{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:BZZYV5ZZ4QRZTOSKH5PBYKC2HX","short_pith_number":"pith:BZZYV5ZZ","canonical_record":{"source":{"id":"2311.16567","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-11-28T07:14:41Z","cross_cats_sorted":[],"title_canon_sha256":"7269b390e39e8b33ce877b5e971c3f8fac3c522571c5f170c6e0a57db6212b44","abstract_canon_sha256":"3657e1d200ebe4d15b9dc83f58f813cae8d37784b26a23ed720d9fcf2e1f02a2"},"schema_version":"1.0"},"canonical_sha256":"0e738af739e42399ba4a3f5e1c285a3dc0d3fb7db46c2d8b9d2ca6e09586e3f7","source":{"kind":"arxiv","id":"2311.16567","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.16567","created_at":"2026-07-05T08:30:30Z"},{"alias_kind":"arxiv_version","alias_value":"2311.16567v2","created_at":"2026-07-05T08:30:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.16567","created_at":"2026-07-05T08:30:30Z"},{"alias_kind":"pith_short_12","alias_value":"BZZYV5ZZ4QRZ","created_at":"2026-07-05T08:30:30Z"},{"alias_kind":"pith_short_16","alias_value":"BZZYV5ZZ4QRZTOSK","created_at":"2026-07-05T08:30:30Z"},{"alias_kind":"pith_short_8","alias_value":"BZZYV5ZZ","created_at":"2026-07-05T08:30:30Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:BZZYV5ZZ4QRZTOSKH5PBYKC2HX","target":"record","payload":{"canonical_record":{"source":{"id":"2311.16567","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-11-28T07:14:41Z","cross_cats_sorted":[],"title_canon_sha256":"7269b390e39e8b33ce877b5e971c3f8fac3c522571c5f170c6e0a57db6212b44","abstract_canon_sha256":"3657e1d200ebe4d15b9dc83f58f813cae8d37784b26a23ed720d9fcf2e1f02a2"},"schema_version":"1.0"},"canonical_sha256":"0e738af739e42399ba4a3f5e1c285a3dc0d3fb7db46c2d8b9d2ca6e09586e3f7","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:30:30.211280Z","signature_b64":"HRwJwetWEma6PLIgOPEL29JL7jDDZcOhctapRpsr20QUgze85FeqMHFzE4P4zGDipmLnhxinfcE6IaApACn0Bg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0e738af739e42399ba4a3f5e1c285a3dc0d3fb7db46c2d8b9d2ca6e09586e3f7","last_reissued_at":"2026-07-05T08:30:30.210709Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:30:30.210709Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2311.16567","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":"2026-07-05T08:30:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"iPE/zqpuCiTWbyu1T4iyVx6xp29rwnm/2LyLjMNRY66nZ+oHKj77lL0Z1fEyIRaP4dT0U+jU8Fxq4twMW8zlCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T08:19:20.482569Z"},"content_sha256":"17c4496f6b800dd80aba0cf5899bd8bd831803df89aae1fc7b41474eb866b6e5","schema_version":"1.0","event_id":"sha256:17c4496f6b800dd80aba0cf5899bd8bd831803df89aae1fc7b41474eb866b6e5"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:BZZYV5ZZ4QRZTOSKH5PBYKC2HX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"MobileDiffusion: Instant Text-to-Image Generation on Mobile Devices","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Haolin Jia, Tingbo Hou, Yang Zhao, Yanwu Xu, Zhisheng Xiao","submitted_at":"2023-11-28T07:14:41Z","abstract_excerpt":"The deployment of large-scale text-to-image diffusion models on mobile devices is impeded by their substantial model size and slow inference speed. In this paper, we propose \\textbf{MobileDiffusion}, a highly efficient text-to-image diffusion model obtained through extensive optimizations in both architecture and sampling techniques. We conduct a comprehensive examination of model architecture design to reduce redundancy, enhance computational efficiency, and minimize model's parameter count, while preserving image generation quality. Additionally, we employ distillation and diffusion-GAN fine"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.16567","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/2311.16567/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":"2026-07-05T08:30:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"grtuZqGDus11COe7b+r1qqh6IqykEOv00vCnxcUgQb843K9MIXFPk0OHbkkmhhgyf0Z230q9VYi1lMAAJC9PBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T08:19:20.483091Z"},"content_sha256":"23a1ab11dbe6b2ed988c134727e6717ca23d710ff7cb56d375f1e4409d367716","schema_version":"1.0","event_id":"sha256:23a1ab11dbe6b2ed988c134727e6717ca23d710ff7cb56d375f1e4409d367716"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/BZZYV5ZZ4QRZTOSKH5PBYKC2HX/bundle.json","state_url":"https://pith.science/pith/BZZYV5ZZ4QRZTOSKH5PBYKC2HX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/BZZYV5ZZ4QRZTOSKH5PBYKC2HX/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":"2026-08-06T08:19:20Z","links":{"resolver":"https://pith.science/pith/BZZYV5ZZ4QRZTOSKH5PBYKC2HX","bundle":"https://pith.science/pith/BZZYV5ZZ4QRZTOSKH5PBYKC2HX/bundle.json","state":"https://pith.science/pith/BZZYV5ZZ4QRZTOSKH5PBYKC2HX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/BZZYV5ZZ4QRZTOSKH5PBYKC2HX/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:BZZYV5ZZ4QRZTOSKH5PBYKC2HX","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":"3657e1d200ebe4d15b9dc83f58f813cae8d37784b26a23ed720d9fcf2e1f02a2","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-11-28T07:14:41Z","title_canon_sha256":"7269b390e39e8b33ce877b5e971c3f8fac3c522571c5f170c6e0a57db6212b44"},"schema_version":"1.0","source":{"id":"2311.16567","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.16567","created_at":"2026-07-05T08:30:30Z"},{"alias_kind":"arxiv_version","alias_value":"2311.16567v2","created_at":"2026-07-05T08:30:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.16567","created_at":"2026-07-05T08:30:30Z"},{"alias_kind":"pith_short_12","alias_value":"BZZYV5ZZ4QRZ","created_at":"2026-07-05T08:30:30Z"},{"alias_kind":"pith_short_16","alias_value":"BZZYV5ZZ4QRZTOSK","created_at":"2026-07-05T08:30:30Z"},{"alias_kind":"pith_short_8","alias_value":"BZZYV5ZZ","created_at":"2026-07-05T08:30:30Z"}],"graph_snapshots":[{"event_id":"sha256:23a1ab11dbe6b2ed988c134727e6717ca23d710ff7cb56d375f1e4409d367716","target":"graph","created_at":"2026-07-05T08:30:30Z","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/2311.16567/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The deployment of large-scale text-to-image diffusion models on mobile devices is impeded by their substantial model size and slow inference speed. In this paper, we propose \\textbf{MobileDiffusion}, a highly efficient text-to-image diffusion model obtained through extensive optimizations in both architecture and sampling techniques. We conduct a comprehensive examination of model architecture design to reduce redundancy, enhance computational efficiency, and minimize model's parameter count, while preserving image generation quality. Additionally, we employ distillation and diffusion-GAN fine","authors_text":"Haolin Jia, Tingbo Hou, Yang Zhao, Yanwu Xu, Zhisheng Xiao","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-11-28T07:14:41Z","title":"MobileDiffusion: Instant Text-to-Image Generation on Mobile Devices"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.16567","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":"sha256:17c4496f6b800dd80aba0cf5899bd8bd831803df89aae1fc7b41474eb866b6e5","target":"record","created_at":"2026-07-05T08:30:30Z","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":"3657e1d200ebe4d15b9dc83f58f813cae8d37784b26a23ed720d9fcf2e1f02a2","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-11-28T07:14:41Z","title_canon_sha256":"7269b390e39e8b33ce877b5e971c3f8fac3c522571c5f170c6e0a57db6212b44"},"schema_version":"1.0","source":{"id":"2311.16567","kind":"arxiv","version":2}},"canonical_sha256":"0e738af739e42399ba4a3f5e1c285a3dc0d3fb7db46c2d8b9d2ca6e09586e3f7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0e738af739e42399ba4a3f5e1c285a3dc0d3fb7db46c2d8b9d2ca6e09586e3f7","first_computed_at":"2026-07-05T08:30:30.210709Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:30:30.210709Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"HRwJwetWEma6PLIgOPEL29JL7jDDZcOhctapRpsr20QUgze85FeqMHFzE4P4zGDipmLnhxinfcE6IaApACn0Bg==","signature_status":"signed_v1","signed_at":"2026-07-05T08:30:30.211280Z","signed_message":"canonical_sha256_bytes"},"source_id":"2311.16567","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:17c4496f6b800dd80aba0cf5899bd8bd831803df89aae1fc7b41474eb866b6e5","sha256:23a1ab11dbe6b2ed988c134727e6717ca23d710ff7cb56d375f1e4409d367716"],"state_sha256":"8dd2aed4d22f6be6abcccdafdd5cab63a3533ab98258bc34a0e141e259fd9b05"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zCnqJ0xPIgrSaR0+SkJvkwTfnruN5Wp8vywzekjgssQXMiXc9mMXDWyrOpKY6k0cRq9wSf0+rnrwwiVE3TUtAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T08:19:20.488052Z","bundle_sha256":"b8abf6c8d3fffdaf838991668b900674bc825ca648bcbc314fc1d0a3bc24c06c"}}