{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:GQUJ75BEWYZB2HQYH45TL7GB36","short_pith_number":"pith:GQUJ75BE","canonical_record":{"source":{"id":"2410.05045","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2024-10-07T14:00:08Z","cross_cats_sorted":["cs.CL","cs.RO"],"title_canon_sha256":"7a114251b6fdac2f2bbcc0d7cbbce535ce302b5866851047a4957cb3e2316057","abstract_canon_sha256":"fb2b91376d58e9603108a981ad48dce6dc6664c9d1f2093e6ddc526a78d10824"},"schema_version":"1.0"},"canonical_sha256":"34289ff424b6321d1e183f3b35fcc1dfb4543bdf88b64cca17b9c7c7f293fe82","source":{"kind":"arxiv","id":"2410.05045","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.05045","created_at":"2026-07-05T09:17:00Z"},{"alias_kind":"arxiv_version","alias_value":"2410.05045v1","created_at":"2026-07-05T09:17:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.05045","created_at":"2026-07-05T09:17:00Z"},{"alias_kind":"pith_short_12","alias_value":"GQUJ75BEWYZB","created_at":"2026-07-05T09:17:00Z"},{"alias_kind":"pith_short_16","alias_value":"GQUJ75BEWYZB2HQY","created_at":"2026-07-05T09:17:00Z"},{"alias_kind":"pith_short_8","alias_value":"GQUJ75BE","created_at":"2026-07-05T09:17:00Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:GQUJ75BEWYZB2HQYH45TL7GB36","target":"record","payload":{"canonical_record":{"source":{"id":"2410.05045","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2024-10-07T14:00:08Z","cross_cats_sorted":["cs.CL","cs.RO"],"title_canon_sha256":"7a114251b6fdac2f2bbcc0d7cbbce535ce302b5866851047a4957cb3e2316057","abstract_canon_sha256":"fb2b91376d58e9603108a981ad48dce6dc6664c9d1f2093e6ddc526a78d10824"},"schema_version":"1.0"},"canonical_sha256":"34289ff424b6321d1e183f3b35fcc1dfb4543bdf88b64cca17b9c7c7f293fe82","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:17:00.626579Z","signature_b64":"HRqexR8HW8r5Hp+qvGGm59ae2Di1BmP1yXYM7wD50UCupdWSrLAuaNQSQm6vEQ/L+DQ8luU8Q20fafsN/GceCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"34289ff424b6321d1e183f3b35fcc1dfb4543bdf88b64cca17b9c7c7f293fe82","last_reissued_at":"2026-07-05T09:17:00.626028Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:17:00.626028Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2410.05045","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":"2026-07-05T09:17:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EjTZlu7Fo4zApODB+Qanj5saL8Qwnn4rm6DZxps6l4PcVcz10XZ4TTNp7T0cwxOaoEviyQHAJZGp7DSQO3PHBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T22:50:11.341466Z"},"content_sha256":"fbfb8963f8d1aa51d8c61552ac4048a9bf55d88eb279593b996d7b6d9df55d21","schema_version":"1.0","event_id":"sha256:fbfb8963f8d1aa51d8c61552ac4048a9bf55d88eb279593b996d7b6d9df55d21"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:GQUJ75BEWYZB2HQYH45TL7GB36","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Can LLMs plan paths with extra hints from solvers?","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CL","cs.RO"],"primary_cat":"cs.AI","authors_text":"Erik Wu, Sayan Mitra","submitted_at":"2024-10-07T14:00:08Z","abstract_excerpt":"Large Language Models (LLMs) have shown remarkable capabilities in natural language processing, mathematical problem solving, and tasks related to program synthesis. However, their effectiveness in long-term planning and higher-order reasoning has been noted to be limited and fragile. This paper explores an approach for enhancing LLM performance in solving a classical robotic planning task by integrating solver-generated feedback. We explore four different strategies for providing feedback, including visual feedback, we utilize fine-tuning, and we evaluate the performance of three different LL"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.05045","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/2410.05045/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":"2026-07-05T09:17:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"muScHD2rTXgOo6IulrkZGvS5rk0osqxjRxcKhwCnGDZrP7DO/ZlaQQ48qpKFS2w0PKeETCG82ZOR4rOqBeCLAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T22:50:11.341969Z"},"content_sha256":"e4d4ede88959296fc1abf748d62698be390f13b8bab2965bc2fdb8631cf5b209","schema_version":"1.0","event_id":"sha256:e4d4ede88959296fc1abf748d62698be390f13b8bab2965bc2fdb8631cf5b209"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/GQUJ75BEWYZB2HQYH45TL7GB36/bundle.json","state_url":"https://pith.science/pith/GQUJ75BEWYZB2HQYH45TL7GB36/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/GQUJ75BEWYZB2HQYH45TL7GB36/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":"2026-08-22T22:50:11Z","links":{"resolver":"https://pith.science/pith/GQUJ75BEWYZB2HQYH45TL7GB36","bundle":"https://pith.science/pith/GQUJ75BEWYZB2HQYH45TL7GB36/bundle.json","state":"https://pith.science/pith/GQUJ75BEWYZB2HQYH45TL7GB36/state.json","well_known_bundle":"https://pith.science/.well-known/pith/GQUJ75BEWYZB2HQYH45TL7GB36/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:GQUJ75BEWYZB2HQYH45TL7GB36","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":"fb2b91376d58e9603108a981ad48dce6dc6664c9d1f2093e6ddc526a78d10824","cross_cats_sorted":["cs.CL","cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2024-10-07T14:00:08Z","title_canon_sha256":"7a114251b6fdac2f2bbcc0d7cbbce535ce302b5866851047a4957cb3e2316057"},"schema_version":"1.0","source":{"id":"2410.05045","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.05045","created_at":"2026-07-05T09:17:00Z"},{"alias_kind":"arxiv_version","alias_value":"2410.05045v1","created_at":"2026-07-05T09:17:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.05045","created_at":"2026-07-05T09:17:00Z"},{"alias_kind":"pith_short_12","alias_value":"GQUJ75BEWYZB","created_at":"2026-07-05T09:17:00Z"},{"alias_kind":"pith_short_16","alias_value":"GQUJ75BEWYZB2HQY","created_at":"2026-07-05T09:17:00Z"},{"alias_kind":"pith_short_8","alias_value":"GQUJ75BE","created_at":"2026-07-05T09:17:00Z"}],"graph_snapshots":[{"event_id":"sha256:e4d4ede88959296fc1abf748d62698be390f13b8bab2965bc2fdb8631cf5b209","target":"graph","created_at":"2026-07-05T09:17:00Z","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/2410.05045/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large Language Models (LLMs) have shown remarkable capabilities in natural language processing, mathematical problem solving, and tasks related to program synthesis. However, their effectiveness in long-term planning and higher-order reasoning has been noted to be limited and fragile. This paper explores an approach for enhancing LLM performance in solving a classical robotic planning task by integrating solver-generated feedback. We explore four different strategies for providing feedback, including visual feedback, we utilize fine-tuning, and we evaluate the performance of three different LL","authors_text":"Erik Wu, Sayan Mitra","cross_cats":["cs.CL","cs.RO"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2024-10-07T14:00:08Z","title":"Can LLMs plan paths with extra hints from solvers?"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.05045","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:fbfb8963f8d1aa51d8c61552ac4048a9bf55d88eb279593b996d7b6d9df55d21","target":"record","created_at":"2026-07-05T09:17:00Z","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":"fb2b91376d58e9603108a981ad48dce6dc6664c9d1f2093e6ddc526a78d10824","cross_cats_sorted":["cs.CL","cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2024-10-07T14:00:08Z","title_canon_sha256":"7a114251b6fdac2f2bbcc0d7cbbce535ce302b5866851047a4957cb3e2316057"},"schema_version":"1.0","source":{"id":"2410.05045","kind":"arxiv","version":1}},"canonical_sha256":"34289ff424b6321d1e183f3b35fcc1dfb4543bdf88b64cca17b9c7c7f293fe82","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"34289ff424b6321d1e183f3b35fcc1dfb4543bdf88b64cca17b9c7c7f293fe82","first_computed_at":"2026-07-05T09:17:00.626028Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:17:00.626028Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"HRqexR8HW8r5Hp+qvGGm59ae2Di1BmP1yXYM7wD50UCupdWSrLAuaNQSQm6vEQ/L+DQ8luU8Q20fafsN/GceCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T09:17:00.626579Z","signed_message":"canonical_sha256_bytes"},"source_id":"2410.05045","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:fbfb8963f8d1aa51d8c61552ac4048a9bf55d88eb279593b996d7b6d9df55d21","sha256:e4d4ede88959296fc1abf748d62698be390f13b8bab2965bc2fdb8631cf5b209"],"state_sha256":"e1795a3035441666affaa71048d02e689c341be2259deb5eae6729514a5ca6c3"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wseCqbpjLRAq3g8mUgje12nsUX8zd/aeza1tROzAeunkXJW3Lg0MMmet/gSOgJqWOv1j3WM45pYXiYXSbBA6DA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-22T22:50:11.345839Z","bundle_sha256":"67ff7acac1bcb9665bfa24068cfaf450a34f29055f543d2118a912c9c777da9f"}}