{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:2JY23BPSNKNTDFUMZLJLBJ3RW3","short_pith_number":"pith:2JY23BPS","canonical_record":{"source":{"id":"2607.20048","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-22T11:42:42Z","cross_cats_sorted":[],"title_canon_sha256":"240b897e90d8c309b737f7947d0341d575c4d5a0f17d0bea9a62df0b9fd7b9e7","abstract_canon_sha256":"32bcb70cb4f72c077f17976ce5747805fa4383490f5a9c94d3b0365e229b71b6"},"schema_version":"1.0"},"canonical_sha256":"d271ad85f26a9b31968ccad2b0a771b6cfaf01aba1fb4d165338548ade840805","source":{"kind":"arxiv","id":"2607.20048","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.20048","created_at":"2026-07-23T01:24:57Z"},{"alias_kind":"arxiv_version","alias_value":"2607.20048v1","created_at":"2026-07-23T01:24:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.20048","created_at":"2026-07-23T01:24:57Z"},{"alias_kind":"pith_short_12","alias_value":"2JY23BPSNKNT","created_at":"2026-07-23T01:24:57Z"},{"alias_kind":"pith_short_16","alias_value":"2JY23BPSNKNTDFUM","created_at":"2026-07-23T01:24:57Z"},{"alias_kind":"pith_short_8","alias_value":"2JY23BPS","created_at":"2026-07-23T01:24:57Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:2JY23BPSNKNTDFUMZLJLBJ3RW3","target":"record","payload":{"canonical_record":{"source":{"id":"2607.20048","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-22T11:42:42Z","cross_cats_sorted":[],"title_canon_sha256":"240b897e90d8c309b737f7947d0341d575c4d5a0f17d0bea9a62df0b9fd7b9e7","abstract_canon_sha256":"32bcb70cb4f72c077f17976ce5747805fa4383490f5a9c94d3b0365e229b71b6"},"schema_version":"1.0"},"canonical_sha256":"d271ad85f26a9b31968ccad2b0a771b6cfaf01aba1fb4d165338548ade840805","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-23T01:24:57.327744Z","signature_b64":"dKX1peUuX2So7NnMP6OS0Km5ey0TUx/1w1Wg1VpInbgsb7TfgInvSph7dg9MCAzjTE8ZNcgeP95a5yOfWO90Bw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d271ad85f26a9b31968ccad2b0a771b6cfaf01aba1fb4d165338548ade840805","last_reissued_at":"2026-07-23T01:24:57.326820Z","signature_status":"signed_v1","first_computed_at":"2026-07-23T01:24:57.326820Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2607.20048","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":"2026-07-23T01:24:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8nhjHf1r7Ok7SaDfRukirlnw9pqF/UUqg4zfTM+/bfd6yzcyn9+ZiBNaEF2LRSbWUquhXnJc/z77yBJwXPepDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T05:49:25.474630Z"},"content_sha256":"615368e522169363251d0128e43c5861a4ef43df613f962216fd78388efd549d","schema_version":"1.0","event_id":"sha256:615368e522169363251d0128e43c5861a4ef43df613f962216fd78388efd549d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:2JY23BPSNKNTDFUMZLJLBJ3RW3","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Importance-Aware OBS Pruning for Diffusion Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Ba-Thinh Lam, Hieu Le, Srijan Das","submitted_at":"2026-07-22T11:42:42Z","abstract_excerpt":"We propose importance-aware pruning for diffusion models, a training-free framework that prioritizes preserving parameters critical to semantically salient image regions. To do so, we incorporate spatial importance maps -- derived from conditioning signals or model attention -- into the pruning objective. This produces parameter rankings aligned with perceptual relevance rather than uniform reconstruction error. On MS-COCO dataset, our proposed approach consistently retains subject fidelity and structural correctness at high compression ratios where conventional pruning causes visible degradat"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.20048","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/2607.20048/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":"2026-07-23T01:24:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XGye4v3ETvGB6LKOpL9rmAvYX2xYo8Bii/tKWWvbfAD+wYnJ+H0Pl4KCmxlatZCiiMTnqL5j7xl6RpcCpekqDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T05:49:25.475174Z"},"content_sha256":"5ea80dd4c1305d310a9c41ca743e8f095890ddebf6146095efeba21e7d7ca02a","schema_version":"1.0","event_id":"sha256:5ea80dd4c1305d310a9c41ca743e8f095890ddebf6146095efeba21e7d7ca02a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2JY23BPSNKNTDFUMZLJLBJ3RW3/bundle.json","state_url":"https://pith.science/pith/2JY23BPSNKNTDFUMZLJLBJ3RW3/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2JY23BPSNKNTDFUMZLJLBJ3RW3/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":"2026-08-03T05:49:25Z","links":{"resolver":"https://pith.science/pith/2JY23BPSNKNTDFUMZLJLBJ3RW3","bundle":"https://pith.science/pith/2JY23BPSNKNTDFUMZLJLBJ3RW3/bundle.json","state":"https://pith.science/pith/2JY23BPSNKNTDFUMZLJLBJ3RW3/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2JY23BPSNKNTDFUMZLJLBJ3RW3/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:2JY23BPSNKNTDFUMZLJLBJ3RW3","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":"32bcb70cb4f72c077f17976ce5747805fa4383490f5a9c94d3b0365e229b71b6","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-22T11:42:42Z","title_canon_sha256":"240b897e90d8c309b737f7947d0341d575c4d5a0f17d0bea9a62df0b9fd7b9e7"},"schema_version":"1.0","source":{"id":"2607.20048","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.20048","created_at":"2026-07-23T01:24:57Z"},{"alias_kind":"arxiv_version","alias_value":"2607.20048v1","created_at":"2026-07-23T01:24:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.20048","created_at":"2026-07-23T01:24:57Z"},{"alias_kind":"pith_short_12","alias_value":"2JY23BPSNKNT","created_at":"2026-07-23T01:24:57Z"},{"alias_kind":"pith_short_16","alias_value":"2JY23BPSNKNTDFUM","created_at":"2026-07-23T01:24:57Z"},{"alias_kind":"pith_short_8","alias_value":"2JY23BPS","created_at":"2026-07-23T01:24:57Z"}],"graph_snapshots":[{"event_id":"sha256:5ea80dd4c1305d310a9c41ca743e8f095890ddebf6146095efeba21e7d7ca02a","target":"graph","created_at":"2026-07-23T01:24:57Z","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/2607.20048/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We propose importance-aware pruning for diffusion models, a training-free framework that prioritizes preserving parameters critical to semantically salient image regions. To do so, we incorporate spatial importance maps -- derived from conditioning signals or model attention -- into the pruning objective. This produces parameter rankings aligned with perceptual relevance rather than uniform reconstruction error. On MS-COCO dataset, our proposed approach consistently retains subject fidelity and structural correctness at high compression ratios where conventional pruning causes visible degradat","authors_text":"Ba-Thinh Lam, Hieu Le, Srijan Das","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-22T11:42:42Z","title":"Importance-Aware OBS Pruning for Diffusion Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.20048","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":"sha256:615368e522169363251d0128e43c5861a4ef43df613f962216fd78388efd549d","target":"record","created_at":"2026-07-23T01:24:57Z","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":"32bcb70cb4f72c077f17976ce5747805fa4383490f5a9c94d3b0365e229b71b6","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-22T11:42:42Z","title_canon_sha256":"240b897e90d8c309b737f7947d0341d575c4d5a0f17d0bea9a62df0b9fd7b9e7"},"schema_version":"1.0","source":{"id":"2607.20048","kind":"arxiv","version":1}},"canonical_sha256":"d271ad85f26a9b31968ccad2b0a771b6cfaf01aba1fb4d165338548ade840805","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d271ad85f26a9b31968ccad2b0a771b6cfaf01aba1fb4d165338548ade840805","first_computed_at":"2026-07-23T01:24:57.326820Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-23T01:24:57.326820Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"dKX1peUuX2So7NnMP6OS0Km5ey0TUx/1w1Wg1VpInbgsb7TfgInvSph7dg9MCAzjTE8ZNcgeP95a5yOfWO90Bw==","signature_status":"signed_v1","signed_at":"2026-07-23T01:24:57.327744Z","signed_message":"canonical_sha256_bytes"},"source_id":"2607.20048","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:615368e522169363251d0128e43c5861a4ef43df613f962216fd78388efd549d","sha256:5ea80dd4c1305d310a9c41ca743e8f095890ddebf6146095efeba21e7d7ca02a"],"state_sha256":"000365f476973a3cf3f002d013741460a1e59be16b925f707f85ab4d35af6981"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ObAEar9PBHaIFHM4GuPiWC+xQSN35Q8LsoQxtQ1Uak/+cV4OVmq/35O1vqgg+Y51Hrdz4XZ0f3m6StT/u2UjBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-03T05:49:25.480978Z","bundle_sha256":"aa2adcbaf53ed522b7b2cbe0f217ffe8fef95a587a5e6fdf29a32fac35d01372"}}