{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:OYPHQXXRPNSKMGYDAEQ74M3LD3","short_pith_number":"pith:OYPHQXXR","canonical_record":{"source":{"id":"2408.16967","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-08-30T02:01:56Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"ee62f2d6313374e702524179df8fab70d7300285e37cda62ec0e1097b0e080d1","abstract_canon_sha256":"8b7ccdceb5dd44d4481c13c7dab6a0fc1323ae8ca94124e4bb6b43ff4ce307d2"},"schema_version":"1.0"},"canonical_sha256":"761e785ef17b64a61b030121fe336b1ee6da7d10f9de70392fad8ebe29b7ea97","source":{"kind":"arxiv","id":"2408.16967","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.16967","created_at":"2026-07-05T09:01:08Z"},{"alias_kind":"arxiv_version","alias_value":"2408.16967v1","created_at":"2026-07-05T09:01:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.16967","created_at":"2026-07-05T09:01:08Z"},{"alias_kind":"pith_short_12","alias_value":"OYPHQXXRPNSK","created_at":"2026-07-05T09:01:08Z"},{"alias_kind":"pith_short_16","alias_value":"OYPHQXXRPNSKMGYD","created_at":"2026-07-05T09:01:08Z"},{"alias_kind":"pith_short_8","alias_value":"OYPHQXXR","created_at":"2026-07-05T09:01:08Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:OYPHQXXRPNSKMGYDAEQ74M3LD3","target":"record","payload":{"canonical_record":{"source":{"id":"2408.16967","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-08-30T02:01:56Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"ee62f2d6313374e702524179df8fab70d7300285e37cda62ec0e1097b0e080d1","abstract_canon_sha256":"8b7ccdceb5dd44d4481c13c7dab6a0fc1323ae8ca94124e4bb6b43ff4ce307d2"},"schema_version":"1.0"},"canonical_sha256":"761e785ef17b64a61b030121fe336b1ee6da7d10f9de70392fad8ebe29b7ea97","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:01:08.891761Z","signature_b64":"KKAHTvcKmhKbssp1uR9LIIsd8z7Zvcsj16G8XqpuYDsJrDLcR4FjmueAdCpiA4kmR3/bX0Po2QVTFduQ5qXkCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"761e785ef17b64a61b030121fe336b1ee6da7d10f9de70392fad8ebe29b7ea97","last_reissued_at":"2026-07-05T09:01:08.891301Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:01:08.891301Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2408.16967","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":"2026-07-05T09:01:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"d8rzIWZirOHO/SrwjcuCDarS9098g3hz7WDaGKcS4z8ftfK7ZGTtStjuJWwg8Z27RkQ2dvfxhEJ+vF6fk/5mBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T20:41:09.254978Z"},"content_sha256":"6e62f48b105fc6cc411a94b52c66ee1d9ec17e8f1924ada926a7acaa6a1bb597","schema_version":"1.0","event_id":"sha256:6e62f48b105fc6cc411a94b52c66ee1d9ec17e8f1924ada926a7acaa6a1bb597"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:OYPHQXXRPNSKMGYDAEQ74M3LD3","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"MemLong: Memory-Augmented Retrieval for Long Text Modeling","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Juntao Li, Kehai Chen, Min Zhang, Weijie Liu, Zecheng Tang","submitted_at":"2024-08-30T02:01:56Z","abstract_excerpt":"Recent advancements in Large Language Models (LLMs) have yielded remarkable success across diverse fields. However, handling long contexts remains a significant challenge for LLMs due to the quadratic time and space complexity of attention mechanisms and the growing memory consumption of the key-value cache during generation. This work introduces MemLong: Memory-Augmented Retrieval for Long Text Generation, a method designed to enhance the capabilities of long-context language modeling by utilizing an external retriever for historical information retrieval. MemLong combines a non-differentiabl"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.16967","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/2408.16967/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":"2026-07-05T09:01:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Wc30rrI7bEVS+16VjHjfTxYy0T2Bt5p9missGTN/o3wudbfs1mEoV2XXHTYvzkilkcKj64mGzaIXFwmpBJ9LBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T20:41:09.255550Z"},"content_sha256":"72811d1ef5ac07dbb0f148b3991eb8afe32cba5d94d87bd740a128dace2cfa5e","schema_version":"1.0","event_id":"sha256:72811d1ef5ac07dbb0f148b3991eb8afe32cba5d94d87bd740a128dace2cfa5e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/OYPHQXXRPNSKMGYDAEQ74M3LD3/bundle.json","state_url":"https://pith.science/pith/OYPHQXXRPNSKMGYDAEQ74M3LD3/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/OYPHQXXRPNSKMGYDAEQ74M3LD3/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":"2026-08-03T20:41:09Z","links":{"resolver":"https://pith.science/pith/OYPHQXXRPNSKMGYDAEQ74M3LD3","bundle":"https://pith.science/pith/OYPHQXXRPNSKMGYDAEQ74M3LD3/bundle.json","state":"https://pith.science/pith/OYPHQXXRPNSKMGYDAEQ74M3LD3/state.json","well_known_bundle":"https://pith.science/.well-known/pith/OYPHQXXRPNSKMGYDAEQ74M3LD3/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:OYPHQXXRPNSKMGYDAEQ74M3LD3","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":"8b7ccdceb5dd44d4481c13c7dab6a0fc1323ae8ca94124e4bb6b43ff4ce307d2","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-08-30T02:01:56Z","title_canon_sha256":"ee62f2d6313374e702524179df8fab70d7300285e37cda62ec0e1097b0e080d1"},"schema_version":"1.0","source":{"id":"2408.16967","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.16967","created_at":"2026-07-05T09:01:08Z"},{"alias_kind":"arxiv_version","alias_value":"2408.16967v1","created_at":"2026-07-05T09:01:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.16967","created_at":"2026-07-05T09:01:08Z"},{"alias_kind":"pith_short_12","alias_value":"OYPHQXXRPNSK","created_at":"2026-07-05T09:01:08Z"},{"alias_kind":"pith_short_16","alias_value":"OYPHQXXRPNSKMGYD","created_at":"2026-07-05T09:01:08Z"},{"alias_kind":"pith_short_8","alias_value":"OYPHQXXR","created_at":"2026-07-05T09:01:08Z"}],"graph_snapshots":[{"event_id":"sha256:72811d1ef5ac07dbb0f148b3991eb8afe32cba5d94d87bd740a128dace2cfa5e","target":"graph","created_at":"2026-07-05T09:01:08Z","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/2408.16967/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recent advancements in Large Language Models (LLMs) have yielded remarkable success across diverse fields. However, handling long contexts remains a significant challenge for LLMs due to the quadratic time and space complexity of attention mechanisms and the growing memory consumption of the key-value cache during generation. This work introduces MemLong: Memory-Augmented Retrieval for Long Text Generation, a method designed to enhance the capabilities of long-context language modeling by utilizing an external retriever for historical information retrieval. MemLong combines a non-differentiabl","authors_text":"Juntao Li, Kehai Chen, Min Zhang, Weijie Liu, Zecheng Tang","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-08-30T02:01:56Z","title":"MemLong: Memory-Augmented Retrieval for Long Text Modeling"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.16967","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":"sha256:6e62f48b105fc6cc411a94b52c66ee1d9ec17e8f1924ada926a7acaa6a1bb597","target":"record","created_at":"2026-07-05T09:01:08Z","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":"8b7ccdceb5dd44d4481c13c7dab6a0fc1323ae8ca94124e4bb6b43ff4ce307d2","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-08-30T02:01:56Z","title_canon_sha256":"ee62f2d6313374e702524179df8fab70d7300285e37cda62ec0e1097b0e080d1"},"schema_version":"1.0","source":{"id":"2408.16967","kind":"arxiv","version":1}},"canonical_sha256":"761e785ef17b64a61b030121fe336b1ee6da7d10f9de70392fad8ebe29b7ea97","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"761e785ef17b64a61b030121fe336b1ee6da7d10f9de70392fad8ebe29b7ea97","first_computed_at":"2026-07-05T09:01:08.891301Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:01:08.891301Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"KKAHTvcKmhKbssp1uR9LIIsd8z7Zvcsj16G8XqpuYDsJrDLcR4FjmueAdCpiA4kmR3/bX0Po2QVTFduQ5qXkCg==","signature_status":"signed_v1","signed_at":"2026-07-05T09:01:08.891761Z","signed_message":"canonical_sha256_bytes"},"source_id":"2408.16967","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6e62f48b105fc6cc411a94b52c66ee1d9ec17e8f1924ada926a7acaa6a1bb597","sha256:72811d1ef5ac07dbb0f148b3991eb8afe32cba5d94d87bd740a128dace2cfa5e"],"state_sha256":"285dd9848dceae9b03a632344ffec70e80bb15595e285d8fc8987db17301fe66"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"f9dWmsMah78Un0RqBUNKOGkhTVtsju8TCdaJ36En9pmzLLM0ImQkFDqtl4CLG8il8oTbw6iN9Os1+ihqX6kxBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-03T20:41:09.262383Z","bundle_sha256":"3b997acbceb7593dcd90d532b555f9e5fe2daf5ffc9beaa81d39873994e06583"}}