{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:ETVERKYZG6AMZQGIDHPVHRALYB","short_pith_number":"pith:ETVERKYZ","canonical_record":{"source":{"id":"2406.07001","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-06-11T06:53:19Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"4e7b6ecb01bf6c91799a1d84f23b1133b82cf670fff76127008e9e4ec8d5ba8e","abstract_canon_sha256":"5661ec01fddb6f25894e990f73fcda111327539f9b38973aaf147d5ce27a0a9d"},"schema_version":"1.0"},"canonical_sha256":"24ea48ab193780ccc0c819df53c40bc077a8ef13c667abd80c0ef68ff90cbb9b","source":{"kind":"arxiv","id":"2406.07001","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.07001","created_at":"2026-07-05T08:30:16Z"},{"alias_kind":"arxiv_version","alias_value":"2406.07001v1","created_at":"2026-07-05T08:30:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.07001","created_at":"2026-07-05T08:30:16Z"},{"alias_kind":"pith_short_12","alias_value":"ETVERKYZG6AM","created_at":"2026-07-05T08:30:16Z"},{"alias_kind":"pith_short_16","alias_value":"ETVERKYZG6AMZQGI","created_at":"2026-07-05T08:30:16Z"},{"alias_kind":"pith_short_8","alias_value":"ETVERKYZ","created_at":"2026-07-05T08:30:16Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:ETVERKYZG6AMZQGIDHPVHRALYB","target":"record","payload":{"canonical_record":{"source":{"id":"2406.07001","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-06-11T06:53:19Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"4e7b6ecb01bf6c91799a1d84f23b1133b82cf670fff76127008e9e4ec8d5ba8e","abstract_canon_sha256":"5661ec01fddb6f25894e990f73fcda111327539f9b38973aaf147d5ce27a0a9d"},"schema_version":"1.0"},"canonical_sha256":"24ea48ab193780ccc0c819df53c40bc077a8ef13c667abd80c0ef68ff90cbb9b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:30:16.563181Z","signature_b64":"na3CnlLb/GXQIdTALRiGDnHNPP4a23+xUUNFTq2sZtqxzPfeLgVZ1QvS/20d4OSvMjw959LX5KIZsvtdgN3GBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"24ea48ab193780ccc0c819df53c40bc077a8ef13c667abd80c0ef68ff90cbb9b","last_reissued_at":"2026-07-05T08:30:16.562748Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:30:16.562748Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2406.07001","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":"2026-07-05T08:30:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"JR78HYhMF/PUoVaikDgLUVxHAFTjc7ZFOe7GHrtuj34vUKqN1gnpvUr7u3Xa0MKdESPx2ACh9Czhg178lCSfBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T19:08:00.894359Z"},"content_sha256":"3224ff88d6fc9730e742da71d88413d21cbee2f223df800c8da35edc279a6067","schema_version":"1.0","event_id":"sha256:3224ff88d6fc9730e742da71d88413d21cbee2f223df800c8da35edc279a6067"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:ETVERKYZG6AMZQGIDHPVHRALYB","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Mitigating Boundary Ambiguity and Inherent Bias for Text Classification in the Era of Large Language Models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Dangyang Chen, Jie Tian, Wei Wei, Wenfeng Xie, Xiaoye Qu, Yu Cheng, Zhenyi Lu","submitted_at":"2024-06-11T06:53:19Z","abstract_excerpt":"Text classification is a crucial task encountered frequently in practical scenarios, yet it is still under-explored in the era of large language models (LLMs). This study shows that LLMs are vulnerable to changes in the number and arrangement of options in text classification. Our extensive empirical analyses reveal that the key bottleneck arises from ambiguous decision boundaries and inherent biases towards specific tokens and positions. To mitigate these issues, we make the first attempt and propose a novel two-stage classification framework for LLMs. Our approach is grounded in the empirica"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.07001","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/2406.07001/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":"2026-07-05T08:30:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"h/M7UYXlKmLyYjJckag1sS/ut/Kcq0rKniGkrP1w6aCzhGmYZ/hactXnYAAqx2uHEgDZ7uobUAtNAx8zcu96DQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T19:08:00.901023Z"},"content_sha256":"46195f36ee4d60ac05ab567e7d311a03fd6c1435e40b07c5fec473dc7d5a06bc","schema_version":"1.0","event_id":"sha256:46195f36ee4d60ac05ab567e7d311a03fd6c1435e40b07c5fec473dc7d5a06bc"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ETVERKYZG6AMZQGIDHPVHRALYB/bundle.json","state_url":"https://pith.science/pith/ETVERKYZG6AMZQGIDHPVHRALYB/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ETVERKYZG6AMZQGIDHPVHRALYB/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":"2026-08-06T19:08:00Z","links":{"resolver":"https://pith.science/pith/ETVERKYZG6AMZQGIDHPVHRALYB","bundle":"https://pith.science/pith/ETVERKYZG6AMZQGIDHPVHRALYB/bundle.json","state":"https://pith.science/pith/ETVERKYZG6AMZQGIDHPVHRALYB/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ETVERKYZG6AMZQGIDHPVHRALYB/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:ETVERKYZG6AMZQGIDHPVHRALYB","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":"5661ec01fddb6f25894e990f73fcda111327539f9b38973aaf147d5ce27a0a9d","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-06-11T06:53:19Z","title_canon_sha256":"4e7b6ecb01bf6c91799a1d84f23b1133b82cf670fff76127008e9e4ec8d5ba8e"},"schema_version":"1.0","source":{"id":"2406.07001","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.07001","created_at":"2026-07-05T08:30:16Z"},{"alias_kind":"arxiv_version","alias_value":"2406.07001v1","created_at":"2026-07-05T08:30:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.07001","created_at":"2026-07-05T08:30:16Z"},{"alias_kind":"pith_short_12","alias_value":"ETVERKYZG6AM","created_at":"2026-07-05T08:30:16Z"},{"alias_kind":"pith_short_16","alias_value":"ETVERKYZG6AMZQGI","created_at":"2026-07-05T08:30:16Z"},{"alias_kind":"pith_short_8","alias_value":"ETVERKYZ","created_at":"2026-07-05T08:30:16Z"}],"graph_snapshots":[{"event_id":"sha256:46195f36ee4d60ac05ab567e7d311a03fd6c1435e40b07c5fec473dc7d5a06bc","target":"graph","created_at":"2026-07-05T08:30:16Z","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/2406.07001/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Text classification is a crucial task encountered frequently in practical scenarios, yet it is still under-explored in the era of large language models (LLMs). This study shows that LLMs are vulnerable to changes in the number and arrangement of options in text classification. Our extensive empirical analyses reveal that the key bottleneck arises from ambiguous decision boundaries and inherent biases towards specific tokens and positions. To mitigate these issues, we make the first attempt and propose a novel two-stage classification framework for LLMs. Our approach is grounded in the empirica","authors_text":"Dangyang Chen, Jie Tian, Wei Wei, Wenfeng Xie, Xiaoye Qu, Yu Cheng, Zhenyi Lu","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-06-11T06:53:19Z","title":"Mitigating Boundary Ambiguity and Inherent Bias for Text Classification in the Era of Large Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.07001","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":"sha256:3224ff88d6fc9730e742da71d88413d21cbee2f223df800c8da35edc279a6067","target":"record","created_at":"2026-07-05T08:30:16Z","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":"5661ec01fddb6f25894e990f73fcda111327539f9b38973aaf147d5ce27a0a9d","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-06-11T06:53:19Z","title_canon_sha256":"4e7b6ecb01bf6c91799a1d84f23b1133b82cf670fff76127008e9e4ec8d5ba8e"},"schema_version":"1.0","source":{"id":"2406.07001","kind":"arxiv","version":1}},"canonical_sha256":"24ea48ab193780ccc0c819df53c40bc077a8ef13c667abd80c0ef68ff90cbb9b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"24ea48ab193780ccc0c819df53c40bc077a8ef13c667abd80c0ef68ff90cbb9b","first_computed_at":"2026-07-05T08:30:16.562748Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:30:16.562748Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"na3CnlLb/GXQIdTALRiGDnHNPP4a23+xUUNFTq2sZtqxzPfeLgVZ1QvS/20d4OSvMjw959LX5KIZsvtdgN3GBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T08:30:16.563181Z","signed_message":"canonical_sha256_bytes"},"source_id":"2406.07001","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3224ff88d6fc9730e742da71d88413d21cbee2f223df800c8da35edc279a6067","sha256:46195f36ee4d60ac05ab567e7d311a03fd6c1435e40b07c5fec473dc7d5a06bc"],"state_sha256":"23d7ed67f0eb34c5c731c6857e37a39eccd834b865b4ca8eae48d58a17c55a00"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"v8ljvlx+FSfLUwMA12NK5exKOAoKOnbDNDGtSVwXMUSXhnN/wvgiG4132US1XAdB9HlJ+Vat/b7PdHuHUx6ODQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T19:08:00.916177Z","bundle_sha256":"b7a08b546da0f33b2df1e16f655b0bf2123481407676a2fe7c24b885c15e5b86"}}