{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:FBNAKSACMPMH7GIBWZMQRKATL3","short_pith_number":"pith:FBNAKSAC","canonical_record":{"source":{"id":"2607.21562","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-23T17:46:26Z","cross_cats_sorted":["cs.GR"],"title_canon_sha256":"99bd908cfb1602dea9cf6c1b086d6988cfa62be2112e735d4a9f22c8e298947d","abstract_canon_sha256":"f1e50d5a02b938de56065fdcf2875fdf3d2a445ff7e8c8d41e8fec023b1b2477"},"schema_version":"1.0"},"canonical_sha256":"285a05480263d87f9901b65908a8135eee3ae2e42cfac4836ef31155143b9bc1","source":{"kind":"arxiv","id":"2607.21562","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.21562","created_at":"2026-07-24T01:24:39Z"},{"alias_kind":"arxiv_version","alias_value":"2607.21562v1","created_at":"2026-07-24T01:24:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.21562","created_at":"2026-07-24T01:24:39Z"},{"alias_kind":"pith_short_12","alias_value":"FBNAKSACMPMH","created_at":"2026-07-24T01:24:39Z"},{"alias_kind":"pith_short_16","alias_value":"FBNAKSACMPMH7GIB","created_at":"2026-07-24T01:24:39Z"},{"alias_kind":"pith_short_8","alias_value":"FBNAKSAC","created_at":"2026-07-24T01:24:39Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:FBNAKSACMPMH7GIBWZMQRKATL3","target":"record","payload":{"canonical_record":{"source":{"id":"2607.21562","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-23T17:46:26Z","cross_cats_sorted":["cs.GR"],"title_canon_sha256":"99bd908cfb1602dea9cf6c1b086d6988cfa62be2112e735d4a9f22c8e298947d","abstract_canon_sha256":"f1e50d5a02b938de56065fdcf2875fdf3d2a445ff7e8c8d41e8fec023b1b2477"},"schema_version":"1.0"},"canonical_sha256":"285a05480263d87f9901b65908a8135eee3ae2e42cfac4836ef31155143b9bc1","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-24T01:24:39.792702Z","signature_b64":"zNAfL3XZAz4wQCPtOh/mnBrEC+eE49T94SUw1l/lNBvUoGSbqUC313Oq619vP2lqfg0IrGLDoewJmV+ri0PyDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"285a05480263d87f9901b65908a8135eee3ae2e42cfac4836ef31155143b9bc1","last_reissued_at":"2026-07-24T01:24:39.791837Z","signature_status":"signed_v1","first_computed_at":"2026-07-24T01:24:39.791837Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2607.21562","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":"2026-07-24T01:24:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pKJU6fVGiGFRT8urn+roPQ2D+vzLKxWfY6PumASC0oP8O2s2Tgh/fc36/HBDU1RzDarveYGLZKmozDpw4ZPqCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T01:19:11.088270Z"},"content_sha256":"479562bcee5a5c93c2fa77ef9dc5af4ce8bf0d0afd0a5f5a01845840936dcb0b","schema_version":"1.0","event_id":"sha256:479562bcee5a5c93c2fa77ef9dc5af4ce8bf0d0afd0a5f5a01845840936dcb0b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:FBNAKSACMPMH7GIBWZMQRKATL3","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Scene Parameter Saliency via Differentiable Light Transport","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.GR"],"primary_cat":"cs.CV","authors_text":"Eugene Fiume, Linas Beresna","submitted_at":"2026-07-23T17:46:26Z","abstract_excerpt":"Gradient-based saliency methods reveal which input features most influence a neural network's output, and are a standard tool for model interpretability. We observe that differentiable renderers, which are conventionally used for parameter optimisation, produce an analogous form of saliency: given any scalar metric evaluated on a rendered image, a single reverse-mode differentiation pass yields per-parameter gradients that identify which scene elements most influence the metric. We call these gradient fields metric saliency maps. Unlike neural saliency, which propagates attribution through lea"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.21562","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/2607.21562/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":"2026-07-24T01:24:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VgIkOyDqOqdfDcE7XOUKvTUAjY9guggYaw9wYLKf32X0N08jfCmTs7B9Bwg1l29h/uf2QBcIPkKTpzpshPcCBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T01:19:11.088761Z"},"content_sha256":"b7ce2819bb0e2ac3870619a973b121d294c59e0f27f642143762340910394424","schema_version":"1.0","event_id":"sha256:b7ce2819bb0e2ac3870619a973b121d294c59e0f27f642143762340910394424"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/FBNAKSACMPMH7GIBWZMQRKATL3/bundle.json","state_url":"https://pith.science/pith/FBNAKSACMPMH7GIBWZMQRKATL3/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/FBNAKSACMPMH7GIBWZMQRKATL3/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":"2026-08-05T01:19:11Z","links":{"resolver":"https://pith.science/pith/FBNAKSACMPMH7GIBWZMQRKATL3","bundle":"https://pith.science/pith/FBNAKSACMPMH7GIBWZMQRKATL3/bundle.json","state":"https://pith.science/pith/FBNAKSACMPMH7GIBWZMQRKATL3/state.json","well_known_bundle":"https://pith.science/.well-known/pith/FBNAKSACMPMH7GIBWZMQRKATL3/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:FBNAKSACMPMH7GIBWZMQRKATL3","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":"f1e50d5a02b938de56065fdcf2875fdf3d2a445ff7e8c8d41e8fec023b1b2477","cross_cats_sorted":["cs.GR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-23T17:46:26Z","title_canon_sha256":"99bd908cfb1602dea9cf6c1b086d6988cfa62be2112e735d4a9f22c8e298947d"},"schema_version":"1.0","source":{"id":"2607.21562","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.21562","created_at":"2026-07-24T01:24:39Z"},{"alias_kind":"arxiv_version","alias_value":"2607.21562v1","created_at":"2026-07-24T01:24:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.21562","created_at":"2026-07-24T01:24:39Z"},{"alias_kind":"pith_short_12","alias_value":"FBNAKSACMPMH","created_at":"2026-07-24T01:24:39Z"},{"alias_kind":"pith_short_16","alias_value":"FBNAKSACMPMH7GIB","created_at":"2026-07-24T01:24:39Z"},{"alias_kind":"pith_short_8","alias_value":"FBNAKSAC","created_at":"2026-07-24T01:24:39Z"}],"graph_snapshots":[{"event_id":"sha256:b7ce2819bb0e2ac3870619a973b121d294c59e0f27f642143762340910394424","target":"graph","created_at":"2026-07-24T01:24:39Z","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/2607.21562/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Gradient-based saliency methods reveal which input features most influence a neural network's output, and are a standard tool for model interpretability. We observe that differentiable renderers, which are conventionally used for parameter optimisation, produce an analogous form of saliency: given any scalar metric evaluated on a rendered image, a single reverse-mode differentiation pass yields per-parameter gradients that identify which scene elements most influence the metric. We call these gradient fields metric saliency maps. Unlike neural saliency, which propagates attribution through lea","authors_text":"Eugene Fiume, Linas Beresna","cross_cats":["cs.GR"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-23T17:46:26Z","title":"Scene Parameter Saliency via Differentiable Light Transport"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.21562","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":"sha256:479562bcee5a5c93c2fa77ef9dc5af4ce8bf0d0afd0a5f5a01845840936dcb0b","target":"record","created_at":"2026-07-24T01:24:39Z","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":"f1e50d5a02b938de56065fdcf2875fdf3d2a445ff7e8c8d41e8fec023b1b2477","cross_cats_sorted":["cs.GR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-23T17:46:26Z","title_canon_sha256":"99bd908cfb1602dea9cf6c1b086d6988cfa62be2112e735d4a9f22c8e298947d"},"schema_version":"1.0","source":{"id":"2607.21562","kind":"arxiv","version":1}},"canonical_sha256":"285a05480263d87f9901b65908a8135eee3ae2e42cfac4836ef31155143b9bc1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"285a05480263d87f9901b65908a8135eee3ae2e42cfac4836ef31155143b9bc1","first_computed_at":"2026-07-24T01:24:39.791837Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-24T01:24:39.791837Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"zNAfL3XZAz4wQCPtOh/mnBrEC+eE49T94SUw1l/lNBvUoGSbqUC313Oq619vP2lqfg0IrGLDoewJmV+ri0PyDg==","signature_status":"signed_v1","signed_at":"2026-07-24T01:24:39.792702Z","signed_message":"canonical_sha256_bytes"},"source_id":"2607.21562","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:479562bcee5a5c93c2fa77ef9dc5af4ce8bf0d0afd0a5f5a01845840936dcb0b","sha256:b7ce2819bb0e2ac3870619a973b121d294c59e0f27f642143762340910394424"],"state_sha256":"3d22a69c5071e6c326a364d695a459f7e5cc4f03e4d53a4137621c880f1c1a64"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fnfMCuEXG7/8CwRvqiM8gx3DQnYS+jIqFTu65dYBpa510Kjg3IEh8X7BzsJmwxMrAtYnBRmBGtwAFMHwnHFrDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T01:19:11.093047Z","bundle_sha256":"1c0aab3068d2c2dc5529d6cfaa506026cb989625311a8dce7820234fdc17b8af"}}