{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:LO3E3EU2L7WWNU72JS5DPZCPWS","short_pith_number":"pith:LO3E3EU2","canonical_record":{"source":{"id":"2603.19464","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2026-03-19T20:55:46Z","cross_cats_sorted":[],"title_canon_sha256":"b1c5cd1eecdb5ad9d005792ceec95a0277214eec05f5c0428ffde3841c886b1f","abstract_canon_sha256":"772c442f5a574321a53834e8f267c2b2d36185d06a77bcea82d146ae21cf31b0"},"schema_version":"1.0"},"canonical_sha256":"5bb64d929a5fed66d3fa4cba37e44fb48828e7d24ebf2a2214f24b62155bdac7","source":{"kind":"arxiv","id":"2603.19464","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2603.19464","created_at":"2026-06-30T00:15:09Z"},{"alias_kind":"arxiv_version","alias_value":"2603.19464v2","created_at":"2026-06-30T00:15:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2603.19464","created_at":"2026-06-30T00:15:09Z"},{"alias_kind":"pith_short_12","alias_value":"LO3E3EU2L7WW","created_at":"2026-06-30T00:15:09Z"},{"alias_kind":"pith_short_16","alias_value":"LO3E3EU2L7WWNU72","created_at":"2026-06-30T00:15:09Z"},{"alias_kind":"pith_short_8","alias_value":"LO3E3EU2","created_at":"2026-06-30T00:15:09Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:LO3E3EU2L7WWNU72JS5DPZCPWS","target":"record","payload":{"canonical_record":{"source":{"id":"2603.19464","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2026-03-19T20:55:46Z","cross_cats_sorted":[],"title_canon_sha256":"b1c5cd1eecdb5ad9d005792ceec95a0277214eec05f5c0428ffde3841c886b1f","abstract_canon_sha256":"772c442f5a574321a53834e8f267c2b2d36185d06a77bcea82d146ae21cf31b0"},"schema_version":"1.0"},"canonical_sha256":"5bb64d929a5fed66d3fa4cba37e44fb48828e7d24ebf2a2214f24b62155bdac7","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-30T00:15:09.511333Z","signature_b64":"GYcuxaO7CNjF8+0P4//nYUy3gDJJhZTJAvbKA4bMI+spesp+rrTqTT4SHceKl0xnsvCWXQ8QaZnDkBbgZKxgBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5bb64d929a5fed66d3fa4cba37e44fb48828e7d24ebf2a2214f24b62155bdac7","last_reissued_at":"2026-06-30T00:15:09.510842Z","signature_status":"signed_v1","first_computed_at":"2026-06-30T00:15:09.510842Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2603.19464","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":"2026-06-30T00:15:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nWYe7fxBpgY+7KBsKJE2fvo0mni+wswEm5haS0uA25SS6PGPTMKkSKHF8B118NOwblNQB2Ux6OZBpX21/yD2AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T17:14:58.244351Z"},"content_sha256":"b7ea74cc4d5fbbed88f91f6e5b3bec2087e9b78a4be9ea7aa93332e0d57186ca","schema_version":"1.0","event_id":"sha256:b7ea74cc4d5fbbed88f91f6e5b3bec2087e9b78a4be9ea7aa93332e0d57186ca"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:LO3E3EU2L7WWNU72JS5DPZCPWS","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Can LLMs Prove Robotic Path Planning Optimality? A Benchmark for Research-Level Algorithm Verification","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Md. Tasin Tazwar, Minghan Wei, Zhengbang Yang, Zhuangdi Zhu","submitted_at":"2026-03-19T20:55:46Z","abstract_excerpt":"Robotic path planning problems are often NP-hard, and practical solutions typically rely on approximation algorithms with provable performance guarantees for general cases. While designing such algorithms is challenging, formally proving their approximation optimality is even more demanding, which requires domain-specific geometric insights and multi-step mathematical reasoning over complex operational constraints. Recent Large Language Models (LLMs) have demonstrated strong performance on mathematical reasoning benchmarks, yet their ability to assist with research-level optimality proofs in r"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2603.19464","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/2603.19464/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":"2026-06-30T00:15:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7b80/5yxnfr7qLBp13xRZYpXeMdPxWC/UpFGFMyYv7RhNpOLIr4OsIdrSv28UEP6TuJhJ+ptaribREy08D1qAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T17:14:58.244850Z"},"content_sha256":"d3d5c10b5d4dbd1bc569b34a6ffba948e8b364e0049625971769b8be5593e4ed","schema_version":"1.0","event_id":"sha256:d3d5c10b5d4dbd1bc569b34a6ffba948e8b364e0049625971769b8be5593e4ed"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LO3E3EU2L7WWNU72JS5DPZCPWS/bundle.json","state_url":"https://pith.science/pith/LO3E3EU2L7WWNU72JS5DPZCPWS/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LO3E3EU2L7WWNU72JS5DPZCPWS/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":"2026-08-08T17:14:58Z","links":{"resolver":"https://pith.science/pith/LO3E3EU2L7WWNU72JS5DPZCPWS","bundle":"https://pith.science/pith/LO3E3EU2L7WWNU72JS5DPZCPWS/bundle.json","state":"https://pith.science/pith/LO3E3EU2L7WWNU72JS5DPZCPWS/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LO3E3EU2L7WWNU72JS5DPZCPWS/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:LO3E3EU2L7WWNU72JS5DPZCPWS","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":"772c442f5a574321a53834e8f267c2b2d36185d06a77bcea82d146ae21cf31b0","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2026-03-19T20:55:46Z","title_canon_sha256":"b1c5cd1eecdb5ad9d005792ceec95a0277214eec05f5c0428ffde3841c886b1f"},"schema_version":"1.0","source":{"id":"2603.19464","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2603.19464","created_at":"2026-06-30T00:15:09Z"},{"alias_kind":"arxiv_version","alias_value":"2603.19464v2","created_at":"2026-06-30T00:15:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2603.19464","created_at":"2026-06-30T00:15:09Z"},{"alias_kind":"pith_short_12","alias_value":"LO3E3EU2L7WW","created_at":"2026-06-30T00:15:09Z"},{"alias_kind":"pith_short_16","alias_value":"LO3E3EU2L7WWNU72","created_at":"2026-06-30T00:15:09Z"},{"alias_kind":"pith_short_8","alias_value":"LO3E3EU2","created_at":"2026-06-30T00:15:09Z"}],"graph_snapshots":[{"event_id":"sha256:d3d5c10b5d4dbd1bc569b34a6ffba948e8b364e0049625971769b8be5593e4ed","target":"graph","created_at":"2026-06-30T00:15:09Z","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/2603.19464/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Robotic path planning problems are often NP-hard, and practical solutions typically rely on approximation algorithms with provable performance guarantees for general cases. While designing such algorithms is challenging, formally proving their approximation optimality is even more demanding, which requires domain-specific geometric insights and multi-step mathematical reasoning over complex operational constraints. Recent Large Language Models (LLMs) have demonstrated strong performance on mathematical reasoning benchmarks, yet their ability to assist with research-level optimality proofs in r","authors_text":"Md. Tasin Tazwar, Minghan Wei, Zhengbang Yang, Zhuangdi Zhu","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2026-03-19T20:55:46Z","title":"Can LLMs Prove Robotic Path Planning Optimality? A Benchmark for Research-Level Algorithm Verification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2603.19464","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:b7ea74cc4d5fbbed88f91f6e5b3bec2087e9b78a4be9ea7aa93332e0d57186ca","target":"record","created_at":"2026-06-30T00:15:09Z","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":"772c442f5a574321a53834e8f267c2b2d36185d06a77bcea82d146ae21cf31b0","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2026-03-19T20:55:46Z","title_canon_sha256":"b1c5cd1eecdb5ad9d005792ceec95a0277214eec05f5c0428ffde3841c886b1f"},"schema_version":"1.0","source":{"id":"2603.19464","kind":"arxiv","version":2}},"canonical_sha256":"5bb64d929a5fed66d3fa4cba37e44fb48828e7d24ebf2a2214f24b62155bdac7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5bb64d929a5fed66d3fa4cba37e44fb48828e7d24ebf2a2214f24b62155bdac7","first_computed_at":"2026-06-30T00:15:09.510842Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-30T00:15:09.510842Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"GYcuxaO7CNjF8+0P4//nYUy3gDJJhZTJAvbKA4bMI+spesp+rrTqTT4SHceKl0xnsvCWXQ8QaZnDkBbgZKxgBA==","signature_status":"signed_v1","signed_at":"2026-06-30T00:15:09.511333Z","signed_message":"canonical_sha256_bytes"},"source_id":"2603.19464","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b7ea74cc4d5fbbed88f91f6e5b3bec2087e9b78a4be9ea7aa93332e0d57186ca","sha256:d3d5c10b5d4dbd1bc569b34a6ffba948e8b364e0049625971769b8be5593e4ed"],"state_sha256":"3f1d7e74c5b4394ed24d10e6832ef08f87e3fed7aa1b646be8dc01792f5448e0"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7l32/TLbT2R961Cx4yqTVIub3BzSfSElKL4CP2DBugnT4NgQiS8eh9iH1nkBoC9pX5o+xpz07Fw/MZ4w/aXeDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T17:14:58.248557Z","bundle_sha256":"f05adeb9bd9cbbc68a57511c6e0f4e2baf4729b17badd0de95afdc40265aed64"}}