{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:SX6S73LOQCZU5WU3H6QV62ZV3N","short_pith_number":"pith:SX6S73LO","canonical_record":{"source":{"id":"2406.18420","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-06-26T15:15:15Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"62031382ee4bd2f5b144284728b0ee90077f99617007e8dc4b33de7c165fd23a","abstract_canon_sha256":"bc5edacf452a1a6688288e39d4127fbcf11b829232cc68ed0d597a959843075e"},"schema_version":"1.0"},"canonical_sha256":"95fd2fed6e80b34eda9b3fa15f6b35db5f4fdd8a262e21b8f3663ea01c7d4d22","source":{"kind":"arxiv","id":"2406.18420","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.18420","created_at":"2026-07-05T08:37:08Z"},{"alias_kind":"arxiv_version","alias_value":"2406.18420v1","created_at":"2026-07-05T08:37:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.18420","created_at":"2026-07-05T08:37:08Z"},{"alias_kind":"pith_short_12","alias_value":"SX6S73LOQCZU","created_at":"2026-07-05T08:37:08Z"},{"alias_kind":"pith_short_16","alias_value":"SX6S73LOQCZU5WU3","created_at":"2026-07-05T08:37:08Z"},{"alias_kind":"pith_short_8","alias_value":"SX6S73LO","created_at":"2026-07-05T08:37:08Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:SX6S73LOQCZU5WU3H6QV62ZV3N","target":"record","payload":{"canonical_record":{"source":{"id":"2406.18420","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-06-26T15:15:15Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"62031382ee4bd2f5b144284728b0ee90077f99617007e8dc4b33de7c165fd23a","abstract_canon_sha256":"bc5edacf452a1a6688288e39d4127fbcf11b829232cc68ed0d597a959843075e"},"schema_version":"1.0"},"canonical_sha256":"95fd2fed6e80b34eda9b3fa15f6b35db5f4fdd8a262e21b8f3663ea01c7d4d22","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:37:08.893302Z","signature_b64":"+LqvsQ5dEikl2vL6ldaN2vSEZgddlDhhtUEFwGU2GG1BDd9nj+X2oexw4klRT5D2GyimbM7la2bZLi7WiuuyDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"95fd2fed6e80b34eda9b3fa15f6b35db5f4fdd8a262e21b8f3663ea01c7d4d22","last_reissued_at":"2026-07-05T08:37:08.892882Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:37:08.892882Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2406.18420","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":"2026-07-05T08:37:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Imq3JbAkCUmAMK+Ti10O6F+A3N4RCWVPXEvIQsZop4QLi6VBHsQmH6Ukss6s/LO7+5/o621SxzUz9NiLIizmDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T12:58:48.969164Z"},"content_sha256":"6382f7108a90939d4ed9ad748cec5499b1377208dd2e66ae71c4366f830d449c","schema_version":"1.0","event_id":"sha256:6382f7108a90939d4ed9ad748cec5499b1377208dd2e66ae71c4366f830d449c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:SX6S73LOQCZU5WU3H6QV62ZV3N","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Mixture of Experts in a Mixture of RL settings","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Jakob Foerster, Johan Obando-Ceron, Karolina Dziugaite, Pablo Samuel Castro, Timon Willi","submitted_at":"2024-06-26T15:15:15Z","abstract_excerpt":"Mixtures of Experts (MoEs) have gained prominence in (self-)supervised learning due to their enhanced inference efficiency, adaptability to distributed training, and modularity. Previous research has illustrated that MoEs can significantly boost Deep Reinforcement Learning (DRL) performance by expanding the network's parameter count while reducing dormant neurons, thereby enhancing the model's learning capacity and ability to deal with non-stationarity. In this work, we shed more light on MoEs' ability to deal with non-stationarity and investigate MoEs in DRL settings with \"amplified\" non-stat"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.18420","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/2406.18420/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":"2026-07-05T08:37:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rkhDARKqGoEgXSbaDn41WEI+3mb83aCaGmlPRFIDHgbxrmVYm79xABgI4iC93QhMRRwnbu7WgtYfZf1icNyxAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T12:58:48.969654Z"},"content_sha256":"d41c49293810c5f484d78ba1650c5d06658372dda3428fea4050154f2e20025d","schema_version":"1.0","event_id":"sha256:d41c49293810c5f484d78ba1650c5d06658372dda3428fea4050154f2e20025d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SX6S73LOQCZU5WU3H6QV62ZV3N/bundle.json","state_url":"https://pith.science/pith/SX6S73LOQCZU5WU3H6QV62ZV3N/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SX6S73LOQCZU5WU3H6QV62ZV3N/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":"2026-08-18T12:58:48Z","links":{"resolver":"https://pith.science/pith/SX6S73LOQCZU5WU3H6QV62ZV3N","bundle":"https://pith.science/pith/SX6S73LOQCZU5WU3H6QV62ZV3N/bundle.json","state":"https://pith.science/pith/SX6S73LOQCZU5WU3H6QV62ZV3N/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SX6S73LOQCZU5WU3H6QV62ZV3N/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:SX6S73LOQCZU5WU3H6QV62ZV3N","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":"bc5edacf452a1a6688288e39d4127fbcf11b829232cc68ed0d597a959843075e","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-06-26T15:15:15Z","title_canon_sha256":"62031382ee4bd2f5b144284728b0ee90077f99617007e8dc4b33de7c165fd23a"},"schema_version":"1.0","source":{"id":"2406.18420","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.18420","created_at":"2026-07-05T08:37:08Z"},{"alias_kind":"arxiv_version","alias_value":"2406.18420v1","created_at":"2026-07-05T08:37:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.18420","created_at":"2026-07-05T08:37:08Z"},{"alias_kind":"pith_short_12","alias_value":"SX6S73LOQCZU","created_at":"2026-07-05T08:37:08Z"},{"alias_kind":"pith_short_16","alias_value":"SX6S73LOQCZU5WU3","created_at":"2026-07-05T08:37:08Z"},{"alias_kind":"pith_short_8","alias_value":"SX6S73LO","created_at":"2026-07-05T08:37:08Z"}],"graph_snapshots":[{"event_id":"sha256:d41c49293810c5f484d78ba1650c5d06658372dda3428fea4050154f2e20025d","target":"graph","created_at":"2026-07-05T08:37:08Z","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/2406.18420/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Mixtures of Experts (MoEs) have gained prominence in (self-)supervised learning due to their enhanced inference efficiency, adaptability to distributed training, and modularity. Previous research has illustrated that MoEs can significantly boost Deep Reinforcement Learning (DRL) performance by expanding the network's parameter count while reducing dormant neurons, thereby enhancing the model's learning capacity and ability to deal with non-stationarity. In this work, we shed more light on MoEs' ability to deal with non-stationarity and investigate MoEs in DRL settings with \"amplified\" non-stat","authors_text":"Jakob Foerster, Johan Obando-Ceron, Karolina Dziugaite, Pablo Samuel Castro, Timon Willi","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-06-26T15:15:15Z","title":"Mixture of Experts in a Mixture of RL settings"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.18420","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":"sha256:6382f7108a90939d4ed9ad748cec5499b1377208dd2e66ae71c4366f830d449c","target":"record","created_at":"2026-07-05T08:37:08Z","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":"bc5edacf452a1a6688288e39d4127fbcf11b829232cc68ed0d597a959843075e","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-06-26T15:15:15Z","title_canon_sha256":"62031382ee4bd2f5b144284728b0ee90077f99617007e8dc4b33de7c165fd23a"},"schema_version":"1.0","source":{"id":"2406.18420","kind":"arxiv","version":1}},"canonical_sha256":"95fd2fed6e80b34eda9b3fa15f6b35db5f4fdd8a262e21b8f3663ea01c7d4d22","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"95fd2fed6e80b34eda9b3fa15f6b35db5f4fdd8a262e21b8f3663ea01c7d4d22","first_computed_at":"2026-07-05T08:37:08.892882Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:37:08.892882Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"+LqvsQ5dEikl2vL6ldaN2vSEZgddlDhhtUEFwGU2GG1BDd9nj+X2oexw4klRT5D2GyimbM7la2bZLi7WiuuyDw==","signature_status":"signed_v1","signed_at":"2026-07-05T08:37:08.893302Z","signed_message":"canonical_sha256_bytes"},"source_id":"2406.18420","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6382f7108a90939d4ed9ad748cec5499b1377208dd2e66ae71c4366f830d449c","sha256:d41c49293810c5f484d78ba1650c5d06658372dda3428fea4050154f2e20025d"],"state_sha256":"4aa73f0a1f933b4aebaae3736e18db1c6dc1f3979325b1019847cacc6d6b45f4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aeP+4GuYU29qgzFI5fnS7OdjutB6Be1iKWvkfYZjNnzisozP0Wtitom7RSAymk/f7HFifptXf8RK4etbVNoeBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-18T12:58:48.973606Z","bundle_sha256":"7aeaa3052dfe5cef1cfbb12955a1765cf3d572b79d09babb9df477949a318487"}}