{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:XLQO5R65URE77MSK3MJZTRKTZN","short_pith_number":"pith:XLQO5R65","schema_version":"1.0","canonical_sha256":"bae0eec7dda449ffb24adb1399c553cb6ec57dbf0c21e83c1a154f37c2c28173","source":{"kind":"arxiv","id":"2411.05000","version":2},"attestation_state":"computed","paper":{"title":"Needle Threading: Can LLMs Follow Threads through Near-Million-Scale Haystacks?","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Jonathan Roberts, Kai Han, Samuel Albanie","submitted_at":"2024-11-07T18:59:27Z","abstract_excerpt":"As the context limits of Large Language Models (LLMs) increase, the range of possible applications and downstream functions broadens. In many real-world tasks, decisions depend on details scattered across collections of often disparate documents containing mostly irrelevant information. Long-context LLMs appear well-suited to this form of complex information retrieval and reasoning, which has traditionally proven costly and time-consuming. However, although the development of longer context models has seen rapid gains in recent years, our understanding of how effectively LLMs use their context"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2411.05000","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-11-07T18:59:27Z","cross_cats_sorted":[],"title_canon_sha256":"0351da4b5f846ccadc639332028edcc5d9beb22987922303e8c7965e0b0b2075","abstract_canon_sha256":"d21f4ad74ee793a5dfd3d7ceb6ce421b14b8c885adb351c39c2add985b218be0"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:52:38.255440Z","signature_b64":"rBpaN5fVwW+UmLEB0+S1zo2fSJBx30T0OD3llGmEDQMBlzEbfeBUHGbbPyAhGLv+FDE5Rg22zFQxp9Y3O4E7BQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bae0eec7dda449ffb24adb1399c553cb6ec57dbf0c21e83c1a154f37c2c28173","last_reissued_at":"2026-07-05T10:52:38.254954Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:52:38.254954Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Needle Threading: Can LLMs Follow Threads through Near-Million-Scale Haystacks?","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Jonathan Roberts, Kai Han, Samuel Albanie","submitted_at":"2024-11-07T18:59:27Z","abstract_excerpt":"As the context limits of Large Language Models (LLMs) increase, the range of possible applications and downstream functions broadens. In many real-world tasks, decisions depend on details scattered across collections of often disparate documents containing mostly irrelevant information. Long-context LLMs appear well-suited to this form of complex information retrieval and reasoning, which has traditionally proven costly and time-consuming. However, although the development of longer context models has seen rapid gains in recent years, our understanding of how effectively LLMs use their context"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.05000","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/2411.05000/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2411.05000","created_at":"2026-07-05T10:52:38.255005+00:00"},{"alias_kind":"arxiv_version","alias_value":"2411.05000v2","created_at":"2026-07-05T10:52:38.255005+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.05000","created_at":"2026-07-05T10:52:38.255005+00:00"},{"alias_kind":"pith_short_12","alias_value":"XLQO5R65URE7","created_at":"2026-07-05T10:52:38.255005+00:00"},{"alias_kind":"pith_short_16","alias_value":"XLQO5R65URE77MSK","created_at":"2026-07-05T10:52:38.255005+00:00"},{"alias_kind":"pith_short_8","alias_value":"XLQO5R65","created_at":"2026-07-05T10:52:38.255005+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2507.01734","citing_title":"LLMs for Legal Subsumption in German Employment Contracts","ref_index":26,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/XLQO5R65URE77MSK3MJZTRKTZN","json":"https://pith.science/pith/XLQO5R65URE77MSK3MJZTRKTZN.json","graph_json":"https://pith.science/api/pith-number/XLQO5R65URE77MSK3MJZTRKTZN/graph.json","events_json":"https://pith.science/api/pith-number/XLQO5R65URE77MSK3MJZTRKTZN/events.json","paper":"https://pith.science/paper/XLQO5R65"},"agent_actions":{"view_html":"https://pith.science/pith/XLQO5R65URE77MSK3MJZTRKTZN","download_json":"https://pith.science/pith/XLQO5R65URE77MSK3MJZTRKTZN.json","view_paper":"https://pith.science/paper/XLQO5R65","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2411.05000&json=true","fetch_graph":"https://pith.science/api/pith-number/XLQO5R65URE77MSK3MJZTRKTZN/graph.json","fetch_events":"https://pith.science/api/pith-number/XLQO5R65URE77MSK3MJZTRKTZN/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/XLQO5R65URE77MSK3MJZTRKTZN/action/timestamp_anchor","attest_storage":"https://pith.science/pith/XLQO5R65URE77MSK3MJZTRKTZN/action/storage_attestation","attest_author":"https://pith.science/pith/XLQO5R65URE77MSK3MJZTRKTZN/action/author_attestation","sign_citation":"https://pith.science/pith/XLQO5R65URE77MSK3MJZTRKTZN/action/citation_signature","submit_replication":"https://pith.science/pith/XLQO5R65URE77MSK3MJZTRKTZN/action/replication_record"}},"created_at":"2026-07-05T10:52:38.255005+00:00","updated_at":"2026-07-05T10:52:38.255005+00:00"}