{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:UPYHCTT2H7J4T2Q7OJRXENSPPG","short_pith_number":"pith:UPYHCTT2","canonical_record":{"source":{"id":"2606.05494","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2026-06-03T22:34:40Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"581b28eb119bcad94ebdd0c281aff4c522a2cd793c3110d4ce9797a52733a5f8","abstract_canon_sha256":"769c1efe2f1a5ca9870d567821dbaa772d71a7e8efc8023b0e3d87d173e1f7c4"},"schema_version":"1.0"},"canonical_sha256":"a3f0714e7a3fd3c9ea1f726372364f798a47b2082a3e052fb404293cc12f13d4","source":{"kind":"arxiv","id":"2606.05494","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.05494","created_at":"2026-06-05T01:14:52Z"},{"alias_kind":"arxiv_version","alias_value":"2606.05494v1","created_at":"2026-06-05T01:14:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.05494","created_at":"2026-06-05T01:14:52Z"},{"alias_kind":"pith_short_12","alias_value":"UPYHCTT2H7J4","created_at":"2026-06-05T01:14:52Z"},{"alias_kind":"pith_short_16","alias_value":"UPYHCTT2H7J4T2Q7","created_at":"2026-06-05T01:14:52Z"},{"alias_kind":"pith_short_8","alias_value":"UPYHCTT2","created_at":"2026-06-05T01:14:52Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:UPYHCTT2H7J4T2Q7OJRXENSPPG","target":"record","payload":{"canonical_record":{"source":{"id":"2606.05494","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2026-06-03T22:34:40Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"581b28eb119bcad94ebdd0c281aff4c522a2cd793c3110d4ce9797a52733a5f8","abstract_canon_sha256":"769c1efe2f1a5ca9870d567821dbaa772d71a7e8efc8023b0e3d87d173e1f7c4"},"schema_version":"1.0"},"canonical_sha256":"a3f0714e7a3fd3c9ea1f726372364f798a47b2082a3e052fb404293cc12f13d4","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-05T01:14:52.881707Z","signature_b64":"lnNzq1vRxa7T4vGLENkwXQTQ5DTX6PI3oeyadW3nHko3hkHl8KRGZvzNM+i+AMAwsDGrwOW+Ikj7/CE4/IX9DA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a3f0714e7a3fd3c9ea1f726372364f798a47b2082a3e052fb404293cc12f13d4","last_reissued_at":"2026-06-05T01:14:52.881166Z","signature_status":"signed_v1","first_computed_at":"2026-06-05T01:14:52.881166Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2606.05494","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":"2026-06-05T01:14:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PVWE1qRc7vTF7ompGCjR4hF+ADK+uGR3+79oyyvJ2c2rvMb6LHGgRcDWEjyTVDiwpqT+nwVYn4EnKF217kH1AA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-31T22:56:25.074719Z"},"content_sha256":"bda260ba3043aef9cf25ff8091855b7354b0c792c6358fb8761650110507f1fd","schema_version":"1.0","event_id":"sha256:bda260ba3043aef9cf25ff8091855b7354b0c792c6358fb8761650110507f1fd"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:UPYHCTT2H7J4T2Q7OJRXENSPPG","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"MASF: A Multi-Model Adaptive Selection Framework for Abstractive Text summarization","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Ahmed Alansary, Ali Hamdi","submitted_at":"2026-06-03T22:34:40Z","abstract_excerpt":"Automatic text summarization has become increasingly important due to the rapid growth of digital textual information. This paper presents a Multi-Model Adaptive Summarization Framework designed to improve the robustness and quality of abstractive text summarization. Relying on a single model often leads to inconsistent summarization quality across articles with varying structures and topics. To address this limitation, the proposed framework integrates multiple fine-tuned transformer-based summarization models and introduces an adaptive selection mechanism. In this framework, each model indep"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.05494","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/2606.05494/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":"2026-06-05T01:14:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"srGRclt/eQG1aXlfNgep2J/MXMyxPhk7qgfmk7HF/lyx0u3RbJXruyNzqABljh41mGDrKFZ1UQxclAfFjSH8CQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-31T22:56:25.075572Z"},"content_sha256":"f3e20d27c49d02c212e19ea3bc6ab140499d6d1169e46e8d4d6ee835c9b97cc7","schema_version":"1.0","event_id":"sha256:f3e20d27c49d02c212e19ea3bc6ab140499d6d1169e46e8d4d6ee835c9b97cc7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/UPYHCTT2H7J4T2Q7OJRXENSPPG/bundle.json","state_url":"https://pith.science/pith/UPYHCTT2H7J4T2Q7OJRXENSPPG/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/UPYHCTT2H7J4T2Q7OJRXENSPPG/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":"2026-07-31T22:56:25Z","links":{"resolver":"https://pith.science/pith/UPYHCTT2H7J4T2Q7OJRXENSPPG","bundle":"https://pith.science/pith/UPYHCTT2H7J4T2Q7OJRXENSPPG/bundle.json","state":"https://pith.science/pith/UPYHCTT2H7J4T2Q7OJRXENSPPG/state.json","well_known_bundle":"https://pith.science/.well-known/pith/UPYHCTT2H7J4T2Q7OJRXENSPPG/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:UPYHCTT2H7J4T2Q7OJRXENSPPG","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":"769c1efe2f1a5ca9870d567821dbaa772d71a7e8efc8023b0e3d87d173e1f7c4","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2026-06-03T22:34:40Z","title_canon_sha256":"581b28eb119bcad94ebdd0c281aff4c522a2cd793c3110d4ce9797a52733a5f8"},"schema_version":"1.0","source":{"id":"2606.05494","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.05494","created_at":"2026-06-05T01:14:52Z"},{"alias_kind":"arxiv_version","alias_value":"2606.05494v1","created_at":"2026-06-05T01:14:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.05494","created_at":"2026-06-05T01:14:52Z"},{"alias_kind":"pith_short_12","alias_value":"UPYHCTT2H7J4","created_at":"2026-06-05T01:14:52Z"},{"alias_kind":"pith_short_16","alias_value":"UPYHCTT2H7J4T2Q7","created_at":"2026-06-05T01:14:52Z"},{"alias_kind":"pith_short_8","alias_value":"UPYHCTT2","created_at":"2026-06-05T01:14:52Z"}],"graph_snapshots":[{"event_id":"sha256:f3e20d27c49d02c212e19ea3bc6ab140499d6d1169e46e8d4d6ee835c9b97cc7","target":"graph","created_at":"2026-06-05T01:14:52Z","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/2606.05494/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Automatic text summarization has become increasingly important due to the rapid growth of digital textual information. This paper presents a Multi-Model Adaptive Summarization Framework designed to improve the robustness and quality of abstractive text summarization. Relying on a single model often leads to inconsistent summarization quality across articles with varying structures and topics. To address this limitation, the proposed framework integrates multiple fine-tuned transformer-based summarization models and introduces an adaptive selection mechanism. In this framework, each model indep","authors_text":"Ahmed Alansary, Ali Hamdi","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2026-06-03T22:34:40Z","title":"MASF: A Multi-Model Adaptive Selection Framework for Abstractive Text summarization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.05494","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:bda260ba3043aef9cf25ff8091855b7354b0c792c6358fb8761650110507f1fd","target":"record","created_at":"2026-06-05T01:14:52Z","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":"769c1efe2f1a5ca9870d567821dbaa772d71a7e8efc8023b0e3d87d173e1f7c4","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2026-06-03T22:34:40Z","title_canon_sha256":"581b28eb119bcad94ebdd0c281aff4c522a2cd793c3110d4ce9797a52733a5f8"},"schema_version":"1.0","source":{"id":"2606.05494","kind":"arxiv","version":1}},"canonical_sha256":"a3f0714e7a3fd3c9ea1f726372364f798a47b2082a3e052fb404293cc12f13d4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a3f0714e7a3fd3c9ea1f726372364f798a47b2082a3e052fb404293cc12f13d4","first_computed_at":"2026-06-05T01:14:52.881166Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-05T01:14:52.881166Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"lnNzq1vRxa7T4vGLENkwXQTQ5DTX6PI3oeyadW3nHko3hkHl8KRGZvzNM+i+AMAwsDGrwOW+Ikj7/CE4/IX9DA==","signature_status":"signed_v1","signed_at":"2026-06-05T01:14:52.881707Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.05494","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:bda260ba3043aef9cf25ff8091855b7354b0c792c6358fb8761650110507f1fd","sha256:f3e20d27c49d02c212e19ea3bc6ab140499d6d1169e46e8d4d6ee835c9b97cc7"],"state_sha256":"b65ae0a919610a94d4ff0818f19ad55208ad7e7f3bdaf04f2ba6daa551342249"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"b3pNb3OAFuGH/RJ4UiaNk3XXpQLg9JbSDMkONBUuOJkmnGokCSzS4bGNDI7uBUaHXS83zRXDgWPMc8s0NK1NAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-31T22:56:25.080490Z","bundle_sha256":"4e5e5624ac40a9a9f9dd177bfe1705da699d5ba75dadf31ce26ffebe8a52bd08"}}