{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:QL7SAMHNY7437GRWE5E7NBEZJK","short_pith_number":"pith:QL7SAMHN","canonical_record":{"source":{"id":"2505.01238","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-05-02T13:00:05Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"17f04512099a837c56a2cbcd23132cc2f7e67d775ad782b76eb90b44f35ee2e9","abstract_canon_sha256":"f8d4e406acba7110da445e717d5dd7c8fecabdb46f0000eff062fa8e9068c8b3"},"schema_version":"1.0"},"canonical_sha256":"82ff2030edc7f9bf9a362749f684994a925e39417b605fca8d0d43e820d1944e","source":{"kind":"arxiv","id":"2505.01238","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.01238","created_at":"2026-07-05T10:57:47Z"},{"alias_kind":"arxiv_version","alias_value":"2505.01238v1","created_at":"2026-07-05T10:57:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.01238","created_at":"2026-07-05T10:57:47Z"},{"alias_kind":"pith_short_12","alias_value":"QL7SAMHNY743","created_at":"2026-07-05T10:57:47Z"},{"alias_kind":"pith_short_16","alias_value":"QL7SAMHNY7437GRW","created_at":"2026-07-05T10:57:47Z"},{"alias_kind":"pith_short_8","alias_value":"QL7SAMHN","created_at":"2026-07-05T10:57:47Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:QL7SAMHNY7437GRWE5E7NBEZJK","target":"record","payload":{"canonical_record":{"source":{"id":"2505.01238","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-05-02T13:00:05Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"17f04512099a837c56a2cbcd23132cc2f7e67d775ad782b76eb90b44f35ee2e9","abstract_canon_sha256":"f8d4e406acba7110da445e717d5dd7c8fecabdb46f0000eff062fa8e9068c8b3"},"schema_version":"1.0"},"canonical_sha256":"82ff2030edc7f9bf9a362749f684994a925e39417b605fca8d0d43e820d1944e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:57:47.971695Z","signature_b64":"xM8bRbTfRYhRFSZmyfHfxxWeL3VJoPvlFO0P4RecRtOGbI0hF0wyaGBmJTEjkjg5902WtZiae39bK0qbd5J+CQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"82ff2030edc7f9bf9a362749f684994a925e39417b605fca8d0d43e820d1944e","last_reissued_at":"2026-07-05T10:57:47.971158Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:57:47.971158Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2505.01238","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":"2026-07-05T10:57:47Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SB39TQ1JfhUbrBawR8u7z9Q7UsMjYSl4JT1YaJrEtrIkEVYUuXHvik/RcKj/Ysbeo+anC6/eUMITw+VlK4gXDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T13:34:39.908516Z"},"content_sha256":"f11ff51f20f49b99d29f99ac1adb2546d22cba8e00ea0ba39b5ea33e024f7d74","schema_version":"1.0","event_id":"sha256:f11ff51f20f49b99d29f99ac1adb2546d22cba8e00ea0ba39b5ea33e024f7d74"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:QL7SAMHNY7437GRWE5E7NBEZJK","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"EvalxNLP: A Framework for Benchmarking Post-Hoc Explainability Methods on NLP Models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.CL","authors_text":"Efstratios Zaradoukas, Gjergji Kasneci, Kafaite Zahra Hussain, Mahdi Dhaini","submitted_at":"2025-05-02T13:00:05Z","abstract_excerpt":"As Natural Language Processing (NLP) models continue to evolve and become integral to high-stakes applications, ensuring their interpretability remains a critical challenge. Given the growing variety of explainability methods and diverse stakeholder requirements, frameworks that help stakeholders select appropriate explanations tailored to their specific use cases are increasingly important. To address this need, we introduce EvalxNLP, a Python framework for benchmarking state-of-the-art feature attribution methods for transformer-based NLP models. EvalxNLP integrates eight widely recognized e"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.01238","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/2505.01238/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":"2026-07-05T10:57:47Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bPk7bgEdYmPzwsX/wkKwV8J2O4Q1mThZL4v3sovqKPSs4zAYBI1gSTq8YEkrNI9KfN9hhcy8FpuGHUCwYGU9Aw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T13:34:39.908890Z"},"content_sha256":"c43e1c0f28f04d484e8015bc51b7900d7ff0135a6473efb95dc16520fa967642","schema_version":"1.0","event_id":"sha256:c43e1c0f28f04d484e8015bc51b7900d7ff0135a6473efb95dc16520fa967642"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/QL7SAMHNY7437GRWE5E7NBEZJK/bundle.json","state_url":"https://pith.science/pith/QL7SAMHNY7437GRWE5E7NBEZJK/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/QL7SAMHNY7437GRWE5E7NBEZJK/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":"2026-07-07T13:34:39Z","links":{"resolver":"https://pith.science/pith/QL7SAMHNY7437GRWE5E7NBEZJK","bundle":"https://pith.science/pith/QL7SAMHNY7437GRWE5E7NBEZJK/bundle.json","state":"https://pith.science/pith/QL7SAMHNY7437GRWE5E7NBEZJK/state.json","well_known_bundle":"https://pith.science/.well-known/pith/QL7SAMHNY7437GRWE5E7NBEZJK/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:QL7SAMHNY7437GRWE5E7NBEZJK","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":"f8d4e406acba7110da445e717d5dd7c8fecabdb46f0000eff062fa8e9068c8b3","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-05-02T13:00:05Z","title_canon_sha256":"17f04512099a837c56a2cbcd23132cc2f7e67d775ad782b76eb90b44f35ee2e9"},"schema_version":"1.0","source":{"id":"2505.01238","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.01238","created_at":"2026-07-05T10:57:47Z"},{"alias_kind":"arxiv_version","alias_value":"2505.01238v1","created_at":"2026-07-05T10:57:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.01238","created_at":"2026-07-05T10:57:47Z"},{"alias_kind":"pith_short_12","alias_value":"QL7SAMHNY743","created_at":"2026-07-05T10:57:47Z"},{"alias_kind":"pith_short_16","alias_value":"QL7SAMHNY7437GRW","created_at":"2026-07-05T10:57:47Z"},{"alias_kind":"pith_short_8","alias_value":"QL7SAMHN","created_at":"2026-07-05T10:57:47Z"}],"graph_snapshots":[{"event_id":"sha256:c43e1c0f28f04d484e8015bc51b7900d7ff0135a6473efb95dc16520fa967642","target":"graph","created_at":"2026-07-05T10:57:47Z","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/2505.01238/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"As Natural Language Processing (NLP) models continue to evolve and become integral to high-stakes applications, ensuring their interpretability remains a critical challenge. Given the growing variety of explainability methods and diverse stakeholder requirements, frameworks that help stakeholders select appropriate explanations tailored to their specific use cases are increasingly important. To address this need, we introduce EvalxNLP, a Python framework for benchmarking state-of-the-art feature attribution methods for transformer-based NLP models. EvalxNLP integrates eight widely recognized e","authors_text":"Efstratios Zaradoukas, Gjergji Kasneci, Kafaite Zahra Hussain, Mahdi Dhaini","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-05-02T13:00:05Z","title":"EvalxNLP: A Framework for Benchmarking Post-Hoc Explainability Methods on NLP Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.01238","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:f11ff51f20f49b99d29f99ac1adb2546d22cba8e00ea0ba39b5ea33e024f7d74","target":"record","created_at":"2026-07-05T10:57:47Z","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":"f8d4e406acba7110da445e717d5dd7c8fecabdb46f0000eff062fa8e9068c8b3","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-05-02T13:00:05Z","title_canon_sha256":"17f04512099a837c56a2cbcd23132cc2f7e67d775ad782b76eb90b44f35ee2e9"},"schema_version":"1.0","source":{"id":"2505.01238","kind":"arxiv","version":1}},"canonical_sha256":"82ff2030edc7f9bf9a362749f684994a925e39417b605fca8d0d43e820d1944e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"82ff2030edc7f9bf9a362749f684994a925e39417b605fca8d0d43e820d1944e","first_computed_at":"2026-07-05T10:57:47.971158Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:57:47.971158Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"xM8bRbTfRYhRFSZmyfHfxxWeL3VJoPvlFO0P4RecRtOGbI0hF0wyaGBmJTEjkjg5902WtZiae39bK0qbd5J+CQ==","signature_status":"signed_v1","signed_at":"2026-07-05T10:57:47.971695Z","signed_message":"canonical_sha256_bytes"},"source_id":"2505.01238","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f11ff51f20f49b99d29f99ac1adb2546d22cba8e00ea0ba39b5ea33e024f7d74","sha256:c43e1c0f28f04d484e8015bc51b7900d7ff0135a6473efb95dc16520fa967642"],"state_sha256":"cf305a96b638ac3a9dd8bc05cb7cfd5941e52d92d675319a3b32193baeeffbd6"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vPdw7spiPzcNtaPQBvAgwh7PLcWSjg8cKUWNpgleyjJ1AHKOmkajku9HHlv/fxp8P5zZDOgrCGyV7RP3awDtDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T13:34:39.910843Z","bundle_sha256":"1fca21b75abbeb315ef266948c904100c0de2baeb34816b47aa74cb54917ba79"}}