{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:UNJTQ6LUXOV4CUQKDPABYJELJ4","short_pith_number":"pith:UNJTQ6LU","canonical_record":{"source":{"id":"2505.15345","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-21T10:19:49Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"38483c5194f64868715adb827e3171e4ccaf228e89e1d607d29b0040f1a8dd44","abstract_canon_sha256":"577f3c1fa96cf74c68a1baeb1d7676ea3ec056695ea27fd0e84f25e64a00187d"},"schema_version":"1.0"},"canonical_sha256":"a353387974bbabc1520a1bc01c248b4f0deb2dc58a6313b1569102fa4e30437e","source":{"kind":"arxiv","id":"2505.15345","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.15345","created_at":"2026-07-05T11:08:21Z"},{"alias_kind":"arxiv_version","alias_value":"2505.15345v2","created_at":"2026-07-05T11:08:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.15345","created_at":"2026-07-05T11:08:21Z"},{"alias_kind":"pith_short_12","alias_value":"UNJTQ6LUXOV4","created_at":"2026-07-05T11:08:21Z"},{"alias_kind":"pith_short_16","alias_value":"UNJTQ6LUXOV4CUQK","created_at":"2026-07-05T11:08:21Z"},{"alias_kind":"pith_short_8","alias_value":"UNJTQ6LU","created_at":"2026-07-05T11:08:21Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:UNJTQ6LUXOV4CUQKDPABYJELJ4","target":"record","payload":{"canonical_record":{"source":{"id":"2505.15345","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-21T10:19:49Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"38483c5194f64868715adb827e3171e4ccaf228e89e1d607d29b0040f1a8dd44","abstract_canon_sha256":"577f3c1fa96cf74c68a1baeb1d7676ea3ec056695ea27fd0e84f25e64a00187d"},"schema_version":"1.0"},"canonical_sha256":"a353387974bbabc1520a1bc01c248b4f0deb2dc58a6313b1569102fa4e30437e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:08:21.401780Z","signature_b64":"q1VU3Oc+x8fIDRQ0SaOrYa0wS1KyUg3ecnzppHrjF35rryFlmGmz8dS32UNNAFplCDn7t6755P+1zMN/0VKqBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a353387974bbabc1520a1bc01c248b4f0deb2dc58a6313b1569102fa4e30437e","last_reissued_at":"2026-07-05T11:08:21.401284Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:08:21.401284Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2505.15345","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:08:21Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dL07VFDQaLkzIcug92EfFoOsDkdhyEwFtDEvzI7THgoAwA6fQwriwPEC+5D4aT4bJgr5GyYRkeEN0Dir1+O4Bw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T16:19:43.358712Z"},"content_sha256":"060559b9ec0a92f6c0fa2976d6b9469951bd0e7ab8704eeecd55fa0b01c3f8e9","schema_version":"1.0","event_id":"sha256:060559b9ec0a92f6c0fa2976d6b9469951bd0e7ab8704eeecd55fa0b01c3f8e9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:UNJTQ6LUXOV4CUQKDPABYJELJ4","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Hadamax Encoding: Elevating Performance in Model-Free Atari","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Jacob E. Kooi, Vincent Fran\\c{c}ois-Lavet, Zhao Yang","submitted_at":"2025-05-21T10:19:49Z","abstract_excerpt":"Neural network architectures have a large impact in machine learning. In reinforcement learning, network architectures have remained notably simple, as changes often lead to small gains in performance. This work introduces a novel encoder architecture for pixel-based model-free reinforcement learning. The Hadamax (\\textbf{Hada}mard \\textbf{max}-pooling) encoder achieves state-of-the-art performance by max-pooling Hadamard products between GELU-activated parallel hidden layers. Based on the recent PQN algorithm, the Hadamax encoder achieves state-of-the-art model-free performance in the Atari-5"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.15345","kind":"arxiv","version":2},"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/2505.15345/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":"2026-07-05T11:08:21Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ihJ+lG2gznWJOlperlgZrkWDByexazcobM6khh4DRsV5Wgi2k2YVOqBLLpnYb/dwemSjijZGChbW4asxzMI2DA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T16:19:43.359246Z"},"content_sha256":"d37e129ec6bff794fddfbe808ef84461e665134fad35f57c6a54178fa290d440","schema_version":"1.0","event_id":"sha256:d37e129ec6bff794fddfbe808ef84461e665134fad35f57c6a54178fa290d440"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/UNJTQ6LUXOV4CUQKDPABYJELJ4/bundle.json","state_url":"https://pith.science/pith/UNJTQ6LUXOV4CUQKDPABYJELJ4/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/UNJTQ6LUXOV4CUQKDPABYJELJ4/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":"2026-08-08T16:19:43Z","links":{"resolver":"https://pith.science/pith/UNJTQ6LUXOV4CUQKDPABYJELJ4","bundle":"https://pith.science/pith/UNJTQ6LUXOV4CUQKDPABYJELJ4/bundle.json","state":"https://pith.science/pith/UNJTQ6LUXOV4CUQKDPABYJELJ4/state.json","well_known_bundle":"https://pith.science/.well-known/pith/UNJTQ6LUXOV4CUQKDPABYJELJ4/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:UNJTQ6LUXOV4CUQKDPABYJELJ4","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":"577f3c1fa96cf74c68a1baeb1d7676ea3ec056695ea27fd0e84f25e64a00187d","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-21T10:19:49Z","title_canon_sha256":"38483c5194f64868715adb827e3171e4ccaf228e89e1d607d29b0040f1a8dd44"},"schema_version":"1.0","source":{"id":"2505.15345","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.15345","created_at":"2026-07-05T11:08:21Z"},{"alias_kind":"arxiv_version","alias_value":"2505.15345v2","created_at":"2026-07-05T11:08:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.15345","created_at":"2026-07-05T11:08:21Z"},{"alias_kind":"pith_short_12","alias_value":"UNJTQ6LUXOV4","created_at":"2026-07-05T11:08:21Z"},{"alias_kind":"pith_short_16","alias_value":"UNJTQ6LUXOV4CUQK","created_at":"2026-07-05T11:08:21Z"},{"alias_kind":"pith_short_8","alias_value":"UNJTQ6LU","created_at":"2026-07-05T11:08:21Z"}],"graph_snapshots":[{"event_id":"sha256:d37e129ec6bff794fddfbe808ef84461e665134fad35f57c6a54178fa290d440","target":"graph","created_at":"2026-07-05T11:08:21Z","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/2505.15345/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Neural network architectures have a large impact in machine learning. In reinforcement learning, network architectures have remained notably simple, as changes often lead to small gains in performance. This work introduces a novel encoder architecture for pixel-based model-free reinforcement learning. The Hadamax (\\textbf{Hada}mard \\textbf{max}-pooling) encoder achieves state-of-the-art performance by max-pooling Hadamard products between GELU-activated parallel hidden layers. Based on the recent PQN algorithm, the Hadamax encoder achieves state-of-the-art model-free performance in the Atari-5","authors_text":"Jacob E. Kooi, Vincent Fran\\c{c}ois-Lavet, Zhao Yang","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-21T10:19:49Z","title":"Hadamax Encoding: Elevating Performance in Model-Free Atari"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.15345","kind":"arxiv","version":2},"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":"sha256:060559b9ec0a92f6c0fa2976d6b9469951bd0e7ab8704eeecd55fa0b01c3f8e9","target":"record","created_at":"2026-07-05T11:08:21Z","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":"577f3c1fa96cf74c68a1baeb1d7676ea3ec056695ea27fd0e84f25e64a00187d","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-21T10:19:49Z","title_canon_sha256":"38483c5194f64868715adb827e3171e4ccaf228e89e1d607d29b0040f1a8dd44"},"schema_version":"1.0","source":{"id":"2505.15345","kind":"arxiv","version":2}},"canonical_sha256":"a353387974bbabc1520a1bc01c248b4f0deb2dc58a6313b1569102fa4e30437e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a353387974bbabc1520a1bc01c248b4f0deb2dc58a6313b1569102fa4e30437e","first_computed_at":"2026-07-05T11:08:21.401284Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:08:21.401284Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"q1VU3Oc+x8fIDRQ0SaOrYa0wS1KyUg3ecnzppHrjF35rryFlmGmz8dS32UNNAFplCDn7t6755P+1zMN/0VKqBg==","signature_status":"signed_v1","signed_at":"2026-07-05T11:08:21.401780Z","signed_message":"canonical_sha256_bytes"},"source_id":"2505.15345","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:060559b9ec0a92f6c0fa2976d6b9469951bd0e7ab8704eeecd55fa0b01c3f8e9","sha256:d37e129ec6bff794fddfbe808ef84461e665134fad35f57c6a54178fa290d440"],"state_sha256":"39414f9d6f54b631f6d18bc530cfa7f77ade0d86ff0f8cbaae6d9057370bbfb1"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jhK6EX+pAnghRMyc/PU39S8Dks65qF1IY4oxj9GuBegITJU+LpurCupMzuyyCU8iLwWFhqQD6w1HYmWBYhHPBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T16:19:43.363658Z","bundle_sha256":"8f47234c0037fc26c491d3e2f61061e0075bc3ec6d171387de25315638889fd3"}}