{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:VXAWNNJ7MUQMUL5HFDRNJ625RN","short_pith_number":"pith:VXAWNNJ7","schema_version":"1.0","canonical_sha256":"adc166b53f6520ca2fa728e2d4fb5d8b73be4380092e6e8a812e1c3ad3636ae5","source":{"kind":"arxiv","id":"2606.19277","version":1},"attestation_state":"computed","paper":{"title":"A Unified Framework for Efficient Remote Sensing Visual Question Answering: Adapting Dual, Hybrid, and Encoder-Decoder Architectures","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Leila Hashemi-Beni, Shikha Chandel, Timothy Agboada, Yadav Raj Ghimire","submitted_at":"2026-06-17T16:52:26Z","abstract_excerpt":"Visual Question Answering (VQA) in the Remote Sensing (RS) domain presents unique challenges due to the high resolution, multi scale object distribution, and semantic complexity of aerial imagery. While general domain Foundation Models have achieved remarkable success, their direct application to RSVQA is hindered by massive domain shifts and the computationally prohibitive nature of full fine tuning. This study presents a comparative analysis of RS Adapter, a Parameter Efficient Fine Tuning (PEFT) strategy, applied across three distinct Vision Language Model (VLM) architectures: the Dual Enco"},"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":"2606.19277","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-06-17T16:52:26Z","cross_cats_sorted":[],"title_canon_sha256":"388893056eae3faf976360d68cbc8efc9fbeaf51ed90a4e77ef1b77442986d2b","abstract_canon_sha256":"4cc65c846c99df41dff012e826965e201b4050b3277280ae1722fadb2632817e"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-19T16:12:09.482955Z","signature_b64":"RV6CnBzVjz85BOfNps9f8qHYQ2p4Sppd4uS+D2aYfG9+rbfB5bH4+ZTxCmkfy21/1yanPGX39ZmCYFAe1VPWCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"adc166b53f6520ca2fa728e2d4fb5d8b73be4380092e6e8a812e1c3ad3636ae5","last_reissued_at":"2026-06-19T16:12:09.482613Z","signature_status":"signed_v1","first_computed_at":"2026-06-19T16:12:09.482613Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Unified Framework for Efficient Remote Sensing Visual Question Answering: Adapting Dual, Hybrid, and Encoder-Decoder Architectures","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Leila Hashemi-Beni, Shikha Chandel, Timothy Agboada, Yadav Raj Ghimire","submitted_at":"2026-06-17T16:52:26Z","abstract_excerpt":"Visual Question Answering (VQA) in the Remote Sensing (RS) domain presents unique challenges due to the high resolution, multi scale object distribution, and semantic complexity of aerial imagery. While general domain Foundation Models have achieved remarkable success, their direct application to RSVQA is hindered by massive domain shifts and the computationally prohibitive nature of full fine tuning. This study presents a comparative analysis of RS Adapter, a Parameter Efficient Fine Tuning (PEFT) strategy, applied across three distinct Vision Language Model (VLM) architectures: the Dual Enco"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.19277","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/2606.19277/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":"2606.19277","created_at":"2026-06-19T16:12:09.482672+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.19277v1","created_at":"2026-06-19T16:12:09.482672+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.19277","created_at":"2026-06-19T16:12:09.482672+00:00"},{"alias_kind":"pith_short_12","alias_value":"VXAWNNJ7MUQM","created_at":"2026-06-19T16:12:09.482672+00:00"},{"alias_kind":"pith_short_16","alias_value":"VXAWNNJ7MUQMUL5H","created_at":"2026-06-19T16:12:09.482672+00:00"},{"alias_kind":"pith_short_8","alias_value":"VXAWNNJ7","created_at":"2026-06-19T16:12:09.482672+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/VXAWNNJ7MUQMUL5HFDRNJ625RN","json":"https://pith.science/pith/VXAWNNJ7MUQMUL5HFDRNJ625RN.json","graph_json":"https://pith.science/api/pith-number/VXAWNNJ7MUQMUL5HFDRNJ625RN/graph.json","events_json":"https://pith.science/api/pith-number/VXAWNNJ7MUQMUL5HFDRNJ625RN/events.json","paper":"https://pith.science/paper/VXAWNNJ7"},"agent_actions":{"view_html":"https://pith.science/pith/VXAWNNJ7MUQMUL5HFDRNJ625RN","download_json":"https://pith.science/pith/VXAWNNJ7MUQMUL5HFDRNJ625RN.json","view_paper":"https://pith.science/paper/VXAWNNJ7","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.19277&json=true","fetch_graph":"https://pith.science/api/pith-number/VXAWNNJ7MUQMUL5HFDRNJ625RN/graph.json","fetch_events":"https://pith.science/api/pith-number/VXAWNNJ7MUQMUL5HFDRNJ625RN/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/VXAWNNJ7MUQMUL5HFDRNJ625RN/action/timestamp_anchor","attest_storage":"https://pith.science/pith/VXAWNNJ7MUQMUL5HFDRNJ625RN/action/storage_attestation","attest_author":"https://pith.science/pith/VXAWNNJ7MUQMUL5HFDRNJ625RN/action/author_attestation","sign_citation":"https://pith.science/pith/VXAWNNJ7MUQMUL5HFDRNJ625RN/action/citation_signature","submit_replication":"https://pith.science/pith/VXAWNNJ7MUQMUL5HFDRNJ625RN/action/replication_record"}},"created_at":"2026-06-19T16:12:09.482672+00:00","updated_at":"2026-06-19T16:12:09.482672+00:00"}