{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:2EWTQHJYYEZCWN2COMHX5WHDC4","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":"3791b2c3430835e86ace5a9f05fc116484975429d7a5de264418607bde94e9dc","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-06-26T04:07:41Z","title_canon_sha256":"9b016afecb2d64c3d9b60bf98c31a8129854826da07bb8a15df76a7c7e5a9bc6"},"schema_version":"1.0","source":{"id":"2606.27705","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.27705","created_at":"2026-06-29T01:14:45Z"},{"alias_kind":"arxiv_version","alias_value":"2606.27705v1","created_at":"2026-06-29T01:14:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.27705","created_at":"2026-06-29T01:14:45Z"},{"alias_kind":"pith_short_12","alias_value":"2EWTQHJYYEZC","created_at":"2026-06-29T01:14:45Z"},{"alias_kind":"pith_short_16","alias_value":"2EWTQHJYYEZCWN2C","created_at":"2026-06-29T01:14:45Z"},{"alias_kind":"pith_short_8","alias_value":"2EWTQHJY","created_at":"2026-06-29T01:14:45Z"}],"graph_snapshots":[{"event_id":"sha256:1fcab0410185d4a7bd0df1f2f8549365062d2fa275f9413b787f6998a53ebbbc","target":"graph","created_at":"2026-06-29T01:14:45Z","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/2606.27705/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large Language Models (LLMs) still struggle with the ``lost-in-the-middle'' problem, where critical information located in the middle of long-context inputs is often underrepresented or lost. While existing methods attempt to address this by combining multi-scale rotary position embeddings (RoPE), they typically suffer from high latency or rely on suboptimal hand-crafted scaling strategies. To overcome these limitations, we introduce a layer-specific positional embedding scaling~(LPES) method that assigns distinct scaling factors to each layer. LPES achieves a more balanced attention distribut","authors_text":"Changze Lv, Muling Wu, Qi Qian, Shizheng Li, Tianlong Li, Tianyuan Shi, Xiaoqing Zheng, Xuanjing Huang, Yiran Ding, Yixin Wu, Zhenghua Wang, Zhibo Xu","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-06-26T04:07:41Z","title":"Mitigating Position Bias in Transformers via Layer-Specific Positional Embedding Scaling"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.27705","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:b6fb11a2002ee4f98e3c9d51ba142b6871eea4e90de83164fbc1513e1a72ade0","target":"record","created_at":"2026-06-29T01:14:45Z","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":"3791b2c3430835e86ace5a9f05fc116484975429d7a5de264418607bde94e9dc","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-06-26T04:07:41Z","title_canon_sha256":"9b016afecb2d64c3d9b60bf98c31a8129854826da07bb8a15df76a7c7e5a9bc6"},"schema_version":"1.0","source":{"id":"2606.27705","kind":"arxiv","version":1}},"canonical_sha256":"d12d381d38c1322b3742730f7ed8e3173d6588eefe31a6ae4f61e28e706add79","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d12d381d38c1322b3742730f7ed8e3173d6588eefe31a6ae4f61e28e706add79","first_computed_at":"2026-06-29T01:14:45.998406Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-29T01:14:45.998406Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"QwmVu+AR42SeruNVqkWlExEw6MFDaPdsJSyxe19pbRxFhgLaweqeLoow+99whdU58K0GNAWZsRyiowhdHPzaBg==","signature_status":"signed_v1","signed_at":"2026-06-29T01:14:45.998776Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.27705","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b6fb11a2002ee4f98e3c9d51ba142b6871eea4e90de83164fbc1513e1a72ade0","sha256:1fcab0410185d4a7bd0df1f2f8549365062d2fa275f9413b787f6998a53ebbbc"],"state_sha256":"1d328ffe5e93f9b0f7d05cd92cc2443546985b28a54d9ad4457b3eb227e771a3"}