{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:K7LGWQADCR3WFF3WISNMXOQMTR","short_pith_number":"pith:K7LGWQAD","canonical_record":{"source":{"id":"2603.04852","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-03-05T06:08:50Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"bedfd18548ad6779efcef3ae4a77cd6bd18f716966eb5d07117ed09c96ae1e04","abstract_canon_sha256":"0f7752bcdf77124c96f0dd4499d6767f804eaaf9e356df92023ef3d0a2e705a4"},"schema_version":"1.0"},"canonical_sha256":"57d66b40031477629776449acbba0c9c4743f6a25601219ff92c2a293b0af85c","source":{"kind":"arxiv","id":"2603.04852","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2603.04852","created_at":"2026-06-10T01:09:57Z"},{"alias_kind":"arxiv_version","alias_value":"2603.04852v2","created_at":"2026-06-10T01:09:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2603.04852","created_at":"2026-06-10T01:09:57Z"},{"alias_kind":"pith_short_12","alias_value":"K7LGWQADCR3W","created_at":"2026-06-10T01:09:57Z"},{"alias_kind":"pith_short_16","alias_value":"K7LGWQADCR3WFF3W","created_at":"2026-06-10T01:09:57Z"},{"alias_kind":"pith_short_8","alias_value":"K7LGWQAD","created_at":"2026-06-10T01:09:57Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:K7LGWQADCR3WFF3WISNMXOQMTR","target":"record","payload":{"canonical_record":{"source":{"id":"2603.04852","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-03-05T06:08:50Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"bedfd18548ad6779efcef3ae4a77cd6bd18f716966eb5d07117ed09c96ae1e04","abstract_canon_sha256":"0f7752bcdf77124c96f0dd4499d6767f804eaaf9e356df92023ef3d0a2e705a4"},"schema_version":"1.0"},"canonical_sha256":"57d66b40031477629776449acbba0c9c4743f6a25601219ff92c2a293b0af85c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-10T01:09:57.699311Z","signature_b64":"jNBIMrDrhm/i8LLTt/CMWK8wChP/G5mENrLEoJ5MgyEzu/Pl4+3ZjYYgvTMDF40o0zNgEs3iRRJE8yvT3WsMAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"57d66b40031477629776449acbba0c9c4743f6a25601219ff92c2a293b0af85c","last_reissued_at":"2026-06-10T01:09:57.698242Z","signature_status":"signed_v1","first_computed_at":"2026-06-10T01:09:57.698242Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2603.04852","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-06-10T01:09:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PyC9JIoG8yRNkqS2bfDCtKg0qU67Tj4J3/1vO4GWAcjSI/EAFwnQhgiicSBlKQFe+5knmEyJmL+ozPPL8aaRAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-30T16:04:43.898177Z"},"content_sha256":"b4a225fb326aaec8c0c9b5d300a8dab01b008a7835403449bfb0fc2ae3e728d6","schema_version":"1.0","event_id":"sha256:b4a225fb326aaec8c0c9b5d300a8dab01b008a7835403449bfb0fc2ae3e728d6"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:K7LGWQADCR3WFF3WISNMXOQMTR","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Non-Parametric Structural Priors for Geometry Theorem Prediction","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.AI","authors_text":"Can Li, Hua Huang, Jingdong Wang, Junbo Zhao, Ting Zhang, Wei He","submitted_at":"2026-03-05T06:08:50Z","abstract_excerpt":"Multi-step theorem prediction is a central challenge in geometry problem solving. Existing neural-symbolic approaches rely heavily on supervised parametric models, which exhibit limited generalization to evolving theorem libraries. In this work, we explore training-free theorem prediction through the lens of in-context learning (ICL). We identify a critical scalability bottleneck, termed Structural Drift: as reasoning depth increases, the performance of vanilla ICL degrades sharply, often collapsing to near zero. We attribute this failure to the LLM's inability to recover latent topological de"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2603.04852","kind":"arxiv","version":2},"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/2603.04852/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":"2026-06-10T01:09:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"c8M1NKS+XUsWDJId0pvBraoZ1YXEYZBrDSoIjp1L9wunjTGSxHFcxtWuu/m5o/vctjrolQF3EiWq4q3nCuZhAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-30T16:04:43.898563Z"},"content_sha256":"74c57bbb2d9d59748092772858d06562a6d8cc9d0e3b58492d845815083c4939","schema_version":"1.0","event_id":"sha256:74c57bbb2d9d59748092772858d06562a6d8cc9d0e3b58492d845815083c4939"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/K7LGWQADCR3WFF3WISNMXOQMTR/bundle.json","state_url":"https://pith.science/pith/K7LGWQADCR3WFF3WISNMXOQMTR/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/K7LGWQADCR3WFF3WISNMXOQMTR/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":"2026-06-30T16:04:43Z","links":{"resolver":"https://pith.science/pith/K7LGWQADCR3WFF3WISNMXOQMTR","bundle":"https://pith.science/pith/K7LGWQADCR3WFF3WISNMXOQMTR/bundle.json","state":"https://pith.science/pith/K7LGWQADCR3WFF3WISNMXOQMTR/state.json","well_known_bundle":"https://pith.science/.well-known/pith/K7LGWQADCR3WFF3WISNMXOQMTR/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:K7LGWQADCR3WFF3WISNMXOQMTR","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":"0f7752bcdf77124c96f0dd4499d6767f804eaaf9e356df92023ef3d0a2e705a4","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-03-05T06:08:50Z","title_canon_sha256":"bedfd18548ad6779efcef3ae4a77cd6bd18f716966eb5d07117ed09c96ae1e04"},"schema_version":"1.0","source":{"id":"2603.04852","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2603.04852","created_at":"2026-06-10T01:09:57Z"},{"alias_kind":"arxiv_version","alias_value":"2603.04852v2","created_at":"2026-06-10T01:09:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2603.04852","created_at":"2026-06-10T01:09:57Z"},{"alias_kind":"pith_short_12","alias_value":"K7LGWQADCR3W","created_at":"2026-06-10T01:09:57Z"},{"alias_kind":"pith_short_16","alias_value":"K7LGWQADCR3WFF3W","created_at":"2026-06-10T01:09:57Z"},{"alias_kind":"pith_short_8","alias_value":"K7LGWQAD","created_at":"2026-06-10T01:09:57Z"}],"graph_snapshots":[{"event_id":"sha256:74c57bbb2d9d59748092772858d06562a6d8cc9d0e3b58492d845815083c4939","target":"graph","created_at":"2026-06-10T01:09:57Z","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/2603.04852/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Multi-step theorem prediction is a central challenge in geometry problem solving. Existing neural-symbolic approaches rely heavily on supervised parametric models, which exhibit limited generalization to evolving theorem libraries. In this work, we explore training-free theorem prediction through the lens of in-context learning (ICL). We identify a critical scalability bottleneck, termed Structural Drift: as reasoning depth increases, the performance of vanilla ICL degrades sharply, often collapsing to near zero. We attribute this failure to the LLM's inability to recover latent topological de","authors_text":"Can Li, Hua Huang, Jingdong Wang, Junbo Zhao, Ting Zhang, Wei He","cross_cats":["cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-03-05T06:08:50Z","title":"Non-Parametric Structural Priors for Geometry Theorem Prediction"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2603.04852","kind":"arxiv","version":2},"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:b4a225fb326aaec8c0c9b5d300a8dab01b008a7835403449bfb0fc2ae3e728d6","target":"record","created_at":"2026-06-10T01:09:57Z","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":"0f7752bcdf77124c96f0dd4499d6767f804eaaf9e356df92023ef3d0a2e705a4","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-03-05T06:08:50Z","title_canon_sha256":"bedfd18548ad6779efcef3ae4a77cd6bd18f716966eb5d07117ed09c96ae1e04"},"schema_version":"1.0","source":{"id":"2603.04852","kind":"arxiv","version":2}},"canonical_sha256":"57d66b40031477629776449acbba0c9c4743f6a25601219ff92c2a293b0af85c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"57d66b40031477629776449acbba0c9c4743f6a25601219ff92c2a293b0af85c","first_computed_at":"2026-06-10T01:09:57.698242Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-10T01:09:57.698242Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"jNBIMrDrhm/i8LLTt/CMWK8wChP/G5mENrLEoJ5MgyEzu/Pl4+3ZjYYgvTMDF40o0zNgEs3iRRJE8yvT3WsMAQ==","signature_status":"signed_v1","signed_at":"2026-06-10T01:09:57.699311Z","signed_message":"canonical_sha256_bytes"},"source_id":"2603.04852","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b4a225fb326aaec8c0c9b5d300a8dab01b008a7835403449bfb0fc2ae3e728d6","sha256:74c57bbb2d9d59748092772858d06562a6d8cc9d0e3b58492d845815083c4939"],"state_sha256":"77afaf6b21ba7a9a887a4d2d3881bdfa8930d13ab1578cf6a4ccd862bf37c7fa"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3KKS1QOIG9Ht/vkVexxb6B7aEgRAbfjkzGtyL8THJCxLjLwGw4muTavrDbB1wPDgSt0m+mDO8EP7o5/ebowrCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-30T16:04:43.900467Z","bundle_sha256":"06167e6507f6be7abadc2c4f7fa9c7209f7226cc59f4a01cb948fb0589fbd506"}}