{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:JYIC3N5FB5CLEKHBPTYT7OTKMZ","short_pith_number":"pith:JYIC3N5F","canonical_record":{"source":{"id":"2606.28401","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-24T11:06:22Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"c036f2c6c904d7953be1fadbcd3acd133d2446d429550de13080427441964f8f","abstract_canon_sha256":"6762f3597784244acc18aabb16d273a16857f338a423ea96846d905a7bbacc1c"},"schema_version":"1.0"},"canonical_sha256":"4e102db7a50f44b228e17cf13fba6a667c39d8f7730bfefd9f4e82c24d420cdd","source":{"kind":"arxiv","id":"2606.28401","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.28401","created_at":"2026-06-30T00:15:13Z"},{"alias_kind":"arxiv_version","alias_value":"2606.28401v1","created_at":"2026-06-30T00:15:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.28401","created_at":"2026-06-30T00:15:13Z"},{"alias_kind":"pith_short_12","alias_value":"JYIC3N5FB5CL","created_at":"2026-06-30T00:15:13Z"},{"alias_kind":"pith_short_16","alias_value":"JYIC3N5FB5CLEKHB","created_at":"2026-06-30T00:15:13Z"},{"alias_kind":"pith_short_8","alias_value":"JYIC3N5F","created_at":"2026-06-30T00:15:13Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:JYIC3N5FB5CLEKHBPTYT7OTKMZ","target":"record","payload":{"canonical_record":{"source":{"id":"2606.28401","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-24T11:06:22Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"c036f2c6c904d7953be1fadbcd3acd133d2446d429550de13080427441964f8f","abstract_canon_sha256":"6762f3597784244acc18aabb16d273a16857f338a423ea96846d905a7bbacc1c"},"schema_version":"1.0"},"canonical_sha256":"4e102db7a50f44b228e17cf13fba6a667c39d8f7730bfefd9f4e82c24d420cdd","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-30T00:15:13.071127Z","signature_b64":"maBEe7sXGRO4Wx22YRqJUjexzivMupGp1bsHmFXrKD0Wi6T9qsKu8MrM0YB+OFqp9Bz3z65z03BH7ZyI1V4VBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4e102db7a50f44b228e17cf13fba6a667c39d8f7730bfefd9f4e82c24d420cdd","last_reissued_at":"2026-06-30T00:15:13.070732Z","signature_status":"signed_v1","first_computed_at":"2026-06-30T00:15:13.070732Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2606.28401","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":"2026-06-30T00:15:13Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BKv3PJsXKE4di2oQ5ihgDZOWVLMB8f42HngCn1yTSYPA3yrSKU+F90wv7SezGF7T+sSOygrZXt6gsn3oVgeiDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-02T05:02:01.614834Z"},"content_sha256":"882e8d3814b314572bbe356a27602bd05251a85e524369a37ff0d0cbde0b89b4","schema_version":"1.0","event_id":"sha256:882e8d3814b314572bbe356a27602bd05251a85e524369a37ff0d0cbde0b89b4"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:JYIC3N5FB5CLEKHBPTYT7OTKMZ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Vision-driven Preference Synthesis for Mitigating Hallucinations in VLMs","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Jongheon Jeong, Yunhun Nam","submitted_at":"2026-06-24T11:06:22Z","abstract_excerpt":"Vision-Language Models (VLMs) have shown strong performance in visual understanding, yet they still suffer from hallucinations, generating content that is not grounded in the image. Preference alignment is a promising approach to improve visual faithfulness, but its success depends heavily on how preference pairs are constructed. Existing methods exhibit two key limitations; (a) intervention-based methods often introduce significant deviation from the policy distribution, and (b) sampling-based methods often underuse visual information during the construction. In this paper, we propose ViPSy ("},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.28401","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/2606.28401/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":"2026-06-30T00:15:13Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xOrB/qUTgCYvtLesn9vNiCTFRKcUfHakIRzfX6i0S8ZzTPkw+qV8sL5jcSFoAnRrfl8gt4jMHdnu8MUr1/f0CQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-02T05:02:01.615213Z"},"content_sha256":"da0c71bd85b7a240c4a7175109da834a2a6bb0871538830e95072f13f36cc293","schema_version":"1.0","event_id":"sha256:da0c71bd85b7a240c4a7175109da834a2a6bb0871538830e95072f13f36cc293"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/JYIC3N5FB5CLEKHBPTYT7OTKMZ/bundle.json","state_url":"https://pith.science/pith/JYIC3N5FB5CLEKHBPTYT7OTKMZ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/JYIC3N5FB5CLEKHBPTYT7OTKMZ/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":"2026-07-02T05:02:01Z","links":{"resolver":"https://pith.science/pith/JYIC3N5FB5CLEKHBPTYT7OTKMZ","bundle":"https://pith.science/pith/JYIC3N5FB5CLEKHBPTYT7OTKMZ/bundle.json","state":"https://pith.science/pith/JYIC3N5FB5CLEKHBPTYT7OTKMZ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/JYIC3N5FB5CLEKHBPTYT7OTKMZ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:JYIC3N5FB5CLEKHBPTYT7OTKMZ","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":"6762f3597784244acc18aabb16d273a16857f338a423ea96846d905a7bbacc1c","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-24T11:06:22Z","title_canon_sha256":"c036f2c6c904d7953be1fadbcd3acd133d2446d429550de13080427441964f8f"},"schema_version":"1.0","source":{"id":"2606.28401","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.28401","created_at":"2026-06-30T00:15:13Z"},{"alias_kind":"arxiv_version","alias_value":"2606.28401v1","created_at":"2026-06-30T00:15:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.28401","created_at":"2026-06-30T00:15:13Z"},{"alias_kind":"pith_short_12","alias_value":"JYIC3N5FB5CL","created_at":"2026-06-30T00:15:13Z"},{"alias_kind":"pith_short_16","alias_value":"JYIC3N5FB5CLEKHB","created_at":"2026-06-30T00:15:13Z"},{"alias_kind":"pith_short_8","alias_value":"JYIC3N5F","created_at":"2026-06-30T00:15:13Z"}],"graph_snapshots":[{"event_id":"sha256:da0c71bd85b7a240c4a7175109da834a2a6bb0871538830e95072f13f36cc293","target":"graph","created_at":"2026-06-30T00:15:13Z","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/2606.28401/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Vision-Language Models (VLMs) have shown strong performance in visual understanding, yet they still suffer from hallucinations, generating content that is not grounded in the image. Preference alignment is a promising approach to improve visual faithfulness, but its success depends heavily on how preference pairs are constructed. Existing methods exhibit two key limitations; (a) intervention-based methods often introduce significant deviation from the policy distribution, and (b) sampling-based methods often underuse visual information during the construction. In this paper, we propose ViPSy (","authors_text":"Jongheon Jeong, Yunhun Nam","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-24T11:06:22Z","title":"Vision-driven Preference Synthesis for Mitigating Hallucinations in VLMs"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.28401","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":"sha256:882e8d3814b314572bbe356a27602bd05251a85e524369a37ff0d0cbde0b89b4","target":"record","created_at":"2026-06-30T00:15:13Z","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":"6762f3597784244acc18aabb16d273a16857f338a423ea96846d905a7bbacc1c","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-24T11:06:22Z","title_canon_sha256":"c036f2c6c904d7953be1fadbcd3acd133d2446d429550de13080427441964f8f"},"schema_version":"1.0","source":{"id":"2606.28401","kind":"arxiv","version":1}},"canonical_sha256":"4e102db7a50f44b228e17cf13fba6a667c39d8f7730bfefd9f4e82c24d420cdd","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4e102db7a50f44b228e17cf13fba6a667c39d8f7730bfefd9f4e82c24d420cdd","first_computed_at":"2026-06-30T00:15:13.070732Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-30T00:15:13.070732Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"maBEe7sXGRO4Wx22YRqJUjexzivMupGp1bsHmFXrKD0Wi6T9qsKu8MrM0YB+OFqp9Bz3z65z03BH7ZyI1V4VBg==","signature_status":"signed_v1","signed_at":"2026-06-30T00:15:13.071127Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.28401","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:882e8d3814b314572bbe356a27602bd05251a85e524369a37ff0d0cbde0b89b4","sha256:da0c71bd85b7a240c4a7175109da834a2a6bb0871538830e95072f13f36cc293"],"state_sha256":"a399cee688df72812c25d57df1d018ffc2f71f461d3e5f5606a3e34d6d070944"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QKGc4z8UojRRyT/TeGD5TLCX31OWBfzconcetuaQe+YZKQK2DdXarys81ToO1ai0e3G0jAL3+CtclRHnRB3KDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-02T05:02:01.617526Z","bundle_sha256":"9abf85a37b627cccf884bc3b962defb30d3872b8f25f786457dc3f078cc740cb"}}