{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:KMQG4YXGAHZZRP3AXA26PN7F75","short_pith_number":"pith:KMQG4YXG","canonical_record":{"source":{"id":"2311.09198","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-11-15T18:42:44Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"8942487661615109acb084d64c174efd397f516254279b0914203e16d3113c6c","abstract_canon_sha256":"cfd455c344a5568c74320c02f673caee0e5a0744a0109ca749b8447b3f20038b"},"schema_version":"1.0"},"canonical_sha256":"53206e62e601f398bf60b835e7b7e5ff5c0d2b38d0cdbeeb3259b3d4971c3d28","source":{"kind":"arxiv","id":"2311.09198","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.09198","created_at":"2026-07-05T08:55:07Z"},{"alias_kind":"arxiv_version","alias_value":"2311.09198v2","created_at":"2026-07-05T08:55:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.09198","created_at":"2026-07-05T08:55:07Z"},{"alias_kind":"pith_short_12","alias_value":"KMQG4YXGAHZZ","created_at":"2026-07-05T08:55:07Z"},{"alias_kind":"pith_short_16","alias_value":"KMQG4YXGAHZZRP3A","created_at":"2026-07-05T08:55:07Z"},{"alias_kind":"pith_short_8","alias_value":"KMQG4YXG","created_at":"2026-07-05T08:55:07Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:KMQG4YXGAHZZRP3AXA26PN7F75","target":"record","payload":{"canonical_record":{"source":{"id":"2311.09198","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-11-15T18:42:44Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"8942487661615109acb084d64c174efd397f516254279b0914203e16d3113c6c","abstract_canon_sha256":"cfd455c344a5568c74320c02f673caee0e5a0744a0109ca749b8447b3f20038b"},"schema_version":"1.0"},"canonical_sha256":"53206e62e601f398bf60b835e7b7e5ff5c0d2b38d0cdbeeb3259b3d4971c3d28","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:55:07.055213Z","signature_b64":"snsx7uMrzrq6yn+jcIaDyAX8WAb3zPw7S+Y5ZitgAhsYrHkhMjqmiAv0SoWiC/ffGYrE2+5iBzpsSukcFaPeCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"53206e62e601f398bf60b835e7b7e5ff5c0d2b38d0cdbeeb3259b3d4971c3d28","last_reissued_at":"2026-07-05T08:55:07.054805Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:55:07.054805Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2311.09198","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:55:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1Tv+zjddeu6Z4D/wMc+ilRvaiLCiYLIFwHccrcBaSwrm2iUe6/MkCggUDtNTiObZIo6knNSbeU1DxTRlgtViBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T18:50:31.343458Z"},"content_sha256":"8168a3d20657ec2d5aaa2c959374e5ad7f8bead831d2ecf1fb68402f199ded95","schema_version":"1.0","event_id":"sha256:8168a3d20657ec2d5aaa2c959374e5ad7f8bead831d2ecf1fb68402f199ded95"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:KMQG4YXGAHZZRP3AXA26PN7F75","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Never Lost in the Middle: Mastering Long-Context Question Answering with Position-Agnostic Decompositional Training","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Enming Zhang, Hao Wang, Jiaxing Zhang, Junqing He, Kunhao Pan, Qianguo Sun, Xiaoqun Dong, Yibo Liu, Yuxin Liang, Zhuoyang Song","submitted_at":"2023-11-15T18:42:44Z","abstract_excerpt":"While large language models (LLMs) are equipped with longer text input capabilities than before, they are struggling to seek correct information in long contexts. The \"lost in the middle\" problem challenges most LLMs, referring to the dramatic decline in accuracy when correct information is located in the middle. To overcome this crucial issue, this paper proposes to enhance the information searching and reflection ability of LLMs in long contexts via specially designed tasks called Attention Strengthening Multi-doc QA (ASM QA). Following these tasks, our model excels in focusing more precisel"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.09198","kind":"arxiv","version":2},"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/2311.09198/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":"2026-07-05T08:55:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8Ef+OoN8RxxD+ZjjZkKvQ+Dk8RCdZewiXa1VyD/2EYi8PM+lsFCUSyflUAsdzpt2MycI+q5AkSI39UtLD+fdBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T18:50:31.343975Z"},"content_sha256":"f4f68c542380f6cee1dd338f1289f98e3775109e71f6070626e80d0e07137bb8","schema_version":"1.0","event_id":"sha256:f4f68c542380f6cee1dd338f1289f98e3775109e71f6070626e80d0e07137bb8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/KMQG4YXGAHZZRP3AXA26PN7F75/bundle.json","state_url":"https://pith.science/pith/KMQG4YXGAHZZRP3AXA26PN7F75/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/KMQG4YXGAHZZRP3AXA26PN7F75/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":"2026-08-09T18:50:31Z","links":{"resolver":"https://pith.science/pith/KMQG4YXGAHZZRP3AXA26PN7F75","bundle":"https://pith.science/pith/KMQG4YXGAHZZRP3AXA26PN7F75/bundle.json","state":"https://pith.science/pith/KMQG4YXGAHZZRP3AXA26PN7F75/state.json","well_known_bundle":"https://pith.science/.well-known/pith/KMQG4YXGAHZZRP3AXA26PN7F75/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:KMQG4YXGAHZZRP3AXA26PN7F75","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":"cfd455c344a5568c74320c02f673caee0e5a0744a0109ca749b8447b3f20038b","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-11-15T18:42:44Z","title_canon_sha256":"8942487661615109acb084d64c174efd397f516254279b0914203e16d3113c6c"},"schema_version":"1.0","source":{"id":"2311.09198","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.09198","created_at":"2026-07-05T08:55:07Z"},{"alias_kind":"arxiv_version","alias_value":"2311.09198v2","created_at":"2026-07-05T08:55:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.09198","created_at":"2026-07-05T08:55:07Z"},{"alias_kind":"pith_short_12","alias_value":"KMQG4YXGAHZZ","created_at":"2026-07-05T08:55:07Z"},{"alias_kind":"pith_short_16","alias_value":"KMQG4YXGAHZZRP3A","created_at":"2026-07-05T08:55:07Z"},{"alias_kind":"pith_short_8","alias_value":"KMQG4YXG","created_at":"2026-07-05T08:55:07Z"}],"graph_snapshots":[{"event_id":"sha256:f4f68c542380f6cee1dd338f1289f98e3775109e71f6070626e80d0e07137bb8","target":"graph","created_at":"2026-07-05T08:55:07Z","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/2311.09198/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"While large language models (LLMs) are equipped with longer text input capabilities than before, they are struggling to seek correct information in long contexts. The \"lost in the middle\" problem challenges most LLMs, referring to the dramatic decline in accuracy when correct information is located in the middle. To overcome this crucial issue, this paper proposes to enhance the information searching and reflection ability of LLMs in long contexts via specially designed tasks called Attention Strengthening Multi-doc QA (ASM QA). Following these tasks, our model excels in focusing more precisel","authors_text":"Enming Zhang, Hao Wang, Jiaxing Zhang, Junqing He, Kunhao Pan, Qianguo Sun, Xiaoqun Dong, Yibo Liu, Yuxin Liang, Zhuoyang Song","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-11-15T18:42:44Z","title":"Never Lost in the Middle: Mastering Long-Context Question Answering with Position-Agnostic Decompositional Training"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.09198","kind":"arxiv","version":2},"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":"sha256:8168a3d20657ec2d5aaa2c959374e5ad7f8bead831d2ecf1fb68402f199ded95","target":"record","created_at":"2026-07-05T08:55:07Z","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":"cfd455c344a5568c74320c02f673caee0e5a0744a0109ca749b8447b3f20038b","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-11-15T18:42:44Z","title_canon_sha256":"8942487661615109acb084d64c174efd397f516254279b0914203e16d3113c6c"},"schema_version":"1.0","source":{"id":"2311.09198","kind":"arxiv","version":2}},"canonical_sha256":"53206e62e601f398bf60b835e7b7e5ff5c0d2b38d0cdbeeb3259b3d4971c3d28","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"53206e62e601f398bf60b835e7b7e5ff5c0d2b38d0cdbeeb3259b3d4971c3d28","first_computed_at":"2026-07-05T08:55:07.054805Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:55:07.054805Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"snsx7uMrzrq6yn+jcIaDyAX8WAb3zPw7S+Y5ZitgAhsYrHkhMjqmiAv0SoWiC/ffGYrE2+5iBzpsSukcFaPeCA==","signature_status":"signed_v1","signed_at":"2026-07-05T08:55:07.055213Z","signed_message":"canonical_sha256_bytes"},"source_id":"2311.09198","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8168a3d20657ec2d5aaa2c959374e5ad7f8bead831d2ecf1fb68402f199ded95","sha256:f4f68c542380f6cee1dd338f1289f98e3775109e71f6070626e80d0e07137bb8"],"state_sha256":"7894c531af791efd735990482161eeaedb488976027dbf48fa9ccee998bb831d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8DCByw5gOPD9Pc2AG97U/SjTNE4PiareGD+RQHdczDVOa+CP3y1+877hBf9Y1CcpWMDKfHYenfJVAgil3ic6Cw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T18:50:31.349337Z","bundle_sha256":"cc5b87b9e131293e4f8736b2d7b2944289d37cc8e1336dabf64b08a64df30d5f"}}