{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:RWCECVYNUSECWSGA3UMXOZBFUX","short_pith_number":"pith:RWCECVYN","schema_version":"1.0","canonical_sha256":"8d8441570da4882b48c0dd19776425a5e4829dd07a03ac3e4aab278f2c535f68","source":{"kind":"arxiv","id":"2607.07740","version":1},"attestation_state":"computed","paper":{"title":"Jet-Long: Efficient Long-Context Extension with Dynamic Bifocal RoPE","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Han Cai, Haozhan Tang, Song Han, Yuxian Gu, Zerui Wang","submitted_at":"2026-07-08T06:23:42Z","abstract_excerpt":"Modern LLMs are increasingly deployed in long-context applications such as retrieval-augmented generation, repository-level coding, and agentic workflows whose accumulated reasoning and tool traces routinely push the input an order of magnitude past the pretraining window, making zero-shot context extension the dominant deployment path for open-weight checkpoints. Most existing zero-shot methods fix a single rescaling factor up front, so an aggressive factor sacrifices short-context fidelity while a conservative one breaks down at long contexts. We propose Jet-Long, a tuning-free zero-shot met"},"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":"2607.07740","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-07-08T06:23:42Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"c2d781cb158c1b31079e0d294177ca6bdd50937b7417246237ee1e841e70386e","abstract_canon_sha256":"38cf051eeaa54bf950c373845d63244a882ebb76e179b1d7be8f5f582dfbca68"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-10T00:18:47.598889Z","signature_b64":"4eitf+neCIMcC5zdp1uXTJs+8YxjByqaE2oPWBW/zPuH3egAJa3eOamxzRPKUV2JH4/w2W85tR1JG8OwWbgvAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8d8441570da4882b48c0dd19776425a5e4829dd07a03ac3e4aab278f2c535f68","last_reissued_at":"2026-07-10T00:18:47.598502Z","signature_status":"signed_v1","first_computed_at":"2026-07-10T00:18:47.598502Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Jet-Long: Efficient Long-Context Extension with Dynamic Bifocal RoPE","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Han Cai, Haozhan Tang, Song Han, Yuxian Gu, Zerui Wang","submitted_at":"2026-07-08T06:23:42Z","abstract_excerpt":"Modern LLMs are increasingly deployed in long-context applications such as retrieval-augmented generation, repository-level coding, and agentic workflows whose accumulated reasoning and tool traces routinely push the input an order of magnitude past the pretraining window, making zero-shot context extension the dominant deployment path for open-weight checkpoints. Most existing zero-shot methods fix a single rescaling factor up front, so an aggressive factor sacrifices short-context fidelity while a conservative one breaks down at long contexts. We propose Jet-Long, a tuning-free zero-shot met"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.07740","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/2607.07740/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":"2607.07740","created_at":"2026-07-10T00:18:47.598571+00:00"},{"alias_kind":"arxiv_version","alias_value":"2607.07740v1","created_at":"2026-07-10T00:18:47.598571+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.07740","created_at":"2026-07-10T00:18:47.598571+00:00"},{"alias_kind":"pith_short_12","alias_value":"RWCECVYNUSEC","created_at":"2026-07-10T00:18:47.598571+00:00"},{"alias_kind":"pith_short_16","alias_value":"RWCECVYNUSECWSGA","created_at":"2026-07-10T00:18:47.598571+00:00"},{"alias_kind":"pith_short_8","alias_value":"RWCECVYN","created_at":"2026-07-10T00:18:47.598571+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/RWCECVYNUSECWSGA3UMXOZBFUX","json":"https://pith.science/pith/RWCECVYNUSECWSGA3UMXOZBFUX.json","graph_json":"https://pith.science/api/pith-number/RWCECVYNUSECWSGA3UMXOZBFUX/graph.json","events_json":"https://pith.science/api/pith-number/RWCECVYNUSECWSGA3UMXOZBFUX/events.json","paper":"https://pith.science/paper/RWCECVYN"},"agent_actions":{"view_html":"https://pith.science/pith/RWCECVYNUSECWSGA3UMXOZBFUX","download_json":"https://pith.science/pith/RWCECVYNUSECWSGA3UMXOZBFUX.json","view_paper":"https://pith.science/paper/RWCECVYN","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2607.07740&json=true","fetch_graph":"https://pith.science/api/pith-number/RWCECVYNUSECWSGA3UMXOZBFUX/graph.json","fetch_events":"https://pith.science/api/pith-number/RWCECVYNUSECWSGA3UMXOZBFUX/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/RWCECVYNUSECWSGA3UMXOZBFUX/action/timestamp_anchor","attest_storage":"https://pith.science/pith/RWCECVYNUSECWSGA3UMXOZBFUX/action/storage_attestation","attest_author":"https://pith.science/pith/RWCECVYNUSECWSGA3UMXOZBFUX/action/author_attestation","sign_citation":"https://pith.science/pith/RWCECVYNUSECWSGA3UMXOZBFUX/action/citation_signature","submit_replication":"https://pith.science/pith/RWCECVYNUSECWSGA3UMXOZBFUX/action/replication_record"}},"created_at":"2026-07-10T00:18:47.598571+00:00","updated_at":"2026-07-10T00:18:47.598571+00:00"}