{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:RNFFU4L5PVPMUWG3VCG45FYLDL","short_pith_number":"pith:RNFFU4L5","canonical_record":{"source":{"id":"2507.08548","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-07-11T12:53:19Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"090e82db41f26364f5b82bdad0c7daa3e10ec7cc0d916cd9ca155c80d1032b8a","abstract_canon_sha256":"fa0b8f37c31348d01a4c9778a573a027ec40b4b58f299032b3dd4523216221a5"},"schema_version":"1.0"},"canonical_sha256":"8b4a5a717d7d5eca58dba88dce970b1ad5e16591cd563909be3ded6e4ea0cc7f","source":{"kind":"arxiv","id":"2507.08548","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.08548","created_at":"2026-07-05T11:35:41Z"},{"alias_kind":"arxiv_version","alias_value":"2507.08548v1","created_at":"2026-07-05T11:35:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.08548","created_at":"2026-07-05T11:35:41Z"},{"alias_kind":"pith_short_12","alias_value":"RNFFU4L5PVPM","created_at":"2026-07-05T11:35:41Z"},{"alias_kind":"pith_short_16","alias_value":"RNFFU4L5PVPMUWG3","created_at":"2026-07-05T11:35:41Z"},{"alias_kind":"pith_short_8","alias_value":"RNFFU4L5","created_at":"2026-07-05T11:35:41Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:RNFFU4L5PVPMUWG3VCG45FYLDL","target":"record","payload":{"canonical_record":{"source":{"id":"2507.08548","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-07-11T12:53:19Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"090e82db41f26364f5b82bdad0c7daa3e10ec7cc0d916cd9ca155c80d1032b8a","abstract_canon_sha256":"fa0b8f37c31348d01a4c9778a573a027ec40b4b58f299032b3dd4523216221a5"},"schema_version":"1.0"},"canonical_sha256":"8b4a5a717d7d5eca58dba88dce970b1ad5e16591cd563909be3ded6e4ea0cc7f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:35:41.855743Z","signature_b64":"u2/XAD72jmv9nZWf9DIkPhvh02iypCKg4PE21foJHgjs5AwzdGgpwst65TzpLucrA5ILqdGTGAXPYFzx8doxAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8b4a5a717d7d5eca58dba88dce970b1ad5e16591cd563909be3ded6e4ea0cc7f","last_reissued_at":"2026-07-05T11:35:41.855239Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:35:41.855239Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2507.08548","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":"2026-07-05T11:35:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"b4KrovTNTTCjA3l2YzR8cvrsujAYLzZsZro2wAsq/vuIwRWo8sza1s/RTIW2o7ceDiIBKkvMAXVLmO7wSMi4Ag==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T03:32:51.953215Z"},"content_sha256":"20d214273d90056a47914aaf0eee4c8981a348a3e9ff18eb3dc08a37914ac300","schema_version":"1.0","event_id":"sha256:20d214273d90056a47914aaf0eee4c8981a348a3e9ff18eb3dc08a37914ac300"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:RNFFU4L5PVPMUWG3VCG45FYLDL","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"SAM2RL: Towards Reinforcement Learning Memory Control in Segment Anything Model 2","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Alen Adamyan, Klara Janouskova, Martin Schmid, Matej Straka, Tom\\'a\\v{s} \\v{C}\\'i\\v{z}ek","submitted_at":"2025-07-11T12:53:19Z","abstract_excerpt":"Segment Anything Model 2 (SAM 2) has demonstrated strong performance in object segmentation tasks and has become the state-of-the-art for visual object tracking. The model stores information from previous frames in a memory bank, enabling temporal consistency across video sequences. Recent methods augment SAM 2 with hand-crafted update rules to better handle distractors, occlusions, and object motion. We propose a fundamentally different approach using reinforcement learning for optimizing memory updates in SAM 2 by framing memory control as a sequential decision-making problem. In an overfitt"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.08548","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/2507.08548/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":"2026-07-05T11:35:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qeFPIG4xtjmuzBSglRWFWXIorurGwqwT4DPyfppQWjDdEK/Q12ibLC3TLz3NQ9q8WKCw59iMFYELCaOowCmGCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T03:32:51.954136Z"},"content_sha256":"cdea3d75402d1a5efe835f3a87ed8c4aa186e876539e7e865c43d7c026fe2440","schema_version":"1.0","event_id":"sha256:cdea3d75402d1a5efe835f3a87ed8c4aa186e876539e7e865c43d7c026fe2440"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/RNFFU4L5PVPMUWG3VCG45FYLDL/bundle.json","state_url":"https://pith.science/pith/RNFFU4L5PVPMUWG3VCG45FYLDL/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/RNFFU4L5PVPMUWG3VCG45FYLDL/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":"2026-08-07T03:32:51Z","links":{"resolver":"https://pith.science/pith/RNFFU4L5PVPMUWG3VCG45FYLDL","bundle":"https://pith.science/pith/RNFFU4L5PVPMUWG3VCG45FYLDL/bundle.json","state":"https://pith.science/pith/RNFFU4L5PVPMUWG3VCG45FYLDL/state.json","well_known_bundle":"https://pith.science/.well-known/pith/RNFFU4L5PVPMUWG3VCG45FYLDL/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:RNFFU4L5PVPMUWG3VCG45FYLDL","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":"fa0b8f37c31348d01a4c9778a573a027ec40b4b58f299032b3dd4523216221a5","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-07-11T12:53:19Z","title_canon_sha256":"090e82db41f26364f5b82bdad0c7daa3e10ec7cc0d916cd9ca155c80d1032b8a"},"schema_version":"1.0","source":{"id":"2507.08548","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.08548","created_at":"2026-07-05T11:35:41Z"},{"alias_kind":"arxiv_version","alias_value":"2507.08548v1","created_at":"2026-07-05T11:35:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.08548","created_at":"2026-07-05T11:35:41Z"},{"alias_kind":"pith_short_12","alias_value":"RNFFU4L5PVPM","created_at":"2026-07-05T11:35:41Z"},{"alias_kind":"pith_short_16","alias_value":"RNFFU4L5PVPMUWG3","created_at":"2026-07-05T11:35:41Z"},{"alias_kind":"pith_short_8","alias_value":"RNFFU4L5","created_at":"2026-07-05T11:35:41Z"}],"graph_snapshots":[{"event_id":"sha256:cdea3d75402d1a5efe835f3a87ed8c4aa186e876539e7e865c43d7c026fe2440","target":"graph","created_at":"2026-07-05T11:35:41Z","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/2507.08548/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Segment Anything Model 2 (SAM 2) has demonstrated strong performance in object segmentation tasks and has become the state-of-the-art for visual object tracking. The model stores information from previous frames in a memory bank, enabling temporal consistency across video sequences. Recent methods augment SAM 2 with hand-crafted update rules to better handle distractors, occlusions, and object motion. We propose a fundamentally different approach using reinforcement learning for optimizing memory updates in SAM 2 by framing memory control as a sequential decision-making problem. In an overfitt","authors_text":"Alen Adamyan, Klara Janouskova, Martin Schmid, Matej Straka, Tom\\'a\\v{s} \\v{C}\\'i\\v{z}ek","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-07-11T12:53:19Z","title":"SAM2RL: Towards Reinforcement Learning Memory Control in Segment Anything Model 2"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.08548","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":"sha256:20d214273d90056a47914aaf0eee4c8981a348a3e9ff18eb3dc08a37914ac300","target":"record","created_at":"2026-07-05T11:35:41Z","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":"fa0b8f37c31348d01a4c9778a573a027ec40b4b58f299032b3dd4523216221a5","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-07-11T12:53:19Z","title_canon_sha256":"090e82db41f26364f5b82bdad0c7daa3e10ec7cc0d916cd9ca155c80d1032b8a"},"schema_version":"1.0","source":{"id":"2507.08548","kind":"arxiv","version":1}},"canonical_sha256":"8b4a5a717d7d5eca58dba88dce970b1ad5e16591cd563909be3ded6e4ea0cc7f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8b4a5a717d7d5eca58dba88dce970b1ad5e16591cd563909be3ded6e4ea0cc7f","first_computed_at":"2026-07-05T11:35:41.855239Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:35:41.855239Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"u2/XAD72jmv9nZWf9DIkPhvh02iypCKg4PE21foJHgjs5AwzdGgpwst65TzpLucrA5ILqdGTGAXPYFzx8doxAw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:35:41.855743Z","signed_message":"canonical_sha256_bytes"},"source_id":"2507.08548","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:20d214273d90056a47914aaf0eee4c8981a348a3e9ff18eb3dc08a37914ac300","sha256:cdea3d75402d1a5efe835f3a87ed8c4aa186e876539e7e865c43d7c026fe2440"],"state_sha256":"533a147aa8d1b45e351d270b2b5042d0a027b2c02aeb1593ee172a714ff0fc91"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"CtWmQ1mxxHOC0O5RVYV+556i7IejJwIRyL0D9vmcCoSrB49U6cMnT9iEXiJikkDaXmhtlInqRfGvN/idqkfTCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T03:32:51.965439Z","bundle_sha256":"efc9cc8f104b3b1402800765c3595c3e1a7114d88fc1805eae09df2de373c98d"}}