{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:H2MEXLC6UVSNY2YAMUJHVZGJ3E","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":"1297cefb0c29f3dd0590271b48015f64bfc901b0a433f3e4265ccf3dd0227b99","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-12-16T12:29:24Z","title_canon_sha256":"37857671bf3c0dd0db4d419c45f2c16fba672b977af0b4e7d5b6e3de1035e60f"},"schema_version":"1.0","source":{"id":"2412.11707","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.11707","created_at":"2026-07-05T09:49:50Z"},{"alias_kind":"arxiv_version","alias_value":"2412.11707v1","created_at":"2026-07-05T09:49:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.11707","created_at":"2026-07-05T09:49:50Z"},{"alias_kind":"pith_short_12","alias_value":"H2MEXLC6UVSN","created_at":"2026-07-05T09:49:50Z"},{"alias_kind":"pith_short_16","alias_value":"H2MEXLC6UVSNY2YA","created_at":"2026-07-05T09:49:50Z"},{"alias_kind":"pith_short_8","alias_value":"H2MEXLC6","created_at":"2026-07-05T09:49:50Z"}],"graph_snapshots":[{"event_id":"sha256:a7075ef473439fcd3c3929235386f4d6be2f11ce8c5e3bfcc69c02bd5733f6d7","target":"graph","created_at":"2026-07-05T09:49:50Z","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/2412.11707/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Question Answering (QA) in NLP is the task of finding answers to a query within a relevant context retrieved by a retrieval system. Yet, the mix of relevant and irrelevant information in these contexts can hinder performance enhancements in QA tasks. To address this, we introduce a context filtering approach that removes non-essential details, summarizing crucial content through Reward Modeling. This method emphasizes keeping vital data while omitting the extraneous during summarization model training. We offer a framework for developing efficient QA models by discerning useful information fro","authors_text":"James Thorne, Sangryul Kim","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-12-16T12:29:24Z","title":"Context Filtering with Reward Modeling in Question Answering"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.11707","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":"sha256:0f6d4fb078bae678a76b83182ccac4c8fd4d923fe2b1ae7aa0b8313293d3ac7b","target":"record","created_at":"2026-07-05T09:49:50Z","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":"1297cefb0c29f3dd0590271b48015f64bfc901b0a433f3e4265ccf3dd0227b99","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-12-16T12:29:24Z","title_canon_sha256":"37857671bf3c0dd0db4d419c45f2c16fba672b977af0b4e7d5b6e3de1035e60f"},"schema_version":"1.0","source":{"id":"2412.11707","kind":"arxiv","version":1}},"canonical_sha256":"3e984bac5ea564dc6b0065127ae4c9d90cba7b30ae8d0126f81880f1da455fa7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3e984bac5ea564dc6b0065127ae4c9d90cba7b30ae8d0126f81880f1da455fa7","first_computed_at":"2026-07-05T09:49:50.387926Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:49:50.387926Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"vUUmhAiZ2Fyr40iHDqpBv34wPR0UUzlnWqaGBjnz4TEFCrOA0BXuWOUQtrGfpt9ixtUTVJ9860Rf7pY0fWohBA==","signature_status":"signed_v1","signed_at":"2026-07-05T09:49:50.388363Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.11707","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0f6d4fb078bae678a76b83182ccac4c8fd4d923fe2b1ae7aa0b8313293d3ac7b","sha256:a7075ef473439fcd3c3929235386f4d6be2f11ce8c5e3bfcc69c02bd5733f6d7"],"state_sha256":"87053818e4c94dccb8a88a7bee16b409406956c7f6d85f56a164728606b2e42f"}