{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:76MGTBAHHO6V4USKABMVICOIKZ","short_pith_number":"pith:76MGTBAH","canonical_record":{"source":{"id":"2501.05502","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-09T18:44:10Z","cross_cats_sorted":[],"title_canon_sha256":"560419c834a5dad2bd2a85dcd6caf82cf5e5301daaab8bdebfeb6c3e865c151f","abstract_canon_sha256":"3c53fc1031d41b3afe5d4420de2fabaa83799b7fcdaa5c5f707e04450d5c1369"},"schema_version":"1.0"},"canonical_sha256":"ff986984073bbd5e524a00595409c8567b63933000be41bd37540f2baad09ede","source":{"kind":"arxiv","id":"2501.05502","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.05502","created_at":"2026-07-05T09:59:24Z"},{"alias_kind":"arxiv_version","alias_value":"2501.05502v1","created_at":"2026-07-05T09:59:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.05502","created_at":"2026-07-05T09:59:24Z"},{"alias_kind":"pith_short_12","alias_value":"76MGTBAHHO6V","created_at":"2026-07-05T09:59:24Z"},{"alias_kind":"pith_short_16","alias_value":"76MGTBAHHO6V4USK","created_at":"2026-07-05T09:59:24Z"},{"alias_kind":"pith_short_8","alias_value":"76MGTBAH","created_at":"2026-07-05T09:59:24Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:76MGTBAHHO6V4USKABMVICOIKZ","target":"record","payload":{"canonical_record":{"source":{"id":"2501.05502","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-09T18:44:10Z","cross_cats_sorted":[],"title_canon_sha256":"560419c834a5dad2bd2a85dcd6caf82cf5e5301daaab8bdebfeb6c3e865c151f","abstract_canon_sha256":"3c53fc1031d41b3afe5d4420de2fabaa83799b7fcdaa5c5f707e04450d5c1369"},"schema_version":"1.0"},"canonical_sha256":"ff986984073bbd5e524a00595409c8567b63933000be41bd37540f2baad09ede","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:59:24.436403Z","signature_b64":"JkMcmR46ONG0v4c+P2sz+hnGX4SvbL64xRyvIq7RAk1krfKdharB3uxXJtxwwZ/7d7nlMUzrNwj+wAQS3vrIBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ff986984073bbd5e524a00595409c8567b63933000be41bd37540f2baad09ede","last_reissued_at":"2026-07-05T09:59:24.435939Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:59:24.435939Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2501.05502","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":"2026-07-05T09:59:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pEy79WooupmugoIgEpK0iSfXRZKJX3in3JXlZjaCr8fws6UzMyU6A1dQgbm2Bo2DILfaDEU7+YgTvNHFKh5pAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-09T05:00:36.946605Z"},"content_sha256":"ca76d616c0f3706968983d728621d437a15cf7e7ddc25fbd02bf9c39409544b9","schema_version":"1.0","event_id":"sha256:ca76d616c0f3706968983d728621d437a15cf7e7ddc25fbd02bf9c39409544b9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:76MGTBAHHO6V4USKABMVICOIKZ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Shrink the longest: improving latent space isotropy with symplicial geometry","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Eduard Klyshinsky, Olesya Karpik, Sergei Kudriashov","submitted_at":"2025-01-09T18:44:10Z","abstract_excerpt":"Although transformer-based models have been dominating the field of deep learning, various studies of their embedding space have shown that they suffer from \"representation degeneration problem\": embeddings tend to be distributed in a narrow cone, making the latent space highly anisotropic. Increasing the isotropy has shown to improve performance in downstream tasks both in static and contextual language models. However, most of approaches either add inference overhead or require substantial amount of data for model reparametrization. We propose a novel regularization technique based on simpli"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.05502","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/2501.05502/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":"2026-07-05T09:59:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"R1wEiQqUEkbuwg7fWBBTiY5D9FsDoxxaISlFdxzON1oKA6IZ6uPQc7PgApc/flbOKMD7SZGioJdZ2cZKa7sSCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-09T05:00:36.946976Z"},"content_sha256":"bf8fa406f6e9212aa17ffcb99b64c56bf50357dcd11799db4f084501f46023dd","schema_version":"1.0","event_id":"sha256:bf8fa406f6e9212aa17ffcb99b64c56bf50357dcd11799db4f084501f46023dd"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/76MGTBAHHO6V4USKABMVICOIKZ/bundle.json","state_url":"https://pith.science/pith/76MGTBAHHO6V4USKABMVICOIKZ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/76MGTBAHHO6V4USKABMVICOIKZ/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":"2026-07-09T05:00:36Z","links":{"resolver":"https://pith.science/pith/76MGTBAHHO6V4USKABMVICOIKZ","bundle":"https://pith.science/pith/76MGTBAHHO6V4USKABMVICOIKZ/bundle.json","state":"https://pith.science/pith/76MGTBAHHO6V4USKABMVICOIKZ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/76MGTBAHHO6V4USKABMVICOIKZ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:76MGTBAHHO6V4USKABMVICOIKZ","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":"3c53fc1031d41b3afe5d4420de2fabaa83799b7fcdaa5c5f707e04450d5c1369","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-09T18:44:10Z","title_canon_sha256":"560419c834a5dad2bd2a85dcd6caf82cf5e5301daaab8bdebfeb6c3e865c151f"},"schema_version":"1.0","source":{"id":"2501.05502","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.05502","created_at":"2026-07-05T09:59:24Z"},{"alias_kind":"arxiv_version","alias_value":"2501.05502v1","created_at":"2026-07-05T09:59:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.05502","created_at":"2026-07-05T09:59:24Z"},{"alias_kind":"pith_short_12","alias_value":"76MGTBAHHO6V","created_at":"2026-07-05T09:59:24Z"},{"alias_kind":"pith_short_16","alias_value":"76MGTBAHHO6V4USK","created_at":"2026-07-05T09:59:24Z"},{"alias_kind":"pith_short_8","alias_value":"76MGTBAH","created_at":"2026-07-05T09:59:24Z"}],"graph_snapshots":[{"event_id":"sha256:bf8fa406f6e9212aa17ffcb99b64c56bf50357dcd11799db4f084501f46023dd","target":"graph","created_at":"2026-07-05T09:59:24Z","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/2501.05502/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Although transformer-based models have been dominating the field of deep learning, various studies of their embedding space have shown that they suffer from \"representation degeneration problem\": embeddings tend to be distributed in a narrow cone, making the latent space highly anisotropic. Increasing the isotropy has shown to improve performance in downstream tasks both in static and contextual language models. However, most of approaches either add inference overhead or require substantial amount of data for model reparametrization. We propose a novel regularization technique based on simpli","authors_text":"Eduard Klyshinsky, Olesya Karpik, Sergei Kudriashov","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-09T18:44:10Z","title":"Shrink the longest: improving latent space isotropy with symplicial geometry"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.05502","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:ca76d616c0f3706968983d728621d437a15cf7e7ddc25fbd02bf9c39409544b9","target":"record","created_at":"2026-07-05T09:59:24Z","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":"3c53fc1031d41b3afe5d4420de2fabaa83799b7fcdaa5c5f707e04450d5c1369","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-09T18:44:10Z","title_canon_sha256":"560419c834a5dad2bd2a85dcd6caf82cf5e5301daaab8bdebfeb6c3e865c151f"},"schema_version":"1.0","source":{"id":"2501.05502","kind":"arxiv","version":1}},"canonical_sha256":"ff986984073bbd5e524a00595409c8567b63933000be41bd37540f2baad09ede","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ff986984073bbd5e524a00595409c8567b63933000be41bd37540f2baad09ede","first_computed_at":"2026-07-05T09:59:24.435939Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:59:24.435939Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"JkMcmR46ONG0v4c+P2sz+hnGX4SvbL64xRyvIq7RAk1krfKdharB3uxXJtxwwZ/7d7nlMUzrNwj+wAQS3vrIBg==","signature_status":"signed_v1","signed_at":"2026-07-05T09:59:24.436403Z","signed_message":"canonical_sha256_bytes"},"source_id":"2501.05502","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ca76d616c0f3706968983d728621d437a15cf7e7ddc25fbd02bf9c39409544b9","sha256:bf8fa406f6e9212aa17ffcb99b64c56bf50357dcd11799db4f084501f46023dd"],"state_sha256":"a3f0014e9c7ac55c522c0a2d42e85cae6cc53cd50b9300adfccbf32ad2b756a8"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vfEMXTa0A4P/3WvvamRUNoa7MRKDZa3tgXhhD/O2vHBgvOOTOhvCGF1l7WMCHTIqHTtLxg3B5+M7gJp7HxwrBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-09T05:00:36.948918Z","bundle_sha256":"966d06877c5f18b3dfb0e100d37ca009340b81d2824f14e2e3f5530ffe5bf704"}}