{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:LT6LX5A3QU36N7S5TYA7MUVN42","short_pith_number":"pith:LT6LX5A3","canonical_record":{"source":{"id":"2605.14742","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-05-14T12:10:27Z","cross_cats_sorted":["cs.RO"],"title_canon_sha256":"86897d130e297671775a7e2298a4adb73c5239195a5d29508e111d1aa3355a29","abstract_canon_sha256":"5140e1c1aad4487640c12390edc028491fbb936e54972bf62cff0a7ded10f25f"},"schema_version":"1.0"},"canonical_sha256":"5cfcbbf41b8537e6fe5d9e01f652ade6a375e7a8467a6053b9eb0537416c5879","source":{"kind":"arxiv","id":"2605.14742","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.14742","created_at":"2026-05-17T23:38:58Z"},{"alias_kind":"arxiv_version","alias_value":"2605.14742v1","created_at":"2026-05-17T23:38:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.14742","created_at":"2026-05-17T23:38:58Z"},{"alias_kind":"pith_short_12","alias_value":"LT6LX5A3QU36","created_at":"2026-05-18T12:33:37Z"},{"alias_kind":"pith_short_16","alias_value":"LT6LX5A3QU36N7S5","created_at":"2026-05-18T12:33:37Z"},{"alias_kind":"pith_short_8","alias_value":"LT6LX5A3","created_at":"2026-05-18T12:33:37Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:LT6LX5A3QU36N7S5TYA7MUVN42","target":"record","payload":{"canonical_record":{"source":{"id":"2605.14742","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-05-14T12:10:27Z","cross_cats_sorted":["cs.RO"],"title_canon_sha256":"86897d130e297671775a7e2298a4adb73c5239195a5d29508e111d1aa3355a29","abstract_canon_sha256":"5140e1c1aad4487640c12390edc028491fbb936e54972bf62cff0a7ded10f25f"},"schema_version":"1.0"},"canonical_sha256":"5cfcbbf41b8537e6fe5d9e01f652ade6a375e7a8467a6053b9eb0537416c5879","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:38:58.928744Z","signature_b64":"jnTX5F69+vckDowLJqHcGACkfhSVYUyF0N3braLpTxN4pJ1bTdN/qmYMmB/8mvUBfaXwe6pXF/EIr98AQDNeAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5cfcbbf41b8537e6fe5d9e01f652ade6a375e7a8467a6053b9eb0537416c5879","last_reissued_at":"2026-05-17T23:38:58.928009Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:38:58.928009Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.14742","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":"2026-05-17T23:38:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7xhnXBlW6NCHH6Sje+dnXV3pFTMV16nghsrklH9yLqCJSHONJ8ddO6yiEOYxdBFtDo3oETDkTIBLyKEXYU94AA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-05T12:34:06.612516Z"},"content_sha256":"53199a96d63be5f3d1165128cacc5beba3e92131b32926b919500ce6a8429cf5","schema_version":"1.0","event_id":"sha256:53199a96d63be5f3d1165128cacc5beba3e92131b32926b919500ce6a8429cf5"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:LT6LX5A3QU36N7S5TYA7MUVN42","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"EARL: Towards a Unified Analysis-Guided Reinforcement Learning Framework for Egocentric Interaction Reasoning and Pixel Grounding","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.RO"],"primary_cat":"cs.CV","authors_text":"Lap-Pui Chau, Lei Yao, Xinshen Zhang, Yi Wang, Yuejiao Su, Zhen Ye","submitted_at":"2026-05-14T12:10:27Z","abstract_excerpt":"Understanding human--environment interactions from egocentric vision is essential for assistive robotics and embodied intelligent agents, yet existing multimodal large language models (MLLMs) still struggle with accurate interaction reasoning and fine-grained pixel grounding. To this end, this paper introduces EARL, an Egocentric Analysis-guided Reinforcement Learning framework that explicitly transfers coarse interaction semantics to query-oriented answering and grounding. Specifically, EARL adopts a two-stage parsing framework including coarse-grained interpretation and fine-grained response"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.14742","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":""},"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":"2026-05-17T23:38:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"706DwheU+3rKVUrO7KZTrIAFSztiqSjThxdasTruhbAiAjUAThA2pEiP4C0HgUwqEHZdvd8lNFZyJLfGWPAbDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-05T12:34:06.612867Z"},"content_sha256":"2cfb38f9487c816b9db9cad96fb3320a7da5072bd0b1476888946940b494a8cb","schema_version":"1.0","event_id":"sha256:2cfb38f9487c816b9db9cad96fb3320a7da5072bd0b1476888946940b494a8cb"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LT6LX5A3QU36N7S5TYA7MUVN42/bundle.json","state_url":"https://pith.science/pith/LT6LX5A3QU36N7S5TYA7MUVN42/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LT6LX5A3QU36N7S5TYA7MUVN42/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":"2026-06-05T12:34:06Z","links":{"resolver":"https://pith.science/pith/LT6LX5A3QU36N7S5TYA7MUVN42","bundle":"https://pith.science/pith/LT6LX5A3QU36N7S5TYA7MUVN42/bundle.json","state":"https://pith.science/pith/LT6LX5A3QU36N7S5TYA7MUVN42/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LT6LX5A3QU36N7S5TYA7MUVN42/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:LT6LX5A3QU36N7S5TYA7MUVN42","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":"5140e1c1aad4487640c12390edc028491fbb936e54972bf62cff0a7ded10f25f","cross_cats_sorted":["cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-05-14T12:10:27Z","title_canon_sha256":"86897d130e297671775a7e2298a4adb73c5239195a5d29508e111d1aa3355a29"},"schema_version":"1.0","source":{"id":"2605.14742","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.14742","created_at":"2026-05-17T23:38:58Z"},{"alias_kind":"arxiv_version","alias_value":"2605.14742v1","created_at":"2026-05-17T23:38:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.14742","created_at":"2026-05-17T23:38:58Z"},{"alias_kind":"pith_short_12","alias_value":"LT6LX5A3QU36","created_at":"2026-05-18T12:33:37Z"},{"alias_kind":"pith_short_16","alias_value":"LT6LX5A3QU36N7S5","created_at":"2026-05-18T12:33:37Z"},{"alias_kind":"pith_short_8","alias_value":"LT6LX5A3","created_at":"2026-05-18T12:33:37Z"}],"graph_snapshots":[{"event_id":"sha256:2cfb38f9487c816b9db9cad96fb3320a7da5072bd0b1476888946940b494a8cb","target":"graph","created_at":"2026-05-17T23:38:58Z","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"},"paper":{"abstract_excerpt":"Understanding human--environment interactions from egocentric vision is essential for assistive robotics and embodied intelligent agents, yet existing multimodal large language models (MLLMs) still struggle with accurate interaction reasoning and fine-grained pixel grounding. To this end, this paper introduces EARL, an Egocentric Analysis-guided Reinforcement Learning framework that explicitly transfers coarse interaction semantics to query-oriented answering and grounding. Specifically, EARL adopts a two-stage parsing framework including coarse-grained interpretation and fine-grained response","authors_text":"Lap-Pui Chau, Lei Yao, Xinshen Zhang, Yi Wang, Yuejiao Su, Zhen Ye","cross_cats":["cs.RO"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-05-14T12:10:27Z","title":"EARL: Towards a Unified Analysis-Guided Reinforcement Learning Framework for Egocentric Interaction Reasoning and Pixel Grounding"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.14742","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":"sha256:53199a96d63be5f3d1165128cacc5beba3e92131b32926b919500ce6a8429cf5","target":"record","created_at":"2026-05-17T23:38:58Z","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":"5140e1c1aad4487640c12390edc028491fbb936e54972bf62cff0a7ded10f25f","cross_cats_sorted":["cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-05-14T12:10:27Z","title_canon_sha256":"86897d130e297671775a7e2298a4adb73c5239195a5d29508e111d1aa3355a29"},"schema_version":"1.0","source":{"id":"2605.14742","kind":"arxiv","version":1}},"canonical_sha256":"5cfcbbf41b8537e6fe5d9e01f652ade6a375e7a8467a6053b9eb0537416c5879","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5cfcbbf41b8537e6fe5d9e01f652ade6a375e7a8467a6053b9eb0537416c5879","first_computed_at":"2026-05-17T23:38:58.928009Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:38:58.928009Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"jnTX5F69+vckDowLJqHcGACkfhSVYUyF0N3braLpTxN4pJ1bTdN/qmYMmB/8mvUBfaXwe6pXF/EIr98AQDNeAw==","signature_status":"signed_v1","signed_at":"2026-05-17T23:38:58.928744Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.14742","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:53199a96d63be5f3d1165128cacc5beba3e92131b32926b919500ce6a8429cf5","sha256:2cfb38f9487c816b9db9cad96fb3320a7da5072bd0b1476888946940b494a8cb"],"state_sha256":"992e170f4fb003d9bb2700a38f615aa181249262d213c10ecd11a6e2247a8a98"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4RmqM2oecCPV+4QCykNKUtBN499jDjawb5my3JcJbFfL0kaUnfNdo+6acPeiTL1hEF073NIosZh0NBkbRRH7BA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-05T12:34:06.614873Z","bundle_sha256":"889424402fea81e7372df8eaf1ba70a24df59cceb0c7439ff31df63ae55b5908"}}