{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:3GB7FEJKCQCNRQSWZBIBFRIBNO","short_pith_number":"pith:3GB7FEJK","canonical_record":{"source":{"id":"2605.19926","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-19T14:47:55Z","cross_cats_sorted":[],"title_canon_sha256":"6fc170e50090cbede513ac460893bd3fa0bf543a230e48391b1fb6925bca6198","abstract_canon_sha256":"ad1893970f9893526c7e70e991ffbb77af1c3685797a9d757bac96df0fa012f3"},"schema_version":"1.0"},"canonical_sha256":"d983f2912a1404d8c256c85012c5016bbfefeb7a57894a95fbc354571e639bc9","source":{"kind":"arxiv","id":"2605.19926","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.19926","created_at":"2026-05-20T02:05:55Z"},{"alias_kind":"arxiv_version","alias_value":"2605.19926v1","created_at":"2026-05-20T02:05:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.19926","created_at":"2026-05-20T02:05:55Z"},{"alias_kind":"pith_short_12","alias_value":"3GB7FEJKCQCN","created_at":"2026-05-20T02:05:55Z"},{"alias_kind":"pith_short_16","alias_value":"3GB7FEJKCQCNRQSW","created_at":"2026-05-20T02:05:55Z"},{"alias_kind":"pith_short_8","alias_value":"3GB7FEJK","created_at":"2026-05-20T02:05:55Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:3GB7FEJKCQCNRQSWZBIBFRIBNO","target":"record","payload":{"canonical_record":{"source":{"id":"2605.19926","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-19T14:47:55Z","cross_cats_sorted":[],"title_canon_sha256":"6fc170e50090cbede513ac460893bd3fa0bf543a230e48391b1fb6925bca6198","abstract_canon_sha256":"ad1893970f9893526c7e70e991ffbb77af1c3685797a9d757bac96df0fa012f3"},"schema_version":"1.0"},"canonical_sha256":"d983f2912a1404d8c256c85012c5016bbfefeb7a57894a95fbc354571e639bc9","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-20T02:05:55.601134Z","signature_b64":"I8dO4U6DRcbyMsShlb5bbzGHV/AJLEjUIGLgwFZAnA6cKXIbHPytJFEyp4w5ba4aVtFTifyPFKRMaRO9I+gQAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d983f2912a1404d8c256c85012c5016bbfefeb7a57894a95fbc354571e639bc9","last_reissued_at":"2026-05-20T02:05:55.600304Z","signature_status":"signed_v1","first_computed_at":"2026-05-20T02:05:55.600304Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.19926","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":"2026-05-20T02:05:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1OL4lD5nI7MmUMeK7secXVgtusEYYodspQEYq9LczTaRT4de3UsE7kMRu0RfmQiPxANx6aGpr7xFw3AOw7mvCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-22T18:20:28.777893Z"},"content_sha256":"7413ae90cdf679488207bc891aa1adb904d519150ba5b0853db3c5e8aa0c9899","schema_version":"1.0","event_id":"sha256:7413ae90cdf679488207bc891aa1adb904d519150ba5b0853db3c5e8aa0c9899"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:3GB7FEJKCQCNRQSWZBIBFRIBNO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"JAXenstein: Accelerated Benchmarking for First-Person Environments","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"George Konidaris, Ruo Yu Tao","submitted_at":"2026-05-19T14:47:55Z","abstract_excerpt":"The progression of reinforcement learning algorithms have been driven by challenging benchmarks. The rate in which a researcher can iterate on a problem setting directly impacts the speed of algorithm development. Modern machine learning has produced tools that allow for fast and scalable algorithm development like the JAX library. With the availability of these tools, a serious bottleneck in algorithm development is the availability of large and complex domains for experimentation. Most notably, the JAX reinforcement learning ecosystem does not have any benchmarks that test visual first-perso"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.19926","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/2605.19926/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":"2026-05-20T02:05:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QIEwmhXMyP1ilMEExtWGXKsK+jYu1w/jeNz3cPv4RTzPq04P9PNydW9l7oOLIAfhaYkUOGr53O8LxhIZg506Cg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-22T18:20:28.778597Z"},"content_sha256":"c43aca30a696476205a9cdf705b038fb361b3be0e7e1121fd49401b59a327a66","schema_version":"1.0","event_id":"sha256:c43aca30a696476205a9cdf705b038fb361b3be0e7e1121fd49401b59a327a66"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/3GB7FEJKCQCNRQSWZBIBFRIBNO/bundle.json","state_url":"https://pith.science/pith/3GB7FEJKCQCNRQSWZBIBFRIBNO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/3GB7FEJKCQCNRQSWZBIBFRIBNO/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":"2026-05-22T18:20:28Z","links":{"resolver":"https://pith.science/pith/3GB7FEJKCQCNRQSWZBIBFRIBNO","bundle":"https://pith.science/pith/3GB7FEJKCQCNRQSWZBIBFRIBNO/bundle.json","state":"https://pith.science/pith/3GB7FEJKCQCNRQSWZBIBFRIBNO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/3GB7FEJKCQCNRQSWZBIBFRIBNO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:3GB7FEJKCQCNRQSWZBIBFRIBNO","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":"ad1893970f9893526c7e70e991ffbb77af1c3685797a9d757bac96df0fa012f3","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-19T14:47:55Z","title_canon_sha256":"6fc170e50090cbede513ac460893bd3fa0bf543a230e48391b1fb6925bca6198"},"schema_version":"1.0","source":{"id":"2605.19926","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.19926","created_at":"2026-05-20T02:05:55Z"},{"alias_kind":"arxiv_version","alias_value":"2605.19926v1","created_at":"2026-05-20T02:05:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.19926","created_at":"2026-05-20T02:05:55Z"},{"alias_kind":"pith_short_12","alias_value":"3GB7FEJKCQCN","created_at":"2026-05-20T02:05:55Z"},{"alias_kind":"pith_short_16","alias_value":"3GB7FEJKCQCNRQSW","created_at":"2026-05-20T02:05:55Z"},{"alias_kind":"pith_short_8","alias_value":"3GB7FEJK","created_at":"2026-05-20T02:05:55Z"}],"graph_snapshots":[{"event_id":"sha256:c43aca30a696476205a9cdf705b038fb361b3be0e7e1121fd49401b59a327a66","target":"graph","created_at":"2026-05-20T02:05:55Z","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/2605.19926/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The progression of reinforcement learning algorithms have been driven by challenging benchmarks. The rate in which a researcher can iterate on a problem setting directly impacts the speed of algorithm development. Modern machine learning has produced tools that allow for fast and scalable algorithm development like the JAX library. With the availability of these tools, a serious bottleneck in algorithm development is the availability of large and complex domains for experimentation. Most notably, the JAX reinforcement learning ecosystem does not have any benchmarks that test visual first-perso","authors_text":"George Konidaris, Ruo Yu Tao","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-19T14:47:55Z","title":"JAXenstein: Accelerated Benchmarking for First-Person Environments"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.19926","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":"sha256:7413ae90cdf679488207bc891aa1adb904d519150ba5b0853db3c5e8aa0c9899","target":"record","created_at":"2026-05-20T02:05:55Z","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":"ad1893970f9893526c7e70e991ffbb77af1c3685797a9d757bac96df0fa012f3","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-19T14:47:55Z","title_canon_sha256":"6fc170e50090cbede513ac460893bd3fa0bf543a230e48391b1fb6925bca6198"},"schema_version":"1.0","source":{"id":"2605.19926","kind":"arxiv","version":1}},"canonical_sha256":"d983f2912a1404d8c256c85012c5016bbfefeb7a57894a95fbc354571e639bc9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d983f2912a1404d8c256c85012c5016bbfefeb7a57894a95fbc354571e639bc9","first_computed_at":"2026-05-20T02:05:55.600304Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-20T02:05:55.600304Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"I8dO4U6DRcbyMsShlb5bbzGHV/AJLEjUIGLgwFZAnA6cKXIbHPytJFEyp4w5ba4aVtFTifyPFKRMaRO9I+gQAQ==","signature_status":"signed_v1","signed_at":"2026-05-20T02:05:55.601134Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.19926","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7413ae90cdf679488207bc891aa1adb904d519150ba5b0853db3c5e8aa0c9899","sha256:c43aca30a696476205a9cdf705b038fb361b3be0e7e1121fd49401b59a327a66"],"state_sha256":"f947ae6b8f40ea4674cbc5dd28f97da0a1ac3cf885da93f5a5a3854959de1250"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ykblcuTTSQZzei/Bxqz16auz3cSFrMwEOnbDCBuMePYrXplCSHmP1xM9gE40TP+0Ep4iifl4RWFRgdDIBJeUBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-22T18:20:28.781853Z","bundle_sha256":"cf39f265c057818272d8517e12f9fd93a91a5418d63cc2ac61daa006b8a8d06c"}}