{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:Q5LCUAXK6I3XX7TV4XPBBFSOYN","short_pith_number":"pith:Q5LCUAXK","canonical_record":{"source":{"id":"2501.01926","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-01-03T17:56:28Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"2c0060ba411dd04cb31d416e03f2ab712ea9cb5d59da10d086053312be271c9c","abstract_canon_sha256":"d1dd5ab7c408a6840f19dafa74f2740c6ff0486131904e5d18097982c9328034"},"schema_version":"1.0"},"canonical_sha256":"87562a02eaf2377bfe75e5de10964ec342454a85ce49d4ddfa4c20b6969766ba","source":{"kind":"arxiv","id":"2501.01926","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.01926","created_at":"2026-06-01T01:02:14Z"},{"alias_kind":"arxiv_version","alias_value":"2501.01926v3","created_at":"2026-06-01T01:02:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.01926","created_at":"2026-06-01T01:02:14Z"},{"alias_kind":"pith_short_12","alias_value":"Q5LCUAXK6I3X","created_at":"2026-06-01T01:02:14Z"},{"alias_kind":"pith_short_16","alias_value":"Q5LCUAXK6I3XX7TV","created_at":"2026-06-01T01:02:14Z"},{"alias_kind":"pith_short_8","alias_value":"Q5LCUAXK","created_at":"2026-06-01T01:02:14Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:Q5LCUAXK6I3XX7TV4XPBBFSOYN","target":"record","payload":{"canonical_record":{"source":{"id":"2501.01926","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-01-03T17:56:28Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"2c0060ba411dd04cb31d416e03f2ab712ea9cb5d59da10d086053312be271c9c","abstract_canon_sha256":"d1dd5ab7c408a6840f19dafa74f2740c6ff0486131904e5d18097982c9328034"},"schema_version":"1.0"},"canonical_sha256":"87562a02eaf2377bfe75e5de10964ec342454a85ce49d4ddfa4c20b6969766ba","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-01T01:02:14.218282Z","signature_b64":"IBjIFzJZRpN4QvVdndQEC0qyK4hhFH35W97XcaUhvZ6gvhbs/ZEexRXT2xW2smYzOH/yiY47I2u0fAy9cT6rDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"87562a02eaf2377bfe75e5de10964ec342454a85ce49d4ddfa4c20b6969766ba","last_reissued_at":"2026-06-01T01:02:14.216824Z","signature_status":"signed_v1","first_computed_at":"2026-06-01T01:02:14.216824Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2501.01926","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-06-01T01:02:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GKZuuZozxLj0Y/tR4mIQgzo1TPqvPievuaKSzaq1tdtIhUIsOY9hDEF+8/EUeijCJ5D/osQ7iQOXDSeZHzT+AA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T21:24:55.401404Z"},"content_sha256":"65caa6ac139645a72a2df3e41865c8e2eff53c04cd9293a5e9d349b351bd5c82","schema_version":"1.0","event_id":"sha256:65caa6ac139645a72a2df3e41865c8e2eff53c04cd9293a5e9d349b351bd5c82"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:Q5LCUAXK6I3XX7TV4XPBBFSOYN","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Cross-Modal Attention Calibration for LVLM Hallucination Mitigation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Guanbin Li, Jiacheng Zhang, Jiaming Li, Lin Ma, Zequn Jie","submitted_at":"2025-01-03T17:56:28Z","abstract_excerpt":"Large vision-language models (LVLMs) have shown remarkable capabilities in visual-language understanding. Despite their success, LVLMs still suffer from generating hallucinations in complex generation tasks, leading to inconsistencies between visual inputs and generated content. To address this issue, some approaches have introduced inference-time interventions, such as contrastive decoding, to reduce overreliance on language priors. However, these approaches overlook hallucinations stemming from position bias and spurious inter-modality correlations. In this paper, we propose a Cross-Modal At"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.01926","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2501.01926/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":"2026-06-01T01:02:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Dx/OYRHuWVnOWzeOmPgJcKLx5H68X4/PNYAIbcUhf34FOuXgJ5eOXTicMnh+/mIqF8PrMwh4v86Rtyx/4KWWAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T21:24:55.401780Z"},"content_sha256":"e25d1ed790361c42bdb9288f36d5e88b01a15ceefef50579aa0bad8ce1957f45","schema_version":"1.0","event_id":"sha256:e25d1ed790361c42bdb9288f36d5e88b01a15ceefef50579aa0bad8ce1957f45"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/Q5LCUAXK6I3XX7TV4XPBBFSOYN/bundle.json","state_url":"https://pith.science/pith/Q5LCUAXK6I3XX7TV4XPBBFSOYN/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/Q5LCUAXK6I3XX7TV4XPBBFSOYN/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":"2026-06-01T21:24:55Z","links":{"resolver":"https://pith.science/pith/Q5LCUAXK6I3XX7TV4XPBBFSOYN","bundle":"https://pith.science/pith/Q5LCUAXK6I3XX7TV4XPBBFSOYN/bundle.json","state":"https://pith.science/pith/Q5LCUAXK6I3XX7TV4XPBBFSOYN/state.json","well_known_bundle":"https://pith.science/.well-known/pith/Q5LCUAXK6I3XX7TV4XPBBFSOYN/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:Q5LCUAXK6I3XX7TV4XPBBFSOYN","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":"d1dd5ab7c408a6840f19dafa74f2740c6ff0486131904e5d18097982c9328034","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-01-03T17:56:28Z","title_canon_sha256":"2c0060ba411dd04cb31d416e03f2ab712ea9cb5d59da10d086053312be271c9c"},"schema_version":"1.0","source":{"id":"2501.01926","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.01926","created_at":"2026-06-01T01:02:14Z"},{"alias_kind":"arxiv_version","alias_value":"2501.01926v3","created_at":"2026-06-01T01:02:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.01926","created_at":"2026-06-01T01:02:14Z"},{"alias_kind":"pith_short_12","alias_value":"Q5LCUAXK6I3X","created_at":"2026-06-01T01:02:14Z"},{"alias_kind":"pith_short_16","alias_value":"Q5LCUAXK6I3XX7TV","created_at":"2026-06-01T01:02:14Z"},{"alias_kind":"pith_short_8","alias_value":"Q5LCUAXK","created_at":"2026-06-01T01:02:14Z"}],"graph_snapshots":[{"event_id":"sha256:e25d1ed790361c42bdb9288f36d5e88b01a15ceefef50579aa0bad8ce1957f45","target":"graph","created_at":"2026-06-01T01:02:14Z","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/2501.01926/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large vision-language models (LVLMs) have shown remarkable capabilities in visual-language understanding. Despite their success, LVLMs still suffer from generating hallucinations in complex generation tasks, leading to inconsistencies between visual inputs and generated content. To address this issue, some approaches have introduced inference-time interventions, such as contrastive decoding, to reduce overreliance on language priors. However, these approaches overlook hallucinations stemming from position bias and spurious inter-modality correlations. In this paper, we propose a Cross-Modal At","authors_text":"Guanbin Li, Jiacheng Zhang, Jiaming Li, Lin Ma, Zequn Jie","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-01-03T17:56:28Z","title":"Cross-Modal Attention Calibration for LVLM Hallucination Mitigation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.01926","kind":"arxiv","version":3},"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":"sha256:65caa6ac139645a72a2df3e41865c8e2eff53c04cd9293a5e9d349b351bd5c82","target":"record","created_at":"2026-06-01T01:02:14Z","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":"d1dd5ab7c408a6840f19dafa74f2740c6ff0486131904e5d18097982c9328034","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-01-03T17:56:28Z","title_canon_sha256":"2c0060ba411dd04cb31d416e03f2ab712ea9cb5d59da10d086053312be271c9c"},"schema_version":"1.0","source":{"id":"2501.01926","kind":"arxiv","version":3}},"canonical_sha256":"87562a02eaf2377bfe75e5de10964ec342454a85ce49d4ddfa4c20b6969766ba","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"87562a02eaf2377bfe75e5de10964ec342454a85ce49d4ddfa4c20b6969766ba","first_computed_at":"2026-06-01T01:02:14.216824Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-01T01:02:14.216824Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"IBjIFzJZRpN4QvVdndQEC0qyK4hhFH35W97XcaUhvZ6gvhbs/ZEexRXT2xW2smYzOH/yiY47I2u0fAy9cT6rDQ==","signature_status":"signed_v1","signed_at":"2026-06-01T01:02:14.218282Z","signed_message":"canonical_sha256_bytes"},"source_id":"2501.01926","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:65caa6ac139645a72a2df3e41865c8e2eff53c04cd9293a5e9d349b351bd5c82","sha256:e25d1ed790361c42bdb9288f36d5e88b01a15ceefef50579aa0bad8ce1957f45"],"state_sha256":"c92493f2bc5043de7dd3bc411e6953823783fff4b88a4f1f2ffc311158e14096"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nH36WEK1brgV26B53SYz6lflH9ITsxNQ/ZorqkOcjYJfsuhD/x14dubzZ2mGbOgLJiQg/HdQa2sfCgwEIt0sAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-01T21:24:55.403864Z","bundle_sha256":"cc5def9adddeb734da685fa4a85defddc121783a417f7b00bf7edaa3fcb2ad4b"}}