{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:KXKL7F2MM6M6LFHI7V43QEYITZ","short_pith_number":"pith:KXKL7F2M","canonical_record":{"source":{"id":"2307.10026","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-07-19T15:11:04Z","cross_cats_sorted":[],"title_canon_sha256":"d75801678e76d331c08ab5d3cf54133c36357ffa43c769d638b92a05d6af923c","abstract_canon_sha256":"5281ee9897c683c48fd5454e3a9369c000a22e946524663e66c60fccf6f4932f"},"schema_version":"1.0"},"canonical_sha256":"55d4bf974c6799e594e8fd79b813089e5a6ac717be78213b8c92973ed1b30f29","source":{"kind":"arxiv","id":"2307.10026","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2307.10026","created_at":"2026-07-05T06:32:49Z"},{"alias_kind":"arxiv_version","alias_value":"2307.10026v1","created_at":"2026-07-05T06:32:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2307.10026","created_at":"2026-07-05T06:32:49Z"},{"alias_kind":"pith_short_12","alias_value":"KXKL7F2MM6M6","created_at":"2026-07-05T06:32:49Z"},{"alias_kind":"pith_short_16","alias_value":"KXKL7F2MM6M6LFHI","created_at":"2026-07-05T06:32:49Z"},{"alias_kind":"pith_short_8","alias_value":"KXKL7F2M","created_at":"2026-07-05T06:32:49Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:KXKL7F2MM6M6LFHI7V43QEYITZ","target":"record","payload":{"canonical_record":{"source":{"id":"2307.10026","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-07-19T15:11:04Z","cross_cats_sorted":[],"title_canon_sha256":"d75801678e76d331c08ab5d3cf54133c36357ffa43c769d638b92a05d6af923c","abstract_canon_sha256":"5281ee9897c683c48fd5454e3a9369c000a22e946524663e66c60fccf6f4932f"},"schema_version":"1.0"},"canonical_sha256":"55d4bf974c6799e594e8fd79b813089e5a6ac717be78213b8c92973ed1b30f29","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:32:49.538284Z","signature_b64":"1VfY95q7ZIs8Vx/j3NpFWqAPxRXmceBBHjNf9VMmNRyOzy6JEsUKFtXIvo5xs5hKxMTROvwMserdqmcotx3JCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"55d4bf974c6799e594e8fd79b813089e5a6ac717be78213b8c92973ed1b30f29","last_reissued_at":"2026-07-05T06:32:49.537768Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:32:49.537768Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2307.10026","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":"2026-07-05T06:32:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LYOlQo20ltLIgL4vK0LOh/oEyk1DB/mnZtxRVL0bye8U8bIsOQKdJ9roKVGizoY+h8pSRx6rDbzEEt4+S8RGDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-19T19:31:46.450651Z"},"content_sha256":"f77c5da50d18e74558d4c0860861dad28e4a2eb37edbe6dedd6cb21fc6b2711e","schema_version":"1.0","event_id":"sha256:f77c5da50d18e74558d4c0860861dad28e4a2eb37edbe6dedd6cb21fc6b2711e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:KXKL7F2MM6M6LFHI7V43QEYITZ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Contextual Reliability: When Different Features Matter in Different Contexts","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Aditi Raghunathan, Amrith Setlur, Anca D. Dragan, Daniel S. Brown, Gaurav Ghosal","submitted_at":"2023-07-19T15:11:04Z","abstract_excerpt":"Deep neural networks often fail catastrophically by relying on spurious correlations. Most prior work assumes a clear dichotomy into spurious and reliable features; however, this is often unrealistic. For example, most of the time we do not want an autonomous car to simply copy the speed of surrounding cars -- we don't want our car to run a red light if a neighboring car does so. However, we cannot simply enforce invariance to next-lane speed, since it could provide valuable information about an unobservable pedestrian at a crosswalk. Thus, universally ignoring features that are sometimes (but"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2307.10026","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/2307.10026/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":"2026-07-05T06:32:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LyPdwyiXsqVJk/4bjBLvz45zDCeOaXkUdbpm/VgIRFWQLGCcheuX4lnNQOqVzZK4OH/4z329gC1GmvUjE4sDBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-19T19:31:46.451018Z"},"content_sha256":"83bfb448d534ddb1ff58922b41b0b1b798a7c02b9cf4dfadb539f5f67b2962c3","schema_version":"1.0","event_id":"sha256:83bfb448d534ddb1ff58922b41b0b1b798a7c02b9cf4dfadb539f5f67b2962c3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/KXKL7F2MM6M6LFHI7V43QEYITZ/bundle.json","state_url":"https://pith.science/pith/KXKL7F2MM6M6LFHI7V43QEYITZ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/KXKL7F2MM6M6LFHI7V43QEYITZ/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":"2026-07-19T19:31:46Z","links":{"resolver":"https://pith.science/pith/KXKL7F2MM6M6LFHI7V43QEYITZ","bundle":"https://pith.science/pith/KXKL7F2MM6M6LFHI7V43QEYITZ/bundle.json","state":"https://pith.science/pith/KXKL7F2MM6M6LFHI7V43QEYITZ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/KXKL7F2MM6M6LFHI7V43QEYITZ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:KXKL7F2MM6M6LFHI7V43QEYITZ","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":"5281ee9897c683c48fd5454e3a9369c000a22e946524663e66c60fccf6f4932f","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-07-19T15:11:04Z","title_canon_sha256":"d75801678e76d331c08ab5d3cf54133c36357ffa43c769d638b92a05d6af923c"},"schema_version":"1.0","source":{"id":"2307.10026","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2307.10026","created_at":"2026-07-05T06:32:49Z"},{"alias_kind":"arxiv_version","alias_value":"2307.10026v1","created_at":"2026-07-05T06:32:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2307.10026","created_at":"2026-07-05T06:32:49Z"},{"alias_kind":"pith_short_12","alias_value":"KXKL7F2MM6M6","created_at":"2026-07-05T06:32:49Z"},{"alias_kind":"pith_short_16","alias_value":"KXKL7F2MM6M6LFHI","created_at":"2026-07-05T06:32:49Z"},{"alias_kind":"pith_short_8","alias_value":"KXKL7F2M","created_at":"2026-07-05T06:32:49Z"}],"graph_snapshots":[{"event_id":"sha256:83bfb448d534ddb1ff58922b41b0b1b798a7c02b9cf4dfadb539f5f67b2962c3","target":"graph","created_at":"2026-07-05T06:32:49Z","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/2307.10026/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deep neural networks often fail catastrophically by relying on spurious correlations. Most prior work assumes a clear dichotomy into spurious and reliable features; however, this is often unrealistic. For example, most of the time we do not want an autonomous car to simply copy the speed of surrounding cars -- we don't want our car to run a red light if a neighboring car does so. However, we cannot simply enforce invariance to next-lane speed, since it could provide valuable information about an unobservable pedestrian at a crosswalk. Thus, universally ignoring features that are sometimes (but","authors_text":"Aditi Raghunathan, Amrith Setlur, Anca D. Dragan, Daniel S. Brown, Gaurav Ghosal","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-07-19T15:11:04Z","title":"Contextual Reliability: When Different Features Matter in Different Contexts"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2307.10026","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:f77c5da50d18e74558d4c0860861dad28e4a2eb37edbe6dedd6cb21fc6b2711e","target":"record","created_at":"2026-07-05T06:32:49Z","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":"5281ee9897c683c48fd5454e3a9369c000a22e946524663e66c60fccf6f4932f","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-07-19T15:11:04Z","title_canon_sha256":"d75801678e76d331c08ab5d3cf54133c36357ffa43c769d638b92a05d6af923c"},"schema_version":"1.0","source":{"id":"2307.10026","kind":"arxiv","version":1}},"canonical_sha256":"55d4bf974c6799e594e8fd79b813089e5a6ac717be78213b8c92973ed1b30f29","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"55d4bf974c6799e594e8fd79b813089e5a6ac717be78213b8c92973ed1b30f29","first_computed_at":"2026-07-05T06:32:49.537768Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:32:49.537768Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"1VfY95q7ZIs8Vx/j3NpFWqAPxRXmceBBHjNf9VMmNRyOzy6JEsUKFtXIvo5xs5hKxMTROvwMserdqmcotx3JCA==","signature_status":"signed_v1","signed_at":"2026-07-05T06:32:49.538284Z","signed_message":"canonical_sha256_bytes"},"source_id":"2307.10026","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f77c5da50d18e74558d4c0860861dad28e4a2eb37edbe6dedd6cb21fc6b2711e","sha256:83bfb448d534ddb1ff58922b41b0b1b798a7c02b9cf4dfadb539f5f67b2962c3"],"state_sha256":"86a2eb7d46e64d1d87fe0b9495f13f53d2d94b1a407b703c591fc2037b4d60c4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SFtZSxo2f6YGhNFP8/Lm51YDxX1kSTn48FwsR4s1XkQp/JG7K5YOawHFClo7j0eJWuNU2fMaLVKW/PPkQy4JBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-19T19:31:46.453217Z","bundle_sha256":"3dc2229af9d84efa9ca930ebf9a93287a5b93d9bac241cbd56e8bd38b96614bd"}}