{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:4DOMHNB5UJM7EOALXO5ISWUTZ4","short_pith_number":"pith:4DOMHNB5","canonical_record":{"source":{"id":"2606.25319","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-06-24T02:32:38Z","cross_cats_sorted":[],"title_canon_sha256":"27611270336c4379c303bcac07786c5e900ef8a4090854b6d3d4eb04e2fdc659","abstract_canon_sha256":"95adf0ae4722b5b66e4ed4725899696aff4f905cbd6812c788aa0c8b764df006"},"schema_version":"1.0"},"canonical_sha256":"e0dcc3b43da259f2380bbbba895a93cf3a7b598ff64b38bc11882fc12ad8de87","source":{"kind":"arxiv","id":"2606.25319","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.25319","created_at":"2026-06-25T01:18:01Z"},{"alias_kind":"arxiv_version","alias_value":"2606.25319v1","created_at":"2026-06-25T01:18:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.25319","created_at":"2026-06-25T01:18:01Z"},{"alias_kind":"pith_short_12","alias_value":"4DOMHNB5UJM7","created_at":"2026-06-25T01:18:01Z"},{"alias_kind":"pith_short_16","alias_value":"4DOMHNB5UJM7EOAL","created_at":"2026-06-25T01:18:01Z"},{"alias_kind":"pith_short_8","alias_value":"4DOMHNB5","created_at":"2026-06-25T01:18:01Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:4DOMHNB5UJM7EOALXO5ISWUTZ4","target":"record","payload":{"canonical_record":{"source":{"id":"2606.25319","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-06-24T02:32:38Z","cross_cats_sorted":[],"title_canon_sha256":"27611270336c4379c303bcac07786c5e900ef8a4090854b6d3d4eb04e2fdc659","abstract_canon_sha256":"95adf0ae4722b5b66e4ed4725899696aff4f905cbd6812c788aa0c8b764df006"},"schema_version":"1.0"},"canonical_sha256":"e0dcc3b43da259f2380bbbba895a93cf3a7b598ff64b38bc11882fc12ad8de87","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-25T01:18:01.953167Z","signature_b64":"TmzTt3sl0Z6LzyxEcDIr52k3baD/9jNQCpZ+hZ+sGG8xAYU34WKdwUnjCwg123ETe94JlORsXtmPdX1aGqGhBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e0dcc3b43da259f2380bbbba895a93cf3a7b598ff64b38bc11882fc12ad8de87","last_reissued_at":"2026-06-25T01:18:01.952752Z","signature_status":"signed_v1","first_computed_at":"2026-06-25T01:18:01.952752Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2606.25319","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":"2026-06-25T01:18:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"AFRn4QPz/tZzdXwrAnVQNUvXGUsOGVrOyf7J6suVBUF0vOOpT7KKAF5amDznWpYH7kF4xkXzsa6lLOmrqDxuDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-25T08:04:32.409590Z"},"content_sha256":"673c49125bb3ca33bc8088c85a648566d56982d1fbb6aa279542c24496438322","schema_version":"1.0","event_id":"sha256:673c49125bb3ca33bc8088c85a648566d56982d1fbb6aa279542c24496438322"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:4DOMHNB5UJM7EOALXO5ISWUTZ4","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"V-Zero: Answer-Label-Free On-Policy Distillation with Contrastive Evidence Gating for Fine-Grained Visual Reasoning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Haoxiang Sun, Jiancheng Lv, Jian Zhao, Langxuan Deng, Li Yuan, Peiqi Jia, Tao Wang, Yuhao Zhou, Zhihang Yi","submitted_at":"2026-06-24T02:32:38Z","abstract_excerpt":"Fine-grained visual reasoning requires multimodal large language models (MLLMs) to identify task-relevant visual evidence and ground their reasoning in local image regions. Existing agentic methods typically rely on reinforcement learning with verifiable rewards or supervised fine-tuning on large-scale annotated reasoning traces, leading to costly exploration, hand-designed verification rules, or heavy dependence on textual supervision. A natural way to avoid such external answer labels is to learn from trajectories sampled by the student itself, which points to On-Policy Distillation (OPD). T"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.25319","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/2606.25319/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":"2026-06-25T01:18:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"f4FFXzMBtctYjvojAOp5IDmH6L1Vp7I0cY8nKbDcyLa0nFg89Wql+xZWO8Q3TwJazyQqRJSdmJOimECpM5jIAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-25T08:04:32.409978Z"},"content_sha256":"de7ea5ba9a65319ed77f57408af1e2f38142c5e1e86c7febdaa8cb666e2358c5","schema_version":"1.0","event_id":"sha256:de7ea5ba9a65319ed77f57408af1e2f38142c5e1e86c7febdaa8cb666e2358c5"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/4DOMHNB5UJM7EOALXO5ISWUTZ4/bundle.json","state_url":"https://pith.science/pith/4DOMHNB5UJM7EOALXO5ISWUTZ4/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/4DOMHNB5UJM7EOALXO5ISWUTZ4/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":"2026-06-25T08:04:32Z","links":{"resolver":"https://pith.science/pith/4DOMHNB5UJM7EOALXO5ISWUTZ4","bundle":"https://pith.science/pith/4DOMHNB5UJM7EOALXO5ISWUTZ4/bundle.json","state":"https://pith.science/pith/4DOMHNB5UJM7EOALXO5ISWUTZ4/state.json","well_known_bundle":"https://pith.science/.well-known/pith/4DOMHNB5UJM7EOALXO5ISWUTZ4/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:4DOMHNB5UJM7EOALXO5ISWUTZ4","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":"95adf0ae4722b5b66e4ed4725899696aff4f905cbd6812c788aa0c8b764df006","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-06-24T02:32:38Z","title_canon_sha256":"27611270336c4379c303bcac07786c5e900ef8a4090854b6d3d4eb04e2fdc659"},"schema_version":"1.0","source":{"id":"2606.25319","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.25319","created_at":"2026-06-25T01:18:01Z"},{"alias_kind":"arxiv_version","alias_value":"2606.25319v1","created_at":"2026-06-25T01:18:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.25319","created_at":"2026-06-25T01:18:01Z"},{"alias_kind":"pith_short_12","alias_value":"4DOMHNB5UJM7","created_at":"2026-06-25T01:18:01Z"},{"alias_kind":"pith_short_16","alias_value":"4DOMHNB5UJM7EOAL","created_at":"2026-06-25T01:18:01Z"},{"alias_kind":"pith_short_8","alias_value":"4DOMHNB5","created_at":"2026-06-25T01:18:01Z"}],"graph_snapshots":[{"event_id":"sha256:de7ea5ba9a65319ed77f57408af1e2f38142c5e1e86c7febdaa8cb666e2358c5","target":"graph","created_at":"2026-06-25T01:18:01Z","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/2606.25319/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Fine-grained visual reasoning requires multimodal large language models (MLLMs) to identify task-relevant visual evidence and ground their reasoning in local image regions. Existing agentic methods typically rely on reinforcement learning with verifiable rewards or supervised fine-tuning on large-scale annotated reasoning traces, leading to costly exploration, hand-designed verification rules, or heavy dependence on textual supervision. A natural way to avoid such external answer labels is to learn from trajectories sampled by the student itself, which points to On-Policy Distillation (OPD). T","authors_text":"Haoxiang Sun, Jiancheng Lv, Jian Zhao, Langxuan Deng, Li Yuan, Peiqi Jia, Tao Wang, Yuhao Zhou, Zhihang Yi","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-06-24T02:32:38Z","title":"V-Zero: Answer-Label-Free On-Policy Distillation with Contrastive Evidence Gating for Fine-Grained Visual Reasoning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.25319","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":"sha256:673c49125bb3ca33bc8088c85a648566d56982d1fbb6aa279542c24496438322","target":"record","created_at":"2026-06-25T01:18:01Z","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":"95adf0ae4722b5b66e4ed4725899696aff4f905cbd6812c788aa0c8b764df006","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-06-24T02:32:38Z","title_canon_sha256":"27611270336c4379c303bcac07786c5e900ef8a4090854b6d3d4eb04e2fdc659"},"schema_version":"1.0","source":{"id":"2606.25319","kind":"arxiv","version":1}},"canonical_sha256":"e0dcc3b43da259f2380bbbba895a93cf3a7b598ff64b38bc11882fc12ad8de87","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e0dcc3b43da259f2380bbbba895a93cf3a7b598ff64b38bc11882fc12ad8de87","first_computed_at":"2026-06-25T01:18:01.952752Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-25T01:18:01.952752Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"TmzTt3sl0Z6LzyxEcDIr52k3baD/9jNQCpZ+hZ+sGG8xAYU34WKdwUnjCwg123ETe94JlORsXtmPdX1aGqGhBQ==","signature_status":"signed_v1","signed_at":"2026-06-25T01:18:01.953167Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.25319","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:673c49125bb3ca33bc8088c85a648566d56982d1fbb6aa279542c24496438322","sha256:de7ea5ba9a65319ed77f57408af1e2f38142c5e1e86c7febdaa8cb666e2358c5"],"state_sha256":"d0cd099e97e042b222c67aeb71374d9bd5267b61c19b63633a70ff9703085530"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QxHx6Xc2lvEr552tEmyjqdvnjZVFWQ5SEn4+LQeSqsVpuk9ALvDPTrzDjH/wPehmankB9q2R12i1KsX24RymCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-25T08:04:32.412406Z","bundle_sha256":"650e1f7598e1e9a9d3549e960e9a646b8e2da2127a4f11e41b3b8ac176f79229"}}