{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:75DM6RXX6MLSIVXOLI2V2OFALL","short_pith_number":"pith:75DM6RXX","canonical_record":{"source":{"id":"2606.23881","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-06-22T19:27:00Z","cross_cats_sorted":["cs.CV","cs.IR"],"title_canon_sha256":"f82f908537b26e99d35d538af8b8d48ec3943610858111c4a01925aa6deb39ae","abstract_canon_sha256":"d4e79dc103bde6b1cde324c84008fd4d73a3c7f821b9db096cf9aee14fbe633f"},"schema_version":"1.0"},"canonical_sha256":"ff46cf46f7f3172456ee5a355d38a05ad7b23af90d308faa9a37b28c020ca09f","source":{"kind":"arxiv","id":"2606.23881","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.23881","created_at":"2026-06-24T00:14:29Z"},{"alias_kind":"arxiv_version","alias_value":"2606.23881v1","created_at":"2026-06-24T00:14:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.23881","created_at":"2026-06-24T00:14:29Z"},{"alias_kind":"pith_short_12","alias_value":"75DM6RXX6MLS","created_at":"2026-06-24T00:14:29Z"},{"alias_kind":"pith_short_16","alias_value":"75DM6RXX6MLSIVXO","created_at":"2026-06-24T00:14:29Z"},{"alias_kind":"pith_short_8","alias_value":"75DM6RXX","created_at":"2026-06-24T00:14:29Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:75DM6RXX6MLSIVXOLI2V2OFALL","target":"record","payload":{"canonical_record":{"source":{"id":"2606.23881","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-06-22T19:27:00Z","cross_cats_sorted":["cs.CV","cs.IR"],"title_canon_sha256":"f82f908537b26e99d35d538af8b8d48ec3943610858111c4a01925aa6deb39ae","abstract_canon_sha256":"d4e79dc103bde6b1cde324c84008fd4d73a3c7f821b9db096cf9aee14fbe633f"},"schema_version":"1.0"},"canonical_sha256":"ff46cf46f7f3172456ee5a355d38a05ad7b23af90d308faa9a37b28c020ca09f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-24T00:14:29.236755Z","signature_b64":"mz3hX9Rm5XZ4Ub0clFtGLC4eLr7znvvRzCpM7MMH6+lUAHZj4VI1y/NK1+e0JGrEl3smACqGYxNPrTXgKFxVAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ff46cf46f7f3172456ee5a355d38a05ad7b23af90d308faa9a37b28c020ca09f","last_reissued_at":"2026-06-24T00:14:29.236361Z","signature_status":"signed_v1","first_computed_at":"2026-06-24T00:14:29.236361Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2606.23881","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":"2026-06-24T00:14:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BjVOT7RRm7UHuucrcwxaLNr/xPGOiC1aYKJHrF/lUmdAwzPfHsQERMtuyWf5Hi1kIi06UUOZDaJEBiFxrP58Dw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-03T09:34:40.231138Z"},"content_sha256":"e6fc139ce94a9983aa7c92653954eae3501177eaaeb6bdf6c5174f43581012c7","schema_version":"1.0","event_id":"sha256:e6fc139ce94a9983aa7c92653954eae3501177eaaeb6bdf6c5174f43581012c7"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:75DM6RXX6MLSIVXOLI2V2OFALL","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Ground Then Rank: Revisiting Knowledge-Based VQA with Training-Free Entity Identification","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CV","cs.IR"],"primary_cat":"cs.CL","authors_text":"Qian Ma, Qiong Wu, Yao Ma, Zhengyi Zhou","submitted_at":"2026-06-22T19:27:00Z","abstract_excerpt":"Knowledge-Based Visual Question Answering (KB-VQA) requires grounding visual queries to external knowledge beyond directly observable content in images. While recent multi modal large language models (MLLMs) show strong perceptual abilities, they struggle on KB-VQA tasks requiring groundings from both fine-grained entity and evidence levels. Most existing multi-modal retrieval augmented generation (MM-RAG) methods tightly couple entity discrimination and section-level evidence ranking into a single re-ranking stage, leading to high cost and limited generalization. In this work, we revisit exis"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.23881","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/2606.23881/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":"2026-06-24T00:14:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"uHmxbTEgkXn2DFHefyauXL1wiuGLPcPhpvrBWOIv1GrK91WMrvGYEiSYqhpwKWZTjrQ/vYoDq94FaR5KaLcUDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-03T09:34:40.231549Z"},"content_sha256":"15a983f0e63cca4b16cf1e28a32234d7f3977f78399dd1a74edbc08e0ef67228","schema_version":"1.0","event_id":"sha256:15a983f0e63cca4b16cf1e28a32234d7f3977f78399dd1a74edbc08e0ef67228"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/75DM6RXX6MLSIVXOLI2V2OFALL/bundle.json","state_url":"https://pith.science/pith/75DM6RXX6MLSIVXOLI2V2OFALL/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/75DM6RXX6MLSIVXOLI2V2OFALL/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":"2026-07-03T09:34:40Z","links":{"resolver":"https://pith.science/pith/75DM6RXX6MLSIVXOLI2V2OFALL","bundle":"https://pith.science/pith/75DM6RXX6MLSIVXOLI2V2OFALL/bundle.json","state":"https://pith.science/pith/75DM6RXX6MLSIVXOLI2V2OFALL/state.json","well_known_bundle":"https://pith.science/.well-known/pith/75DM6RXX6MLSIVXOLI2V2OFALL/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:75DM6RXX6MLSIVXOLI2V2OFALL","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":"d4e79dc103bde6b1cde324c84008fd4d73a3c7f821b9db096cf9aee14fbe633f","cross_cats_sorted":["cs.CV","cs.IR"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-06-22T19:27:00Z","title_canon_sha256":"f82f908537b26e99d35d538af8b8d48ec3943610858111c4a01925aa6deb39ae"},"schema_version":"1.0","source":{"id":"2606.23881","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.23881","created_at":"2026-06-24T00:14:29Z"},{"alias_kind":"arxiv_version","alias_value":"2606.23881v1","created_at":"2026-06-24T00:14:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.23881","created_at":"2026-06-24T00:14:29Z"},{"alias_kind":"pith_short_12","alias_value":"75DM6RXX6MLS","created_at":"2026-06-24T00:14:29Z"},{"alias_kind":"pith_short_16","alias_value":"75DM6RXX6MLSIVXO","created_at":"2026-06-24T00:14:29Z"},{"alias_kind":"pith_short_8","alias_value":"75DM6RXX","created_at":"2026-06-24T00:14:29Z"}],"graph_snapshots":[{"event_id":"sha256:15a983f0e63cca4b16cf1e28a32234d7f3977f78399dd1a74edbc08e0ef67228","target":"graph","created_at":"2026-06-24T00:14:29Z","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/2606.23881/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Knowledge-Based Visual Question Answering (KB-VQA) requires grounding visual queries to external knowledge beyond directly observable content in images. While recent multi modal large language models (MLLMs) show strong perceptual abilities, they struggle on KB-VQA tasks requiring groundings from both fine-grained entity and evidence levels. Most existing multi-modal retrieval augmented generation (MM-RAG) methods tightly couple entity discrimination and section-level evidence ranking into a single re-ranking stage, leading to high cost and limited generalization. In this work, we revisit exis","authors_text":"Qian Ma, Qiong Wu, Yao Ma, Zhengyi Zhou","cross_cats":["cs.CV","cs.IR"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-06-22T19:27:00Z","title":"Ground Then Rank: Revisiting Knowledge-Based VQA with Training-Free Entity Identification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.23881","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:e6fc139ce94a9983aa7c92653954eae3501177eaaeb6bdf6c5174f43581012c7","target":"record","created_at":"2026-06-24T00:14:29Z","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":"d4e79dc103bde6b1cde324c84008fd4d73a3c7f821b9db096cf9aee14fbe633f","cross_cats_sorted":["cs.CV","cs.IR"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-06-22T19:27:00Z","title_canon_sha256":"f82f908537b26e99d35d538af8b8d48ec3943610858111c4a01925aa6deb39ae"},"schema_version":"1.0","source":{"id":"2606.23881","kind":"arxiv","version":1}},"canonical_sha256":"ff46cf46f7f3172456ee5a355d38a05ad7b23af90d308faa9a37b28c020ca09f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ff46cf46f7f3172456ee5a355d38a05ad7b23af90d308faa9a37b28c020ca09f","first_computed_at":"2026-06-24T00:14:29.236361Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-24T00:14:29.236361Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"mz3hX9Rm5XZ4Ub0clFtGLC4eLr7znvvRzCpM7MMH6+lUAHZj4VI1y/NK1+e0JGrEl3smACqGYxNPrTXgKFxVAQ==","signature_status":"signed_v1","signed_at":"2026-06-24T00:14:29.236755Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.23881","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e6fc139ce94a9983aa7c92653954eae3501177eaaeb6bdf6c5174f43581012c7","sha256:15a983f0e63cca4b16cf1e28a32234d7f3977f78399dd1a74edbc08e0ef67228"],"state_sha256":"dbcd589a4a370c831f3b4fa5443c5182abd66ab731d4a4159d829292a61beb35"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qSkyH/AbT9huL/k8ee/D0ZrsIgMC6ac/19krRG6sVw/EnzcQDJ44rqTGs83zUQac6HieFXf8gVjku100uxjpBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-03T09:34:40.233639Z","bundle_sha256":"1d0a4a60587e0e9f32f7254b2ddf86ef8ab8fd8cfd0e5d898d8a6c4459fd8ae3"}}