{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:ME6RPETXPCAUE5TPTJZ7ZIWWWJ","short_pith_number":"pith:ME6RPETX","canonical_record":{"source":{"id":"2311.06647","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-11-11T19:34:06Z","cross_cats_sorted":[],"title_canon_sha256":"9573e094370a48d9333a4b5e9a666dc45eb3de56fa8f6a2755193722d8455fdc","abstract_canon_sha256":"456f4bdc3ce81be49a895107acb7a79828b03bc67e47c455027bf1313512e99a"},"schema_version":"1.0"},"canonical_sha256":"613d179277788142766f9a73fca2d6b25b534a4aefe01383f15a7d2995a56101","source":{"kind":"arxiv","id":"2311.06647","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.06647","created_at":"2026-07-05T09:26:56Z"},{"alias_kind":"arxiv_version","alias_value":"2311.06647v3","created_at":"2026-07-05T09:26:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.06647","created_at":"2026-07-05T09:26:56Z"},{"alias_kind":"pith_short_12","alias_value":"ME6RPETXPCAU","created_at":"2026-07-05T09:26:56Z"},{"alias_kind":"pith_short_16","alias_value":"ME6RPETXPCAUE5TP","created_at":"2026-07-05T09:26:56Z"},{"alias_kind":"pith_short_8","alias_value":"ME6RPETX","created_at":"2026-07-05T09:26:56Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:ME6RPETXPCAUE5TPTJZ7ZIWWWJ","target":"record","payload":{"canonical_record":{"source":{"id":"2311.06647","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-11-11T19:34:06Z","cross_cats_sorted":[],"title_canon_sha256":"9573e094370a48d9333a4b5e9a666dc45eb3de56fa8f6a2755193722d8455fdc","abstract_canon_sha256":"456f4bdc3ce81be49a895107acb7a79828b03bc67e47c455027bf1313512e99a"},"schema_version":"1.0"},"canonical_sha256":"613d179277788142766f9a73fca2d6b25b534a4aefe01383f15a7d2995a56101","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:26:56.926113Z","signature_b64":"36aPMbTNxwcXQBcgvaU+DFvPKmEXbRknZfc1Oyc2M0NYntV6D63sg+/J5JWKoNDk9D7dEy11b7yJzo5yc2TKCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"613d179277788142766f9a73fca2d6b25b534a4aefe01383f15a7d2995a56101","last_reissued_at":"2026-07-05T09:26:56.925650Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:26:56.925650Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2311.06647","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:26:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wAuOiVJRqMIm7S0vxzS877erlfA58t0Y/wxskMx+63Wei8nc9tmoaiNqk4vOnBo5U6rKSBlWpRq5N4r80PzUDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T01:43:22.112946Z"},"content_sha256":"ddb3ff265d8f7af8c2c472905f5ca31e8e7a737d119886aeccfc98f60d7ac8eb","schema_version":"1.0","event_id":"sha256:ddb3ff265d8f7af8c2c472905f5ca31e8e7a737d119886aeccfc98f60d7ac8eb"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:ME6RPETXPCAUE5TPTJZ7ZIWWWJ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Robust Text Classification: Analyzing Prototype-Based Networks","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Darshan Deshpande, Filip Ilievski, Kiril Gashteovski, Sascha Saralajew, Zhivar Sourati","submitted_at":"2023-11-11T19:34:06Z","abstract_excerpt":"Downstream applications often require text classification models to be accurate and robust. While the accuracy of the state-of-the-art Language Models (LMs) approximates human performance, they often exhibit a drop in performance on noisy data found in the real world. This lack of robustness can be concerning, as even small perturbations in the text, irrelevant to the target task, can cause classifiers to incorrectly change their predictions. A potential solution can be the family of Prototype-Based Networks (PBNs) that classifies examples based on their similarity to prototypical examples of "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.06647","kind":"arxiv","version":3},"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/2311.06647/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":"2026-07-05T09:26:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"t+MZBLX8ta49thBpUec51AvTNfb/Z6KnvAAaiHxGNtmhl8+fZRQ9p+JblABHwc4VG1PZRAut5zKTB+Vfip/UAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T01:43:22.114049Z"},"content_sha256":"64d26e81f6b6321ab283e100dffbf53b7caf6bc4a360f0ce14fc9d38bf5b9122","schema_version":"1.0","event_id":"sha256:64d26e81f6b6321ab283e100dffbf53b7caf6bc4a360f0ce14fc9d38bf5b9122"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ME6RPETXPCAUE5TPTJZ7ZIWWWJ/bundle.json","state_url":"https://pith.science/pith/ME6RPETXPCAUE5TPTJZ7ZIWWWJ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ME6RPETXPCAUE5TPTJZ7ZIWWWJ/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":"2026-08-04T01:43:22Z","links":{"resolver":"https://pith.science/pith/ME6RPETXPCAUE5TPTJZ7ZIWWWJ","bundle":"https://pith.science/pith/ME6RPETXPCAUE5TPTJZ7ZIWWWJ/bundle.json","state":"https://pith.science/pith/ME6RPETXPCAUE5TPTJZ7ZIWWWJ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ME6RPETXPCAUE5TPTJZ7ZIWWWJ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:ME6RPETXPCAUE5TPTJZ7ZIWWWJ","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":"456f4bdc3ce81be49a895107acb7a79828b03bc67e47c455027bf1313512e99a","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-11-11T19:34:06Z","title_canon_sha256":"9573e094370a48d9333a4b5e9a666dc45eb3de56fa8f6a2755193722d8455fdc"},"schema_version":"1.0","source":{"id":"2311.06647","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.06647","created_at":"2026-07-05T09:26:56Z"},{"alias_kind":"arxiv_version","alias_value":"2311.06647v3","created_at":"2026-07-05T09:26:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.06647","created_at":"2026-07-05T09:26:56Z"},{"alias_kind":"pith_short_12","alias_value":"ME6RPETXPCAU","created_at":"2026-07-05T09:26:56Z"},{"alias_kind":"pith_short_16","alias_value":"ME6RPETXPCAUE5TP","created_at":"2026-07-05T09:26:56Z"},{"alias_kind":"pith_short_8","alias_value":"ME6RPETX","created_at":"2026-07-05T09:26:56Z"}],"graph_snapshots":[{"event_id":"sha256:64d26e81f6b6321ab283e100dffbf53b7caf6bc4a360f0ce14fc9d38bf5b9122","target":"graph","created_at":"2026-07-05T09:26:56Z","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/2311.06647/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Downstream applications often require text classification models to be accurate and robust. While the accuracy of the state-of-the-art Language Models (LMs) approximates human performance, they often exhibit a drop in performance on noisy data found in the real world. This lack of robustness can be concerning, as even small perturbations in the text, irrelevant to the target task, can cause classifiers to incorrectly change their predictions. A potential solution can be the family of Prototype-Based Networks (PBNs) that classifies examples based on their similarity to prototypical examples of ","authors_text":"Darshan Deshpande, Filip Ilievski, Kiril Gashteovski, Sascha Saralajew, Zhivar Sourati","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-11-11T19:34:06Z","title":"Robust Text Classification: Analyzing Prototype-Based Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.06647","kind":"arxiv","version":3},"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:ddb3ff265d8f7af8c2c472905f5ca31e8e7a737d119886aeccfc98f60d7ac8eb","target":"record","created_at":"2026-07-05T09:26:56Z","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":"456f4bdc3ce81be49a895107acb7a79828b03bc67e47c455027bf1313512e99a","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-11-11T19:34:06Z","title_canon_sha256":"9573e094370a48d9333a4b5e9a666dc45eb3de56fa8f6a2755193722d8455fdc"},"schema_version":"1.0","source":{"id":"2311.06647","kind":"arxiv","version":3}},"canonical_sha256":"613d179277788142766f9a73fca2d6b25b534a4aefe01383f15a7d2995a56101","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"613d179277788142766f9a73fca2d6b25b534a4aefe01383f15a7d2995a56101","first_computed_at":"2026-07-05T09:26:56.925650Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:26:56.925650Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"36aPMbTNxwcXQBcgvaU+DFvPKmEXbRknZfc1Oyc2M0NYntV6D63sg+/J5JWKoNDk9D7dEy11b7yJzo5yc2TKCg==","signature_status":"signed_v1","signed_at":"2026-07-05T09:26:56.926113Z","signed_message":"canonical_sha256_bytes"},"source_id":"2311.06647","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ddb3ff265d8f7af8c2c472905f5ca31e8e7a737d119886aeccfc98f60d7ac8eb","sha256:64d26e81f6b6321ab283e100dffbf53b7caf6bc4a360f0ce14fc9d38bf5b9122"],"state_sha256":"6de7f898ab7f11a35413b52a5dd5e885f1e5a571c3d07b6a9722184e550bea5c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TcLZhKPhSB73bPFaV4wdDycL0zNtRLpUEKtrCxT3AlJdPmjP2oFbIiToTrPBk38J+rfF7mdRj0iCOs1yXDZ6Dw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T01:43:22.122193Z","bundle_sha256":"c76591fefbf4402f9f7c9af9d1a46573b50b48e6b2fd35ce2122be4912ea9a2f"}}