{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:CISEULUC2JZE7QCXYUJSHWOF2U","short_pith_number":"pith:CISEULUC","schema_version":"1.0","canonical_sha256":"12244a2e82d2724fc057c51323d9c5d524d5f5f495a29643befd774adf72bb00","source":{"kind":"arxiv","id":"1905.12255","version":3},"attestation_state":"computed","paper":{"title":"Stay on the Path: Instruction Fidelity in Vision-and-Language Navigation","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.CL"],"primary_cat":"cs.AI","authors_text":"Alexander Ku, Ashish Vaswani, Eugene Ie, Gabriel Magalhaes, Jason Baldridge, Vihan Jain","submitted_at":"2019-05-29T07:40:38Z","abstract_excerpt":"Advances in learning and representations have reinvigorated work that connects language to other modalities. A particularly exciting direction is Vision-and-Language Navigation(VLN), in which agents interpret natural language instructions and visual scenes to move through environments and reach goals. Despite recent progress, current research leaves unclear how much of a role language understanding plays in this task, especially because dominant evaluation metrics have focused on goal completion rather than the sequence of actions corresponding to the instructions. Here, we highlight shortcomi"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1905.12255","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.AI","submitted_at":"2019-05-29T07:40:38Z","cross_cats_sorted":["cs.CL"],"title_canon_sha256":"0f44cc6bdf29cc8fe5d4b0257f4a532db6b3d8d64edbe1a4f68ff08dd52eccfe","abstract_canon_sha256":"51ba2424460403eae7d23621a8e69b3ce2b6f1dea227f90d86392ac45ff3104c"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:42:48.057897Z","signature_b64":"NsOFN4QxDPogYSI/KE5xG0WYGSOJllZvZjrqtpf//PFNrd0rOvdULrU2KAkgHgoULCoIwxwKnYn3g6joOD9MBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"12244a2e82d2724fc057c51323d9c5d524d5f5f495a29643befd774adf72bb00","last_reissued_at":"2026-05-17T23:42:48.057436Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:42:48.057436Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Stay on the Path: Instruction Fidelity in Vision-and-Language Navigation","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.CL"],"primary_cat":"cs.AI","authors_text":"Alexander Ku, Ashish Vaswani, Eugene Ie, Gabriel Magalhaes, Jason Baldridge, Vihan Jain","submitted_at":"2019-05-29T07:40:38Z","abstract_excerpt":"Advances in learning and representations have reinvigorated work that connects language to other modalities. A particularly exciting direction is Vision-and-Language Navigation(VLN), in which agents interpret natural language instructions and visual scenes to move through environments and reach goals. Despite recent progress, current research leaves unclear how much of a role language understanding plays in this task, especially because dominant evaluation metrics have focused on goal completion rather than the sequence of actions corresponding to the instructions. Here, we highlight shortcomi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1905.12255","kind":"arxiv","version":3},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1905.12255","created_at":"2026-05-17T23:42:48.057507+00:00"},{"alias_kind":"arxiv_version","alias_value":"1905.12255v3","created_at":"2026-05-17T23:42:48.057507+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1905.12255","created_at":"2026-05-17T23:42:48.057507+00:00"},{"alias_kind":"pith_short_12","alias_value":"CISEULUC2JZE","created_at":"2026-05-18T12:33:15.570797+00:00"},{"alias_kind":"pith_short_16","alias_value":"CISEULUC2JZE7QCX","created_at":"2026-05-18T12:33:15.570797+00:00"},{"alias_kind":"pith_short_8","alias_value":"CISEULUC","created_at":"2026-05-18T12:33:15.570797+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":3,"internal_anchor_count":2,"sample":[{"citing_arxiv_id":"2605.16899","citing_title":"LASAR: Towards Spatio-temporal Reasoning with Latent Cognitive Map","ref_index":20,"is_internal_anchor":true},{"citing_arxiv_id":"2602.11183","citing_title":"Mitigating Error Accumulation in Continuous Navigation via Memory-Augmented Kalman Filtering","ref_index":8,"is_internal_anchor":true},{"citing_arxiv_id":"2604.16298","citing_title":"FineCog-Nav: Integrating Fine-grained Cognitive Modules for Zero-shot Multimodal UAV Navigation","ref_index":16,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/CISEULUC2JZE7QCXYUJSHWOF2U","json":"https://pith.science/pith/CISEULUC2JZE7QCXYUJSHWOF2U.json","graph_json":"https://pith.science/api/pith-number/CISEULUC2JZE7QCXYUJSHWOF2U/graph.json","events_json":"https://pith.science/api/pith-number/CISEULUC2JZE7QCXYUJSHWOF2U/events.json","paper":"https://pith.science/paper/CISEULUC"},"agent_actions":{"view_html":"https://pith.science/pith/CISEULUC2JZE7QCXYUJSHWOF2U","download_json":"https://pith.science/pith/CISEULUC2JZE7QCXYUJSHWOF2U.json","view_paper":"https://pith.science/paper/CISEULUC","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1905.12255&json=true","fetch_graph":"https://pith.science/api/pith-number/CISEULUC2JZE7QCXYUJSHWOF2U/graph.json","fetch_events":"https://pith.science/api/pith-number/CISEULUC2JZE7QCXYUJSHWOF2U/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/CISEULUC2JZE7QCXYUJSHWOF2U/action/timestamp_anchor","attest_storage":"https://pith.science/pith/CISEULUC2JZE7QCXYUJSHWOF2U/action/storage_attestation","attest_author":"https://pith.science/pith/CISEULUC2JZE7QCXYUJSHWOF2U/action/author_attestation","sign_citation":"https://pith.science/pith/CISEULUC2JZE7QCXYUJSHWOF2U/action/citation_signature","submit_replication":"https://pith.science/pith/CISEULUC2JZE7QCXYUJSHWOF2U/action/replication_record"}},"created_at":"2026-05-17T23:42:48.057507+00:00","updated_at":"2026-05-17T23:42:48.057507+00:00"}