{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:Z5ZPKYUX25YC3ZQDF2DVUX5QCK","short_pith_number":"pith:Z5ZPKYUX","canonical_record":{"source":{"id":"2507.04141","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-07-05T19:39:00Z","cross_cats_sorted":["cs.AI","cs.ET","cs.LG","cs.RO"],"title_canon_sha256":"6a03a4c1411d7f1f5e91b31669ef2fd0faf6d9ecd90cfa0c6aa5202db3ffd1e9","abstract_canon_sha256":"8776d55d8f175647c1f2bffa02434008ef3eb5b84c516c08a73a4dba3828d09c"},"schema_version":"1.0"},"canonical_sha256":"cf72f56297d7702de6032e875a5fb012a031651f25008308da151fb090aec0bc","source":{"kind":"arxiv","id":"2507.04141","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.04141","created_at":"2026-07-05T11:32:42Z"},{"alias_kind":"arxiv_version","alias_value":"2507.04141v1","created_at":"2026-07-05T11:32:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.04141","created_at":"2026-07-05T11:32:42Z"},{"alias_kind":"pith_short_12","alias_value":"Z5ZPKYUX25YC","created_at":"2026-07-05T11:32:42Z"},{"alias_kind":"pith_short_16","alias_value":"Z5ZPKYUX25YC3ZQD","created_at":"2026-07-05T11:32:42Z"},{"alias_kind":"pith_short_8","alias_value":"Z5ZPKYUX","created_at":"2026-07-05T11:32:42Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:Z5ZPKYUX25YC3ZQDF2DVUX5QCK","target":"record","payload":{"canonical_record":{"source":{"id":"2507.04141","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-07-05T19:39:00Z","cross_cats_sorted":["cs.AI","cs.ET","cs.LG","cs.RO"],"title_canon_sha256":"6a03a4c1411d7f1f5e91b31669ef2fd0faf6d9ecd90cfa0c6aa5202db3ffd1e9","abstract_canon_sha256":"8776d55d8f175647c1f2bffa02434008ef3eb5b84c516c08a73a4dba3828d09c"},"schema_version":"1.0"},"canonical_sha256":"cf72f56297d7702de6032e875a5fb012a031651f25008308da151fb090aec0bc","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:32:42.657639Z","signature_b64":"ZDB6w7gDmCNfgujHrTvh+lFB4KrUp4IMGGkauSVvxhgnH4ZdXU5vtbvV9sLwGDFy5nioIvXw3wjzvYOPqJcVCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"cf72f56297d7702de6032e875a5fb012a031651f25008308da151fb090aec0bc","last_reissued_at":"2026-07-05T11:32:42.657161Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:32:42.657161Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2507.04141","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":"2026-07-05T11:32:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pTThGnpDfdSsV5yZWqGs0dEFNSZQGJU2GJGj6KWuCPsztScQV8FEuPFH9dXeVomuq6p8KmsD9Ew4Lpy0/MkXBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T21:21:44.227396Z"},"content_sha256":"bb700d890213d0b7f831c5f8643795be0498d10636e6a7a59817256fbed3df98","schema_version":"1.0","event_id":"sha256:bb700d890213d0b7f831c5f8643795be0498d10636e6a7a59817256fbed3df98"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:Z5ZPKYUX25YC3ZQDF2DVUX5QCK","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Pedestrian Intention Prediction via Vision-Language Foundation Models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.ET","cs.LG","cs.RO"],"primary_cat":"cs.CV","authors_text":"He Wang, Mahdi Rezaei, Mohsen Azarmi","submitted_at":"2025-07-05T19:39:00Z","abstract_excerpt":"Prediction of pedestrian crossing intention is a critical function in autonomous vehicles. Conventional vision-based methods of crossing intention prediction often struggle with generalizability, context understanding, and causal reasoning. This study explores the potential of vision-language foundation models (VLFMs) for predicting pedestrian crossing intentions by integrating multimodal data through hierarchical prompt templates. The methodology incorporates contextual information, including visual frames, physical cues observations, and ego-vehicle dynamics, into systematically refined prom"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.04141","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/2507.04141/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":"2026-07-05T11:32:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"k2xRf1dt25uOePYyXtjbpToXsiQC0qPtknRIsWZecafNK1JjEV2IqFDHAatoDORO3KZUdndVkcYUV0cA6SdKBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T21:21:44.227893Z"},"content_sha256":"99653a77de98ba48fe917e32e1c91370c4b5d6b2a9a6ba90bb67a0474e4050d7","schema_version":"1.0","event_id":"sha256:99653a77de98ba48fe917e32e1c91370c4b5d6b2a9a6ba90bb67a0474e4050d7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/Z5ZPKYUX25YC3ZQDF2DVUX5QCK/bundle.json","state_url":"https://pith.science/pith/Z5ZPKYUX25YC3ZQDF2DVUX5QCK/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/Z5ZPKYUX25YC3ZQDF2DVUX5QCK/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":"2026-08-07T21:21:44Z","links":{"resolver":"https://pith.science/pith/Z5ZPKYUX25YC3ZQDF2DVUX5QCK","bundle":"https://pith.science/pith/Z5ZPKYUX25YC3ZQDF2DVUX5QCK/bundle.json","state":"https://pith.science/pith/Z5ZPKYUX25YC3ZQDF2DVUX5QCK/state.json","well_known_bundle":"https://pith.science/.well-known/pith/Z5ZPKYUX25YC3ZQDF2DVUX5QCK/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:Z5ZPKYUX25YC3ZQDF2DVUX5QCK","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":"8776d55d8f175647c1f2bffa02434008ef3eb5b84c516c08a73a4dba3828d09c","cross_cats_sorted":["cs.AI","cs.ET","cs.LG","cs.RO"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-07-05T19:39:00Z","title_canon_sha256":"6a03a4c1411d7f1f5e91b31669ef2fd0faf6d9ecd90cfa0c6aa5202db3ffd1e9"},"schema_version":"1.0","source":{"id":"2507.04141","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.04141","created_at":"2026-07-05T11:32:42Z"},{"alias_kind":"arxiv_version","alias_value":"2507.04141v1","created_at":"2026-07-05T11:32:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.04141","created_at":"2026-07-05T11:32:42Z"},{"alias_kind":"pith_short_12","alias_value":"Z5ZPKYUX25YC","created_at":"2026-07-05T11:32:42Z"},{"alias_kind":"pith_short_16","alias_value":"Z5ZPKYUX25YC3ZQD","created_at":"2026-07-05T11:32:42Z"},{"alias_kind":"pith_short_8","alias_value":"Z5ZPKYUX","created_at":"2026-07-05T11:32:42Z"}],"graph_snapshots":[{"event_id":"sha256:99653a77de98ba48fe917e32e1c91370c4b5d6b2a9a6ba90bb67a0474e4050d7","target":"graph","created_at":"2026-07-05T11:32:42Z","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/2507.04141/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Prediction of pedestrian crossing intention is a critical function in autonomous vehicles. Conventional vision-based methods of crossing intention prediction often struggle with generalizability, context understanding, and causal reasoning. This study explores the potential of vision-language foundation models (VLFMs) for predicting pedestrian crossing intentions by integrating multimodal data through hierarchical prompt templates. The methodology incorporates contextual information, including visual frames, physical cues observations, and ego-vehicle dynamics, into systematically refined prom","authors_text":"He Wang, Mahdi Rezaei, Mohsen Azarmi","cross_cats":["cs.AI","cs.ET","cs.LG","cs.RO"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-07-05T19:39:00Z","title":"Pedestrian Intention Prediction via Vision-Language Foundation Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.04141","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:bb700d890213d0b7f831c5f8643795be0498d10636e6a7a59817256fbed3df98","target":"record","created_at":"2026-07-05T11:32:42Z","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":"8776d55d8f175647c1f2bffa02434008ef3eb5b84c516c08a73a4dba3828d09c","cross_cats_sorted":["cs.AI","cs.ET","cs.LG","cs.RO"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-07-05T19:39:00Z","title_canon_sha256":"6a03a4c1411d7f1f5e91b31669ef2fd0faf6d9ecd90cfa0c6aa5202db3ffd1e9"},"schema_version":"1.0","source":{"id":"2507.04141","kind":"arxiv","version":1}},"canonical_sha256":"cf72f56297d7702de6032e875a5fb012a031651f25008308da151fb090aec0bc","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"cf72f56297d7702de6032e875a5fb012a031651f25008308da151fb090aec0bc","first_computed_at":"2026-07-05T11:32:42.657161Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:32:42.657161Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ZDB6w7gDmCNfgujHrTvh+lFB4KrUp4IMGGkauSVvxhgnH4ZdXU5vtbvV9sLwGDFy5nioIvXw3wjzvYOPqJcVCw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:32:42.657639Z","signed_message":"canonical_sha256_bytes"},"source_id":"2507.04141","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:bb700d890213d0b7f831c5f8643795be0498d10636e6a7a59817256fbed3df98","sha256:99653a77de98ba48fe917e32e1c91370c4b5d6b2a9a6ba90bb67a0474e4050d7"],"state_sha256":"65384b5e0d0ea6f843423b95e7fa413c06ec38feac25bd90acb3d0fa19d60998"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"E7/+yrkvgtLgTVprQdoGeZlRG338sUrcMcekRMVlknffColOlBe4eGNYjO0bIlhmoPGdKzvyV/G4MizyL1RpAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T21:21:44.232036Z","bundle_sha256":"6d913b805580d0e60552f4809a2096a8e9703f4f55ba31d28e0e0dbb052c376a"}}