{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:RQ6DGBCJAEFI66K5L66E2RPEWS","short_pith_number":"pith:RQ6DGBCJ","canonical_record":{"source":{"id":"2608.01314","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-08-02T15:31:31Z","cross_cats_sorted":[],"title_canon_sha256":"cc945da21e704a0c929185d5317b8341b641121cf620a4a9605a3526e7e7774b","abstract_canon_sha256":"f726353a8e32134dd3ef67d3be58b4af96ae6729fd35535751aad2426badb177"},"schema_version":"1.0"},"canonical_sha256":"8c3c330449010a8f795d5fbc4d45e4b4ba6eee96872121e276f1eb521e330c25","source":{"kind":"arxiv","id":"2608.01314","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2608.01314","created_at":"2026-08-04T02:03:53Z"},{"alias_kind":"arxiv_version","alias_value":"2608.01314v1","created_at":"2026-08-04T02:03:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2608.01314","created_at":"2026-08-04T02:03:53Z"},{"alias_kind":"pith_short_12","alias_value":"RQ6DGBCJAEFI","created_at":"2026-08-04T02:03:53Z"},{"alias_kind":"pith_short_16","alias_value":"RQ6DGBCJAEFI66K5","created_at":"2026-08-04T02:03:53Z"},{"alias_kind":"pith_short_8","alias_value":"RQ6DGBCJ","created_at":"2026-08-04T02:03:53Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:RQ6DGBCJAEFI66K5L66E2RPEWS","target":"record","payload":{"canonical_record":{"source":{"id":"2608.01314","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-08-02T15:31:31Z","cross_cats_sorted":[],"title_canon_sha256":"cc945da21e704a0c929185d5317b8341b641121cf620a4a9605a3526e7e7774b","abstract_canon_sha256":"f726353a8e32134dd3ef67d3be58b4af96ae6729fd35535751aad2426badb177"},"schema_version":"1.0"},"canonical_sha256":"8c3c330449010a8f795d5fbc4d45e4b4ba6eee96872121e276f1eb521e330c25","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-08-04T02:03:53.528408Z","signature_b64":"E3BA34iZTsG/jBLNzuxaJHo8xpF5bEcY5HcE2uWTyy/yptmXaxoxeXVCUttw2+XWEI/m9udjgSnwY0yAKkdrBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8c3c330449010a8f795d5fbc4d45e4b4ba6eee96872121e276f1eb521e330c25","last_reissued_at":"2026-08-04T02:03:53.526617Z","signature_status":"signed_v1","first_computed_at":"2026-08-04T02:03:53.526617Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2608.01314","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":"2026-08-04T02:03:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6nCC4bAkeUxLuINzuIYe0sztVrWADjYxzrv2TzDZKrrbDAIS7CjYSIOIu4c/Xe8lDiccJAH5UkgzmT6U1KRqAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T00:51:05.249490Z"},"content_sha256":"3e07defcf0a2a31c822d021b7ad904a9a6ad13bdc2fee1b53993730c3645ac80","schema_version":"1.0","event_id":"sha256:3e07defcf0a2a31c822d021b7ad904a9a6ad13bdc2fee1b53993730c3645ac80"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:RQ6DGBCJAEFI66K5L66E2RPEWS","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Remember-R1: Mitigating Long-Context Visual Forgetting through Reinforcement Learning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Botong Geng, Jiafei Wu, Jianmin Chen, Jiaqi Tang, Lei Zhang, Qianzhou Wang, Qifeng Chen, Wei Wei, Xiaogang Xu, Yingying Yan, Yuyang Xia, Zhe Liu","submitted_at":"2026-08-02T15:31:31Z","abstract_excerpt":"Multimodal large language models (MLLMs) increasingly rely on long chain-of-thought reasoning for complex tasks. However, as reasoning sequences lengthen, models may gradually rely less on visual evidence and more on accumulated textual context, leading to visual forgetting. Existing approaches do not directly constrain how visual evidence is used and maintained along the original reasoning trajectory, leaving long-context visual forgetting insufficiently addressed. To address this issue, we propose Remember-R1, a reinforcement learning framework that mitigates long-context visual forgetting b"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.01314","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/2608.01314/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":"2026-08-04T02:03:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gVvrzHZLrxag/loOIo8QlfAMXI52KmbKOPd50Hq/cAoByeovf41dqcyruvx6+sSWQddzhtrueJyIZFbEeJ98AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T00:51:05.250224Z"},"content_sha256":"ad5e50025ef4a4be6f85444789da1949e521e77c9f3e133583355f8ee83b461e","schema_version":"1.0","event_id":"sha256:ad5e50025ef4a4be6f85444789da1949e521e77c9f3e133583355f8ee83b461e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/RQ6DGBCJAEFI66K5L66E2RPEWS/bundle.json","state_url":"https://pith.science/pith/RQ6DGBCJAEFI66K5L66E2RPEWS/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/RQ6DGBCJAEFI66K5L66E2RPEWS/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":"2026-08-18T00:51:05Z","links":{"resolver":"https://pith.science/pith/RQ6DGBCJAEFI66K5L66E2RPEWS","bundle":"https://pith.science/pith/RQ6DGBCJAEFI66K5L66E2RPEWS/bundle.json","state":"https://pith.science/pith/RQ6DGBCJAEFI66K5L66E2RPEWS/state.json","well_known_bundle":"https://pith.science/.well-known/pith/RQ6DGBCJAEFI66K5L66E2RPEWS/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:RQ6DGBCJAEFI66K5L66E2RPEWS","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":"f726353a8e32134dd3ef67d3be58b4af96ae6729fd35535751aad2426badb177","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-08-02T15:31:31Z","title_canon_sha256":"cc945da21e704a0c929185d5317b8341b641121cf620a4a9605a3526e7e7774b"},"schema_version":"1.0","source":{"id":"2608.01314","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2608.01314","created_at":"2026-08-04T02:03:53Z"},{"alias_kind":"arxiv_version","alias_value":"2608.01314v1","created_at":"2026-08-04T02:03:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2608.01314","created_at":"2026-08-04T02:03:53Z"},{"alias_kind":"pith_short_12","alias_value":"RQ6DGBCJAEFI","created_at":"2026-08-04T02:03:53Z"},{"alias_kind":"pith_short_16","alias_value":"RQ6DGBCJAEFI66K5","created_at":"2026-08-04T02:03:53Z"},{"alias_kind":"pith_short_8","alias_value":"RQ6DGBCJ","created_at":"2026-08-04T02:03:53Z"}],"graph_snapshots":[{"event_id":"sha256:ad5e50025ef4a4be6f85444789da1949e521e77c9f3e133583355f8ee83b461e","target":"graph","created_at":"2026-08-04T02:03:53Z","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/2608.01314/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Multimodal large language models (MLLMs) increasingly rely on long chain-of-thought reasoning for complex tasks. However, as reasoning sequences lengthen, models may gradually rely less on visual evidence and more on accumulated textual context, leading to visual forgetting. Existing approaches do not directly constrain how visual evidence is used and maintained along the original reasoning trajectory, leaving long-context visual forgetting insufficiently addressed. To address this issue, we propose Remember-R1, a reinforcement learning framework that mitigates long-context visual forgetting b","authors_text":"Botong Geng, Jiafei Wu, Jianmin Chen, Jiaqi Tang, Lei Zhang, Qianzhou Wang, Qifeng Chen, Wei Wei, Xiaogang Xu, Yingying Yan, Yuyang Xia, Zhe Liu","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-08-02T15:31:31Z","title":"Remember-R1: Mitigating Long-Context Visual Forgetting through Reinforcement Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.01314","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":"sha256:3e07defcf0a2a31c822d021b7ad904a9a6ad13bdc2fee1b53993730c3645ac80","target":"record","created_at":"2026-08-04T02:03:53Z","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":"f726353a8e32134dd3ef67d3be58b4af96ae6729fd35535751aad2426badb177","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-08-02T15:31:31Z","title_canon_sha256":"cc945da21e704a0c929185d5317b8341b641121cf620a4a9605a3526e7e7774b"},"schema_version":"1.0","source":{"id":"2608.01314","kind":"arxiv","version":1}},"canonical_sha256":"8c3c330449010a8f795d5fbc4d45e4b4ba6eee96872121e276f1eb521e330c25","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8c3c330449010a8f795d5fbc4d45e4b4ba6eee96872121e276f1eb521e330c25","first_computed_at":"2026-08-04T02:03:53.526617Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-08-04T02:03:53.526617Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"E3BA34iZTsG/jBLNzuxaJHo8xpF5bEcY5HcE2uWTyy/yptmXaxoxeXVCUttw2+XWEI/m9udjgSnwY0yAKkdrBg==","signature_status":"signed_v1","signed_at":"2026-08-04T02:03:53.528408Z","signed_message":"canonical_sha256_bytes"},"source_id":"2608.01314","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3e07defcf0a2a31c822d021b7ad904a9a6ad13bdc2fee1b53993730c3645ac80","sha256:ad5e50025ef4a4be6f85444789da1949e521e77c9f3e133583355f8ee83b461e"],"state_sha256":"0dda0802a0401493b221c5026fadffd5b6ded068c1beabd3363c14fdf0de520a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KC8jvx7VH236dSz7LoBB3NbwtdLCkIp0Kt8Y2oP7Rt5sn4qw4tM2v4DQTPacyVWREdO6QdRcABTp1292JYUmCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-18T00:51:05.255982Z","bundle_sha256":"755c85bb7a2b2dfca7ef227ef6c9b26860fbbb8772dff6a1cca814d7278ecef1"}}