{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:6FHI3XNCNKGBPE4RSFBSDB7BXZ","short_pith_number":"pith:6FHI3XNC","canonical_record":{"source":{"id":"2606.04015","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2026-05-31T15:29:36Z","cross_cats_sorted":[],"title_canon_sha256":"865981e15c2eead264f5d2d9ae3f19b03c87029d1055f4ed618ca43fd17dd714","abstract_canon_sha256":"6e558ee9bc203ba34c09d7ecae527bf2e2aa2fb98cdf5a86b8b8924bcde4014d"},"schema_version":"1.0"},"canonical_sha256":"f14e8ddda26a8c17939191432187e1be502538dd1247a32940de36130bbca577","source":{"kind":"arxiv","id":"2606.04015","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.04015","created_at":"2026-06-04T00:06:44Z"},{"alias_kind":"arxiv_version","alias_value":"2606.04015v1","created_at":"2026-06-04T00:06:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.04015","created_at":"2026-06-04T00:06:44Z"},{"alias_kind":"pith_short_12","alias_value":"6FHI3XNCNKGB","created_at":"2026-06-04T00:06:44Z"},{"alias_kind":"pith_short_16","alias_value":"6FHI3XNCNKGBPE4R","created_at":"2026-06-04T00:06:44Z"},{"alias_kind":"pith_short_8","alias_value":"6FHI3XNC","created_at":"2026-06-04T00:06:44Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:6FHI3XNCNKGBPE4RSFBSDB7BXZ","target":"record","payload":{"canonical_record":{"source":{"id":"2606.04015","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2026-05-31T15:29:36Z","cross_cats_sorted":[],"title_canon_sha256":"865981e15c2eead264f5d2d9ae3f19b03c87029d1055f4ed618ca43fd17dd714","abstract_canon_sha256":"6e558ee9bc203ba34c09d7ecae527bf2e2aa2fb98cdf5a86b8b8924bcde4014d"},"schema_version":"1.0"},"canonical_sha256":"f14e8ddda26a8c17939191432187e1be502538dd1247a32940de36130bbca577","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-04T00:06:44.554119Z","signature_b64":"4ftzGOy1FLKf1Ji0xH6HhMgPsMQ8dbdajglG2lrPJi9fIY0MkxlJQ5Ozqzcx7bwd+7foClnHtqC0PtLomkkLBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f14e8ddda26a8c17939191432187e1be502538dd1247a32940de36130bbca577","last_reissued_at":"2026-06-04T00:06:44.553741Z","signature_status":"signed_v1","first_computed_at":"2026-06-04T00:06:44.553741Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2606.04015","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":"2026-06-04T00:06:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YymQmh17Th3m1Ey9eROx+9Z11RpMZwxBnkjCYd9Rw9eXODdGuy4/nAHlif587VkT2h6sXEcCA8WnQ1CB1AWwCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-06T20:15:27.810522Z"},"content_sha256":"4070ff21aa55fe3bd35846f00e304d6c0d30e64a3d76e6dec75a0d24eecdd911","schema_version":"1.0","event_id":"sha256:4070ff21aa55fe3bd35846f00e304d6c0d30e64a3d76e6dec75a0d24eecdd911"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:6FHI3XNCNKGBPE4RSFBSDB7BXZ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"GenED-SC: Generative Editing Semantic Communication with Integrated Multi-Modal LLMs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"eess.SP","authors_text":"Li Ping Qian, Mingze Gong, Shuoyao Wang, Suzhi Bi, Weisheng Xie","submitted_at":"2026-05-31T15:29:36Z","abstract_excerpt":"Deep learning-based joint source-channel coding has recently demonstrated strong potential for semantic communication (SemComm). However, most existing approaches focus on optimizing visual-fidelity metrics, which can lead to reduced perceptual quality. Generative model-based SemComm leverages rich prior knowledge from large-scale pre-training to enhance perceptual quality, but often at the cost of increased distortion and unreliability. This paper addresses the above issues by proposing a two-stage semantic image transmission framework, integrating a multimodal large language model (MLLM) for"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.04015","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/2606.04015/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":"2026-06-04T00:06:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Zh6vrIXgQ5ST2N5rvI8nhmS3e3HLCV3gk27xWGU7c8PkVo/MzHfpDVZoDnJ/g7gPt9kIv0ePTbIgMwHImw41Cw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-06T20:15:27.810988Z"},"content_sha256":"dadb44469d38e95cf4c52a2568a9fd52ac9849eab5ef718d4dafaa7b829c94ae","schema_version":"1.0","event_id":"sha256:dadb44469d38e95cf4c52a2568a9fd52ac9849eab5ef718d4dafaa7b829c94ae"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/6FHI3XNCNKGBPE4RSFBSDB7BXZ/bundle.json","state_url":"https://pith.science/pith/6FHI3XNCNKGBPE4RSFBSDB7BXZ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/6FHI3XNCNKGBPE4RSFBSDB7BXZ/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":"2026-06-06T20:15:27Z","links":{"resolver":"https://pith.science/pith/6FHI3XNCNKGBPE4RSFBSDB7BXZ","bundle":"https://pith.science/pith/6FHI3XNCNKGBPE4RSFBSDB7BXZ/bundle.json","state":"https://pith.science/pith/6FHI3XNCNKGBPE4RSFBSDB7BXZ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/6FHI3XNCNKGBPE4RSFBSDB7BXZ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:6FHI3XNCNKGBPE4RSFBSDB7BXZ","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":"6e558ee9bc203ba34c09d7ecae527bf2e2aa2fb98cdf5a86b8b8924bcde4014d","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2026-05-31T15:29:36Z","title_canon_sha256":"865981e15c2eead264f5d2d9ae3f19b03c87029d1055f4ed618ca43fd17dd714"},"schema_version":"1.0","source":{"id":"2606.04015","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.04015","created_at":"2026-06-04T00:06:44Z"},{"alias_kind":"arxiv_version","alias_value":"2606.04015v1","created_at":"2026-06-04T00:06:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.04015","created_at":"2026-06-04T00:06:44Z"},{"alias_kind":"pith_short_12","alias_value":"6FHI3XNCNKGB","created_at":"2026-06-04T00:06:44Z"},{"alias_kind":"pith_short_16","alias_value":"6FHI3XNCNKGBPE4R","created_at":"2026-06-04T00:06:44Z"},{"alias_kind":"pith_short_8","alias_value":"6FHI3XNC","created_at":"2026-06-04T00:06:44Z"}],"graph_snapshots":[{"event_id":"sha256:dadb44469d38e95cf4c52a2568a9fd52ac9849eab5ef718d4dafaa7b829c94ae","target":"graph","created_at":"2026-06-04T00:06:44Z","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/2606.04015/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deep learning-based joint source-channel coding has recently demonstrated strong potential for semantic communication (SemComm). However, most existing approaches focus on optimizing visual-fidelity metrics, which can lead to reduced perceptual quality. Generative model-based SemComm leverages rich prior knowledge from large-scale pre-training to enhance perceptual quality, but often at the cost of increased distortion and unreliability. This paper addresses the above issues by proposing a two-stage semantic image transmission framework, integrating a multimodal large language model (MLLM) for","authors_text":"Li Ping Qian, Mingze Gong, Shuoyao Wang, Suzhi Bi, Weisheng Xie","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2026-05-31T15:29:36Z","title":"GenED-SC: Generative Editing Semantic Communication with Integrated Multi-Modal LLMs"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.04015","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":"sha256:4070ff21aa55fe3bd35846f00e304d6c0d30e64a3d76e6dec75a0d24eecdd911","target":"record","created_at":"2026-06-04T00:06:44Z","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":"6e558ee9bc203ba34c09d7ecae527bf2e2aa2fb98cdf5a86b8b8924bcde4014d","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2026-05-31T15:29:36Z","title_canon_sha256":"865981e15c2eead264f5d2d9ae3f19b03c87029d1055f4ed618ca43fd17dd714"},"schema_version":"1.0","source":{"id":"2606.04015","kind":"arxiv","version":1}},"canonical_sha256":"f14e8ddda26a8c17939191432187e1be502538dd1247a32940de36130bbca577","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f14e8ddda26a8c17939191432187e1be502538dd1247a32940de36130bbca577","first_computed_at":"2026-06-04T00:06:44.553741Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-04T00:06:44.553741Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"4ftzGOy1FLKf1Ji0xH6HhMgPsMQ8dbdajglG2lrPJi9fIY0MkxlJQ5Ozqzcx7bwd+7foClnHtqC0PtLomkkLBQ==","signature_status":"signed_v1","signed_at":"2026-06-04T00:06:44.554119Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.04015","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4070ff21aa55fe3bd35846f00e304d6c0d30e64a3d76e6dec75a0d24eecdd911","sha256:dadb44469d38e95cf4c52a2568a9fd52ac9849eab5ef718d4dafaa7b829c94ae"],"state_sha256":"8900812433cc1e622b7a74fd82f1b2068078ac30c48151f01f3aeffc21af73a6"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"x4gi4Tck43hzCqb6oT3bfHoH2IHBeyFu3TWD0i6rS6jUTJPmCA04lbPGz9nXoEVr96RxshrLaaJ7eyEyosl5Ag==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-06T20:15:27.813152Z","bundle_sha256":"e87d0db8f8e3d7c39c150807b8ba551652ad118530edf604cab9e38d93629491"}}