{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:VMHFPLXAGPB42IJNTOS2T5HXOC","short_pith_number":"pith:VMHFPLXA","schema_version":"1.0","canonical_sha256":"ab0e57aee033c3cd212d9ba5a9f4f770859f4474845a4e44d606a2b382f9d45c","source":{"kind":"arxiv","id":"2403.14344","version":1},"attestation_state":"computed","paper":{"title":"Tell Me What You Want (What You Really, Really Want): Addressing the Expectation Gap for Goal Conveyance from Humans to Robots","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.HC"],"primary_cat":"cs.RO","authors_text":"Ho Chit Siu, Kevin Leahy","submitted_at":"2024-03-21T12:22:47Z","abstract_excerpt":"Conveying human goals to autonomous systems (AS) occurs both when the system is being designed and when it is being operated. The design-step conveyance is typically mediated by robotics and AI engineers, who must appropriately capture end-user requirements and concepts of operations, while the operation-step conveyance is mediated by the design, interfaces, and behavior of the AI. However, communication can be difficult during both these periods because of mismatches in the expectations and expertise of the end-user and the roboticist, necessitating more design cycles to resolve. We examine s"},"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":"2403.14344","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2024-03-21T12:22:47Z","cross_cats_sorted":["cs.HC"],"title_canon_sha256":"b62dcb188df9a27759a2a6a85dc49f6e88a4318a426d6ec725f9edf3c4e17eb7","abstract_canon_sha256":"44f6494df93907d501b626ac655bfe9d2c4b2a95557fa660c2e2ed4de136267e"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:59:07.329441Z","signature_b64":"nCqg7UHMOGYMSNfbF+bXEzvttVRBc1V5NhCG4wNYsaSV8h+3/HAVaehszyhtu8foH2JUteW0D7vCVNAUQC7oAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ab0e57aee033c3cd212d9ba5a9f4f770859f4474845a4e44d606a2b382f9d45c","last_reissued_at":"2026-07-05T07:59:07.328965Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:59:07.328965Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Tell Me What You Want (What You Really, Really Want): Addressing the Expectation Gap for Goal Conveyance from Humans to Robots","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.HC"],"primary_cat":"cs.RO","authors_text":"Ho Chit Siu, Kevin Leahy","submitted_at":"2024-03-21T12:22:47Z","abstract_excerpt":"Conveying human goals to autonomous systems (AS) occurs both when the system is being designed and when it is being operated. The design-step conveyance is typically mediated by robotics and AI engineers, who must appropriately capture end-user requirements and concepts of operations, while the operation-step conveyance is mediated by the design, interfaces, and behavior of the AI. However, communication can be difficult during both these periods because of mismatches in the expectations and expertise of the end-user and the roboticist, necessitating more design cycles to resolve. We examine s"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.14344","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/2403.14344/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2403.14344","created_at":"2026-07-05T07:59:07.329024+00:00"},{"alias_kind":"arxiv_version","alias_value":"2403.14344v1","created_at":"2026-07-05T07:59:07.329024+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.14344","created_at":"2026-07-05T07:59:07.329024+00:00"},{"alias_kind":"pith_short_12","alias_value":"VMHFPLXAGPB4","created_at":"2026-07-05T07:59:07.329024+00:00"},{"alias_kind":"pith_short_16","alias_value":"VMHFPLXAGPB42IJN","created_at":"2026-07-05T07:59:07.329024+00:00"},{"alias_kind":"pith_short_8","alias_value":"VMHFPLXA","created_at":"2026-07-05T07:59:07.329024+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2503.15516","citing_title":"In Pursuit of Predictive Models of Human Preferences Toward AI Teammates","ref_index":25,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/VMHFPLXAGPB42IJNTOS2T5HXOC","json":"https://pith.science/pith/VMHFPLXAGPB42IJNTOS2T5HXOC.json","graph_json":"https://pith.science/api/pith-number/VMHFPLXAGPB42IJNTOS2T5HXOC/graph.json","events_json":"https://pith.science/api/pith-number/VMHFPLXAGPB42IJNTOS2T5HXOC/events.json","paper":"https://pith.science/paper/VMHFPLXA"},"agent_actions":{"view_html":"https://pith.science/pith/VMHFPLXAGPB42IJNTOS2T5HXOC","download_json":"https://pith.science/pith/VMHFPLXAGPB42IJNTOS2T5HXOC.json","view_paper":"https://pith.science/paper/VMHFPLXA","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2403.14344&json=true","fetch_graph":"https://pith.science/api/pith-number/VMHFPLXAGPB42IJNTOS2T5HXOC/graph.json","fetch_events":"https://pith.science/api/pith-number/VMHFPLXAGPB42IJNTOS2T5HXOC/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/VMHFPLXAGPB42IJNTOS2T5HXOC/action/timestamp_anchor","attest_storage":"https://pith.science/pith/VMHFPLXAGPB42IJNTOS2T5HXOC/action/storage_attestation","attest_author":"https://pith.science/pith/VMHFPLXAGPB42IJNTOS2T5HXOC/action/author_attestation","sign_citation":"https://pith.science/pith/VMHFPLXAGPB42IJNTOS2T5HXOC/action/citation_signature","submit_replication":"https://pith.science/pith/VMHFPLXAGPB42IJNTOS2T5HXOC/action/replication_record"}},"created_at":"2026-07-05T07:59:07.329024+00:00","updated_at":"2026-07-05T07:59:07.329024+00:00"}