{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:7WNED5GAANBELILRZO7LLWFAVA","short_pith_number":"pith:7WNED5GA","canonical_record":{"source":{"id":"2502.02710","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2025-02-04T20:42:47Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"e901823f2dbdf80c3405d26fb0c1a03783bd6ebcb57f8b20038ad27b09b93c32","abstract_canon_sha256":"2a9ff0113601c3d8322cbb34b718fcfff12c0565c9516f83259b29c47e798c6d"},"schema_version":"1.0"},"canonical_sha256":"fd9a41f4c0034245a171cbbeb5d8a0a817d28737df5de896584f32c1a54efa9e","source":{"kind":"arxiv","id":"2502.02710","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.02710","created_at":"2026-07-05T10:09:53Z"},{"alias_kind":"arxiv_version","alias_value":"2502.02710v1","created_at":"2026-07-05T10:09:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.02710","created_at":"2026-07-05T10:09:53Z"},{"alias_kind":"pith_short_12","alias_value":"7WNED5GAANBE","created_at":"2026-07-05T10:09:53Z"},{"alias_kind":"pith_short_16","alias_value":"7WNED5GAANBELILR","created_at":"2026-07-05T10:09:53Z"},{"alias_kind":"pith_short_8","alias_value":"7WNED5GA","created_at":"2026-07-05T10:09:53Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:7WNED5GAANBELILRZO7LLWFAVA","target":"record","payload":{"canonical_record":{"source":{"id":"2502.02710","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2025-02-04T20:42:47Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"e901823f2dbdf80c3405d26fb0c1a03783bd6ebcb57f8b20038ad27b09b93c32","abstract_canon_sha256":"2a9ff0113601c3d8322cbb34b718fcfff12c0565c9516f83259b29c47e798c6d"},"schema_version":"1.0"},"canonical_sha256":"fd9a41f4c0034245a171cbbeb5d8a0a817d28737df5de896584f32c1a54efa9e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:09:53.813080Z","signature_b64":"VGMOn91P86q0WAHhqCuPsFxFFK/8D+POwZfSx6uQCW6EId0O0LkNC4GJjEZIVtkk9i9O5wf+RJhf9PRVLvi2Dg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"fd9a41f4c0034245a171cbbeb5d8a0a817d28737df5de896584f32c1a54efa9e","last_reissued_at":"2026-07-05T10:09:53.812706Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:09:53.812706Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2502.02710","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":"2026-07-05T10:09:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"igR3J2jUY7eLN6yLbPcMWp4GN57zjwKdJxoyS+Hy0QDQHzPdAIh4RXhmfudk0GiibMBMm4ipqiaeL+vIgv9LAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T10:29:31.182955Z"},"content_sha256":"41606f0afe6916275087ac254a86b6b594d3a96309dfa9b161373cf02b1da02c","schema_version":"1.0","event_id":"sha256:41606f0afe6916275087ac254a86b6b594d3a96309dfa9b161373cf02b1da02c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:7WNED5GAANBELILRZO7LLWFAVA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Achievable distributional robustness when the robust risk is only partially identified","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"stat.ML","authors_text":"Fanny Yang, Julia Kostin, Nicola Gnecco","submitted_at":"2025-02-04T20:42:47Z","abstract_excerpt":"In safety-critical applications, machine learning models should generalize well under worst-case distribution shifts, that is, have a small robust risk. Invariance-based algorithms can provably take advantage of structural assumptions on the shifts when the training distributions are heterogeneous enough to identify the robust risk. However, in practice, such identifiability conditions are rarely satisfied -- a scenario so far underexplored in the theoretical literature. In this paper, we aim to fill the gap and propose to study the more general setting when the robust risk is only partially i"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.02710","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/2502.02710/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":"2026-07-05T10:09:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"O5LfcGU+AqbhJPEM1hk2B1EeO9WFFy97l6m7862s/H4JNc6aI0r4lcdYAJMhbMeqdS9hPG2H4bbPs3ct9V4dBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T10:29:31.183486Z"},"content_sha256":"97364191c8cb294d4c695f56092b8a7254a925572d4eb56c93e6de62d7fee1ed","schema_version":"1.0","event_id":"sha256:97364191c8cb294d4c695f56092b8a7254a925572d4eb56c93e6de62d7fee1ed"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/7WNED5GAANBELILRZO7LLWFAVA/bundle.json","state_url":"https://pith.science/pith/7WNED5GAANBELILRZO7LLWFAVA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/7WNED5GAANBELILRZO7LLWFAVA/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":"2026-08-10T10:29:31Z","links":{"resolver":"https://pith.science/pith/7WNED5GAANBELILRZO7LLWFAVA","bundle":"https://pith.science/pith/7WNED5GAANBELILRZO7LLWFAVA/bundle.json","state":"https://pith.science/pith/7WNED5GAANBELILRZO7LLWFAVA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/7WNED5GAANBELILRZO7LLWFAVA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:7WNED5GAANBELILRZO7LLWFAVA","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":"2a9ff0113601c3d8322cbb34b718fcfff12c0565c9516f83259b29c47e798c6d","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2025-02-04T20:42:47Z","title_canon_sha256":"e901823f2dbdf80c3405d26fb0c1a03783bd6ebcb57f8b20038ad27b09b93c32"},"schema_version":"1.0","source":{"id":"2502.02710","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.02710","created_at":"2026-07-05T10:09:53Z"},{"alias_kind":"arxiv_version","alias_value":"2502.02710v1","created_at":"2026-07-05T10:09:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.02710","created_at":"2026-07-05T10:09:53Z"},{"alias_kind":"pith_short_12","alias_value":"7WNED5GAANBE","created_at":"2026-07-05T10:09:53Z"},{"alias_kind":"pith_short_16","alias_value":"7WNED5GAANBELILR","created_at":"2026-07-05T10:09:53Z"},{"alias_kind":"pith_short_8","alias_value":"7WNED5GA","created_at":"2026-07-05T10:09:53Z"}],"graph_snapshots":[{"event_id":"sha256:97364191c8cb294d4c695f56092b8a7254a925572d4eb56c93e6de62d7fee1ed","target":"graph","created_at":"2026-07-05T10:09:53Z","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/2502.02710/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In safety-critical applications, machine learning models should generalize well under worst-case distribution shifts, that is, have a small robust risk. Invariance-based algorithms can provably take advantage of structural assumptions on the shifts when the training distributions are heterogeneous enough to identify the robust risk. However, in practice, such identifiability conditions are rarely satisfied -- a scenario so far underexplored in the theoretical literature. In this paper, we aim to fill the gap and propose to study the more general setting when the robust risk is only partially i","authors_text":"Fanny Yang, Julia Kostin, Nicola Gnecco","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2025-02-04T20:42:47Z","title":"Achievable distributional robustness when the robust risk is only partially identified"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.02710","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":"sha256:41606f0afe6916275087ac254a86b6b594d3a96309dfa9b161373cf02b1da02c","target":"record","created_at":"2026-07-05T10:09:53Z","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":"2a9ff0113601c3d8322cbb34b718fcfff12c0565c9516f83259b29c47e798c6d","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2025-02-04T20:42:47Z","title_canon_sha256":"e901823f2dbdf80c3405d26fb0c1a03783bd6ebcb57f8b20038ad27b09b93c32"},"schema_version":"1.0","source":{"id":"2502.02710","kind":"arxiv","version":1}},"canonical_sha256":"fd9a41f4c0034245a171cbbeb5d8a0a817d28737df5de896584f32c1a54efa9e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"fd9a41f4c0034245a171cbbeb5d8a0a817d28737df5de896584f32c1a54efa9e","first_computed_at":"2026-07-05T10:09:53.812706Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:09:53.812706Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"VGMOn91P86q0WAHhqCuPsFxFFK/8D+POwZfSx6uQCW6EId0O0LkNC4GJjEZIVtkk9i9O5wf+RJhf9PRVLvi2Dg==","signature_status":"signed_v1","signed_at":"2026-07-05T10:09:53.813080Z","signed_message":"canonical_sha256_bytes"},"source_id":"2502.02710","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:41606f0afe6916275087ac254a86b6b594d3a96309dfa9b161373cf02b1da02c","sha256:97364191c8cb294d4c695f56092b8a7254a925572d4eb56c93e6de62d7fee1ed"],"state_sha256":"174322a33ca5a191f0f1a5d247dcc92c3dbdb4c1953cb4b1ac96e0d327848881"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cmoMB08yuGixLMNu9Pmnlcg1YbeZe/k/fFAh2RMBKNVmBLaX8QM/J2LQgkFAOL9HmrcdKFE1NMLEzAOSJVwQCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T10:29:31.188978Z","bundle_sha256":"43ef3e52a54479745180da677b04847514bb4f813d3932ffb9ded5d15095006e"}}