80c624f51fd15cd948961efd8640220004c8459c556b0b1322ff94c034eb02","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.NI","submitted_at":"2024-11-21T16:20:31Z","title_canon_sha256":"aadae95bda40cc2a1dccc63684835855fc51f325d4c1e7334c1d07608b99e4e2"},"schema_version":"1.0","source":{"id":"2411.14264","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.14264","created_at":"2026-07-05T09:38:44Z"},{"alias_kind":"arxiv_version","alias_value":"2411.14264v1","created_at":"2026-07-05T09:38:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.14264","created_at":"2026-07-05T09:38:44Z"},{"alias_kind":"pith_short_12","alias_value":"OLIZEFOCHQWM","created_at":"2026-07-05T09:38:44Z"},{"alias_kind":"pith_short_16","alias_value":"OLIZEFOCHQWMA5W4","created_at":"2026-07-05T09:38:44Z"},{"alias_kind":"pith_short_8","alias_value":"OLIZEFOC","created_at":"2026-07-05T09:38:44Z"}],"graph_snapshots":[{"event_id":"sha256:ce0c2920c4542f279d41523d2613c93eee0b985b9ccc7e147254c4a006af07fa","target":"graph","created_at":"2026-07-05T09:38:44Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2411.14264/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Extended Reality (XR) services are set to transform applications over 5th and 6th generation wireless networks, delivering immersive experiences. Concurrently, Artificial Intelligence (AI) advancements have expanded their role in wireless networks, however, trust and transparency in AI remain to be strengthened. Thus, providing explanations for AI-enabled systems can enhance trust. We introduce Value Function Factorization (VFF)-based Explainable (X) Multi-Agent Reinforcement Learning (MARL) algorithms, explaining reward design in XR codec adaptation through reward decomposition. We contribute","authors_text":"Majid Bavand, Medhat Elsayed, Melike Erol-Kantarci, Pedro Enrique Iturria-Rivera, Raimundas Gaigalas, Yigit Ozcan","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.NI","submitted_at":"2024-11-21T16:20:31Z","title":"Explainable Multi-Agent Reinforcement Learning for Extended Reality Codec Adaptation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.14264","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:2ccacb77ac3acfa8525fe629f68ce4545aba3f19c8726303b79d5cea7d27c821","target":"record","created_at":"2026-07-05T09:38:44Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"7c80c624f51fd15cd948961efd8640220004c8459c556b0b1322ff94c034eb02","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.NI","submitted_at":"2024-11-21T16:20:31Z","title_canon_sha256":"aadae95bda40cc2a1dccc63684835855fc51f325d4c1e7334c1d07608b99e4e2"},"schema_version":"1.0","source":{"id":"2411.14264","kind":"arxiv","version":1}},"canonical_sha256":"72d19215c23c2cc076dcb99a051b5880432a43aee26e8f34e741a703d4f6399f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"72d19215c23c2cc076dcb99a051b5880432a43aee26e8f34e741a703d4f6399f","first_computed_at":"2026-07-05T09:38:44.350581Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:38:44.350581Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Qc3UuCN6PoT7wXPpNdAGuHufdx1N38WovHGJLduPEaNEYkloJL2AW7d3aVl5i2U1Kjsi32xUfPX4xmN5mPe6BA==","signature_status":"signed_v1","signed_at":"2026-07-05T09:38:44.351109Z","signed_message":"canonical_sha256_bytes"},"source_id":"2411.14264","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2ccacb77ac3acfa8525fe629f68ce4545aba3f19c8726303b79d5cea7d27c821","sha256:ce0c2920c4542f279d41523d2613c93eee0b985b9ccc7e147254c4a006af07fa"],"state_sha256":"31c62df80d591253e9420007c4c9a7cf5a66abedb9991390d886902d3a1ae9fa"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XOeCRe4eCmyX3LW+PYjExO/Qvd3apnjsh7thHW4NELeGewjXfgXvTgmPnCGKvkhXHTOxDosIi7HIlpw0adBnCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-12T23:16:52.804404Z","bundle_sha256":"96580814f129bebe7a19a13d40c47b6c5219a0b59adbbcbf548a1a566e2926e4"}}