{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:N2X7X737A25XFJWU2SDEBR6OES","short_pith_number":"pith:N2X7X737","canonical_record":{"source":{"id":"2412.00884","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-01T16:44:55Z","cross_cats_sorted":[],"title_canon_sha256":"f9aff6be6b8ce29d7f5e717c01d75730d46243e1e77614c5ceeed6a229733e8d","abstract_canon_sha256":"57a5252a26507231aeba90dd51dd93f3cdfa581d4f35ba2d703aeeb7539b0796"},"schema_version":"1.0"},"canonical_sha256":"6eaffbff7f06bb72a6d4d48640c7ce24a3bc65a1192f5f11fdc5deddb2c21ed3","source":{"kind":"arxiv","id":"2412.00884","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.00884","created_at":"2026-07-05T09:42:49Z"},{"alias_kind":"arxiv_version","alias_value":"2412.00884v1","created_at":"2026-07-05T09:42:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.00884","created_at":"2026-07-05T09:42:49Z"},{"alias_kind":"pith_short_12","alias_value":"N2X7X737A25X","created_at":"2026-07-05T09:42:49Z"},{"alias_kind":"pith_short_16","alias_value":"N2X7X737A25XFJWU","created_at":"2026-07-05T09:42:49Z"},{"alias_kind":"pith_short_8","alias_value":"N2X7X737","created_at":"2026-07-05T09:42:49Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:N2X7X737A25XFJWU2SDEBR6OES","target":"record","payload":{"canonical_record":{"source":{"id":"2412.00884","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-01T16:44:55Z","cross_cats_sorted":[],"title_canon_sha256":"f9aff6be6b8ce29d7f5e717c01d75730d46243e1e77614c5ceeed6a229733e8d","abstract_canon_sha256":"57a5252a26507231aeba90dd51dd93f3cdfa581d4f35ba2d703aeeb7539b0796"},"schema_version":"1.0"},"canonical_sha256":"6eaffbff7f06bb72a6d4d48640c7ce24a3bc65a1192f5f11fdc5deddb2c21ed3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:42:49.893865Z","signature_b64":"lQS/Tcbbt7SRBZUWhpcpVEEEm1UUmuaVGFNu/fb2ngg4D5vA9nL8mkwosv6HPNqDoy64UhWrqE60U4DqNXtABQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6eaffbff7f06bb72a6d4d48640c7ce24a3bc65a1192f5f11fdc5deddb2c21ed3","last_reissued_at":"2026-07-05T09:42:49.893402Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:42:49.893402Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2412.00884","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":"2026-07-05T09:42:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wsYcMxn1LNffwqFVPxKxOgW1A9jhiCY8aXBNboKdUz5EBM6DDAz+xGWcmJ7HUOIxBVd8whnFr22bOEWEY2sxDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T12:22:54.669495Z"},"content_sha256":"efd52536fbe3c5cb10a097d4a1d2d12a461cdfbe66a4a26934378a45c32123ab","schema_version":"1.0","event_id":"sha256:efd52536fbe3c5cb10a097d4a1d2d12a461cdfbe66a4a26934378a45c32123ab"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:N2X7X737A25XFJWU2SDEBR6OES","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Leveraging Intermediate Neural Collapse with Simplex ETFs for Efficient Deep Neural Networks","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Emily Liu","submitted_at":"2024-12-01T16:44:55Z","abstract_excerpt":"Neural collapse is a phenomenon observed during the terminal phase of neural network training, characterized by the convergence of network activations, class means, and linear classifier weights to a simplex equiangular tight frame (ETF), a configuration of vectors that maximizes mutual distance within a subspace. This phenomenon has been linked to improved interpretability, robustness, and generalization in neural networks. However, its potential to guide neural network training and regularization remains underexplored. Previous research has demonstrated that constraining the final layer of a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.00884","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/2412.00884/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":"2026-07-05T09:42:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/EH6r0ba/kBaDucxHKe0WhukAJdUsYL+YajUKNFs1+Ocwu0aY1zFylZykfKQ89X02KEwfkIYAjTVIvJTasUbCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T12:22:54.670226Z"},"content_sha256":"dc89216f3ed61843a36ee9c3548c82d925cbfafb51131c9f5612a763fec672a4","schema_version":"1.0","event_id":"sha256:dc89216f3ed61843a36ee9c3548c82d925cbfafb51131c9f5612a763fec672a4"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/N2X7X737A25XFJWU2SDEBR6OES/bundle.json","state_url":"https://pith.science/pith/N2X7X737A25XFJWU2SDEBR6OES/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/N2X7X737A25XFJWU2SDEBR6OES/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":"2026-08-19T12:22:54Z","links":{"resolver":"https://pith.science/pith/N2X7X737A25XFJWU2SDEBR6OES","bundle":"https://pith.science/pith/N2X7X737A25XFJWU2SDEBR6OES/bundle.json","state":"https://pith.science/pith/N2X7X737A25XFJWU2SDEBR6OES/state.json","well_known_bundle":"https://pith.science/.well-known/pith/N2X7X737A25XFJWU2SDEBR6OES/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:N2X7X737A25XFJWU2SDEBR6OES","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":"57a5252a26507231aeba90dd51dd93f3cdfa581d4f35ba2d703aeeb7539b0796","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-01T16:44:55Z","title_canon_sha256":"f9aff6be6b8ce29d7f5e717c01d75730d46243e1e77614c5ceeed6a229733e8d"},"schema_version":"1.0","source":{"id":"2412.00884","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.00884","created_at":"2026-07-05T09:42:49Z"},{"alias_kind":"arxiv_version","alias_value":"2412.00884v1","created_at":"2026-07-05T09:42:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.00884","created_at":"2026-07-05T09:42:49Z"},{"alias_kind":"pith_short_12","alias_value":"N2X7X737A25X","created_at":"2026-07-05T09:42:49Z"},{"alias_kind":"pith_short_16","alias_value":"N2X7X737A25XFJWU","created_at":"2026-07-05T09:42:49Z"},{"alias_kind":"pith_short_8","alias_value":"N2X7X737","created_at":"2026-07-05T09:42:49Z"}],"graph_snapshots":[{"event_id":"sha256:dc89216f3ed61843a36ee9c3548c82d925cbfafb51131c9f5612a763fec672a4","target":"graph","created_at":"2026-07-05T09:42:49Z","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/2412.00884/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Neural collapse is a phenomenon observed during the terminal phase of neural network training, characterized by the convergence of network activations, class means, and linear classifier weights to a simplex equiangular tight frame (ETF), a configuration of vectors that maximizes mutual distance within a subspace. This phenomenon has been linked to improved interpretability, robustness, and generalization in neural networks. However, its potential to guide neural network training and regularization remains underexplored. Previous research has demonstrated that constraining the final layer of a","authors_text":"Emily Liu","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-01T16:44:55Z","title":"Leveraging Intermediate Neural Collapse with Simplex ETFs for Efficient Deep Neural Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.00884","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:efd52536fbe3c5cb10a097d4a1d2d12a461cdfbe66a4a26934378a45c32123ab","target":"record","created_at":"2026-07-05T09:42:49Z","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":"57a5252a26507231aeba90dd51dd93f3cdfa581d4f35ba2d703aeeb7539b0796","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-01T16:44:55Z","title_canon_sha256":"f9aff6be6b8ce29d7f5e717c01d75730d46243e1e77614c5ceeed6a229733e8d"},"schema_version":"1.0","source":{"id":"2412.00884","kind":"arxiv","version":1}},"canonical_sha256":"6eaffbff7f06bb72a6d4d48640c7ce24a3bc65a1192f5f11fdc5deddb2c21ed3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6eaffbff7f06bb72a6d4d48640c7ce24a3bc65a1192f5f11fdc5deddb2c21ed3","first_computed_at":"2026-07-05T09:42:49.893402Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:42:49.893402Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"lQS/Tcbbt7SRBZUWhpcpVEEEm1UUmuaVGFNu/fb2ngg4D5vA9nL8mkwosv6HPNqDoy64UhWrqE60U4DqNXtABQ==","signature_status":"signed_v1","signed_at":"2026-07-05T09:42:49.893865Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.00884","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:efd52536fbe3c5cb10a097d4a1d2d12a461cdfbe66a4a26934378a45c32123ab","sha256:dc89216f3ed61843a36ee9c3548c82d925cbfafb51131c9f5612a763fec672a4"],"state_sha256":"5740c4b8738043ccb0d7a132147009b1a56fad3fe87bf8a48fa20349e150c875"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZeW1Bu/YbhP8CzmxHVYrWHuqL7QrgfKVFBxPXZgXmx06X31PNs6iVJMfEmyiDvprQJ1KpNTKdDqNQjXaxNbqCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-19T12:22:54.675542Z","bundle_sha256":"6b9e9add43d0ed02f658a1eeb7fcf5247db560c513da5591cbe4b005fd0c1d15"}}