{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:IEI6GS5FDSYRVQORSHL5YPWHWS","short_pith_number":"pith:IEI6GS5F","canonical_record":{"source":{"id":"2506.05367","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-27T22:40:35Z","cross_cats_sorted":[],"title_canon_sha256":"8c44c29f0229952ba8086554eb73c6fe9b247f02fd60f62c193fac9bf28067f6","abstract_canon_sha256":"e97cadf331d3626df662950633e0e3073bd4249bab31b2c5725796e7f255ea15"},"schema_version":"1.0"},"canonical_sha256":"4111e34ba51cb11ac1d191d7dc3ec7b49d76b83f6d4e362c01042e7e684edcc4","source":{"kind":"arxiv","id":"2506.05367","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.05367","created_at":"2026-07-05T11:41:42Z"},{"alias_kind":"arxiv_version","alias_value":"2506.05367v2","created_at":"2026-07-05T11:41:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.05367","created_at":"2026-07-05T11:41:42Z"},{"alias_kind":"pith_short_12","alias_value":"IEI6GS5FDSYR","created_at":"2026-07-05T11:41:42Z"},{"alias_kind":"pith_short_16","alias_value":"IEI6GS5FDSYRVQOR","created_at":"2026-07-05T11:41:42Z"},{"alias_kind":"pith_short_8","alias_value":"IEI6GS5F","created_at":"2026-07-05T11:41:42Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:IEI6GS5FDSYRVQORSHL5YPWHWS","target":"record","payload":{"canonical_record":{"source":{"id":"2506.05367","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-27T22:40:35Z","cross_cats_sorted":[],"title_canon_sha256":"8c44c29f0229952ba8086554eb73c6fe9b247f02fd60f62c193fac9bf28067f6","abstract_canon_sha256":"e97cadf331d3626df662950633e0e3073bd4249bab31b2c5725796e7f255ea15"},"schema_version":"1.0"},"canonical_sha256":"4111e34ba51cb11ac1d191d7dc3ec7b49d76b83f6d4e362c01042e7e684edcc4","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:41:42.850985Z","signature_b64":"mY3jto8tXPHhRD0f8QI9jlKF/HHltPiiCEsDMvjVIaVfrzkKMb4f9KwnlrAuUXC2Ox0vfHAGc62mtTsjpaiaCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4111e34ba51cb11ac1d191d7dc3ec7b49d76b83f6d4e362c01042e7e684edcc4","last_reissued_at":"2026-07-05T11:41:42.850453Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:41:42.850453Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2506.05367","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:41:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3W4wBxCvv2t9XEe1dID90xGY/wumzlIXrjN86wmx7+yiUwM40B/ToAesnSf/pc432234NwG/9Ldm48is9E/UAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T23:28:28.488483Z"},"content_sha256":"79b24ca028457e686d33d79da00652f52e3a48857dc8be4323ed60116bac61e5","schema_version":"1.0","event_id":"sha256:79b24ca028457e686d33d79da00652f52e3a48857dc8be4323ed60116bac61e5"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:IEI6GS5FDSYRVQORSHL5YPWHWS","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Aakash Garg, Andrii Tsarov, Libing Zeng, Nima Khademi Kalantari","submitted_at":"2025-05-27T22:40:35Z","abstract_excerpt":"In this paper, we propose a novel diffusion-based approach to generate stereo images given a text prompt. Since stereo image datasets with large baselines are scarce, training a diffusion model from scratch is not feasible. Therefore, we propose leveraging the strong priors learned by Stable Diffusion and fine-tuning it on stereo image datasets to adapt it to the task of stereo generation. To improve stereo consistency and text-to-image alignment, we further tune the model using prompt alignment and our proposed stereo consistency reward functions. Comprehensive experiments demonstrate the sup"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.05367","kind":"arxiv","version":2},"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/2506.05367/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":"2026-07-05T11:41:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aCagxvHxDaQqgJAkB4Lyr6sFA7BfDm0RaQ1fw65fH9If7WC3jtsjYdxaoYLAZw7bpjTPy19yEOfhu2yMdFK+CA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T23:28:28.489124Z"},"content_sha256":"0395104b450aaaee97c76275a10e53db2005b36258808b478eb487112b345746","schema_version":"1.0","event_id":"sha256:0395104b450aaaee97c76275a10e53db2005b36258808b478eb487112b345746"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/IEI6GS5FDSYRVQORSHL5YPWHWS/bundle.json","state_url":"https://pith.science/pith/IEI6GS5FDSYRVQORSHL5YPWHWS/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/IEI6GS5FDSYRVQORSHL5YPWHWS/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":"2026-08-07T23:28:28Z","links":{"resolver":"https://pith.science/pith/IEI6GS5FDSYRVQORSHL5YPWHWS","bundle":"https://pith.science/pith/IEI6GS5FDSYRVQORSHL5YPWHWS/bundle.json","state":"https://pith.science/pith/IEI6GS5FDSYRVQORSHL5YPWHWS/state.json","well_known_bundle":"https://pith.science/.well-known/pith/IEI6GS5FDSYRVQORSHL5YPWHWS/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:IEI6GS5FDSYRVQORSHL5YPWHWS","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":"e97cadf331d3626df662950633e0e3073bd4249bab31b2c5725796e7f255ea15","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-27T22:40:35Z","title_canon_sha256":"8c44c29f0229952ba8086554eb73c6fe9b247f02fd60f62c193fac9bf28067f6"},"schema_version":"1.0","source":{"id":"2506.05367","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.05367","created_at":"2026-07-05T11:41:42Z"},{"alias_kind":"arxiv_version","alias_value":"2506.05367v2","created_at":"2026-07-05T11:41:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.05367","created_at":"2026-07-05T11:41:42Z"},{"alias_kind":"pith_short_12","alias_value":"IEI6GS5FDSYR","created_at":"2026-07-05T11:41:42Z"},{"alias_kind":"pith_short_16","alias_value":"IEI6GS5FDSYRVQOR","created_at":"2026-07-05T11:41:42Z"},{"alias_kind":"pith_short_8","alias_value":"IEI6GS5F","created_at":"2026-07-05T11:41:42Z"}],"graph_snapshots":[{"event_id":"sha256:0395104b450aaaee97c76275a10e53db2005b36258808b478eb487112b345746","target":"graph","created_at":"2026-07-05T11:41:42Z","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/2506.05367/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this paper, we propose a novel diffusion-based approach to generate stereo images given a text prompt. Since stereo image datasets with large baselines are scarce, training a diffusion model from scratch is not feasible. Therefore, we propose leveraging the strong priors learned by Stable Diffusion and fine-tuning it on stereo image datasets to adapt it to the task of stereo generation. To improve stereo consistency and text-to-image alignment, we further tune the model using prompt alignment and our proposed stereo consistency reward functions. Comprehensive experiments demonstrate the sup","authors_text":"Aakash Garg, Andrii Tsarov, Libing Zeng, Nima Khademi Kalantari","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-27T22:40:35Z","title":"Text2Stereo: Repurposing Stable Diffusion for Stereo Generation with Consistency Rewards"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.05367","kind":"arxiv","version":2},"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":"sha256:79b24ca028457e686d33d79da00652f52e3a48857dc8be4323ed60116bac61e5","target":"record","created_at":"2026-07-05T11:41:42Z","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":"e97cadf331d3626df662950633e0e3073bd4249bab31b2c5725796e7f255ea15","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-27T22:40:35Z","title_canon_sha256":"8c44c29f0229952ba8086554eb73c6fe9b247f02fd60f62c193fac9bf28067f6"},"schema_version":"1.0","source":{"id":"2506.05367","kind":"arxiv","version":2}},"canonical_sha256":"4111e34ba51cb11ac1d191d7dc3ec7b49d76b83f6d4e362c01042e7e684edcc4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4111e34ba51cb11ac1d191d7dc3ec7b49d76b83f6d4e362c01042e7e684edcc4","first_computed_at":"2026-07-05T11:41:42.850453Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:41:42.850453Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"mY3jto8tXPHhRD0f8QI9jlKF/HHltPiiCEsDMvjVIaVfrzkKMb4f9KwnlrAuUXC2Ox0vfHAGc62mtTsjpaiaCA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:41:42.850985Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.05367","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:79b24ca028457e686d33d79da00652f52e3a48857dc8be4323ed60116bac61e5","sha256:0395104b450aaaee97c76275a10e53db2005b36258808b478eb487112b345746"],"state_sha256":"556807e8f0bdaf2fcd4033922778eded5359f557250ed9b4748b61a4f7c3856c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PSgzPptdmErURrsNTO/2lAk8z1gK2z9H3YXSD2mnvT9rU8p8wu2AEsei72uuU2rPDKacOfjRc7I6hJ1ojRGmBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T23:28:28.494363Z","bundle_sha256":"1159549311ef972e754b3f724d71b8c40c15bb90e95028328174f948bce7c530"}}