{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:NZCINKTK3SBUMNZ657UUUTBMO4","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":"2628cdcf2ac2c7270f5b8b070e507b59f0e8a008ba8cdcdbbe01f053a97f47bb","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2025-12-30T03:13:10Z","title_canon_sha256":"22110778b646b7dc5523396236d427852ae67fd9560a9550409bc3c20f39d5b1"},"schema_version":"1.0","source":{"id":"2512.23959","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2512.23959","created_at":"2026-05-28T01:04:34Z"},{"alias_kind":"arxiv_version","alias_value":"2512.23959v3","created_at":"2026-05-28T01:04:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2512.23959","created_at":"2026-05-28T01:04:34Z"},{"alias_kind":"pith_short_12","alias_value":"NZCINKTK3SBU","created_at":"2026-05-28T01:04:34Z"},{"alias_kind":"pith_short_16","alias_value":"NZCINKTK3SBUMNZ6","created_at":"2026-05-28T01:04:34Z"},{"alias_kind":"pith_short_8","alias_value":"NZCINKTK","created_at":"2026-05-28T01:04:34Z"}],"graph_snapshots":[{"event_id":"sha256:c20f31c8d225d3fa8b7f9318b65187b8c5ffc09406c4fce54ec401cacdffc17f","target":"graph","created_at":"2026-05-28T01:04:34Z","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/2512.23959/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Multi-step retrieval-augmented generation (RAG) has become a widely adopted strategy for enhancing large language models (LLMs) on tasks that demand global comprehension and intensive reasoning. Although many RAG systems incorporate a working memory to consolidate information, existing designs primarily function as a passive storage for isolated facts. This static nature overlooks crucial high-order correlations among primitive facts, thereby limiting models' capacity for multi-step reasoning and resulting in fragmented reasoning and weak global sense-making within extended contexts. We introd","authors_text":"Chulun Zhou, Chunkang Zhang, Fandong Meng, Guoxin Yu, Jie Zhou, Mo Yu, Wai Lam","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2025-12-30T03:13:10Z","title":"HGMEM: Hypergraph-based Working Memory to Improve Multi-step RAG for Long-Context Complex Relational Modeling"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2512.23959","kind":"arxiv","version":3},"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:c2beb48986291937f5668edc014d3f7aac3aef26ad02ff4b01418d2b8f70f3e5","target":"record","created_at":"2026-05-28T01:04:34Z","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":"2628cdcf2ac2c7270f5b8b070e507b59f0e8a008ba8cdcdbbe01f053a97f47bb","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2025-12-30T03:13:10Z","title_canon_sha256":"22110778b646b7dc5523396236d427852ae67fd9560a9550409bc3c20f39d5b1"},"schema_version":"1.0","source":{"id":"2512.23959","kind":"arxiv","version":3}},"canonical_sha256":"6e4486aa6adc8346373eefe94a4c2c773a320b615848c7f0482195c0bcffea82","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6e4486aa6adc8346373eefe94a4c2c773a320b615848c7f0482195c0bcffea82","first_computed_at":"2026-05-28T01:04:34.828892Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-28T01:04:34.828892Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"MCsXZKz55+NV/c6uAYSlHs5pjbvYLQQ16QysVoY57TgArsrdcnDpqilicXR8ERsMo5I/74vygU8+jY7X8EoeCA==","signature_status":"signed_v1","signed_at":"2026-05-28T01:04:34.829344Z","signed_message":"canonical_sha256_bytes"},"source_id":"2512.23959","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c2beb48986291937f5668edc014d3f7aac3aef26ad02ff4b01418d2b8f70f3e5","sha256:c20f31c8d225d3fa8b7f9318b65187b8c5ffc09406c4fce54ec401cacdffc17f"],"state_sha256":"eb8acacb07a46f78b55b80ad025675a14ee7f6bc4b3f155c2b63ea111f0b38be"}