{"as_of":"2026-08-18T11:25:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:050ace202f3ac98cd092ae1ec991e5ec23cdcd5a3fd5243d159bd73d0e2608f1","coverage":[{"denominator":49,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":49,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-16T10:12:42.560499Z","state":"measured"},{"denominator":49,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":49,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-18T06:34:40.430872+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2504.18857/citation-record","integrity":"/paper/2504.18857/integrity","json":"/paper/2504.18857/citation-record.json","paper":"/paper/2504.18857"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:42.352771Z","title":"write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2504.18857","last_updated":"2025-04-26T08:46:10Z","snapshot_observed_at":"2026-08-17T00:01:03.539955Z","submitted_at":"2025-04-26T08:46:10Z","title":"Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-16T10:12:42.352771Z"},"links":{"citing_paper":"/paper/2504.18857"},"observation_digest":"sha256:f7784bc5b4d5a47ee102d60f94e2e4ef646b8cbee6d2405e5bdcd7dbde91fb88","observation_id":"50c080f3-4015-429f-8b13-0bc663c7d6e7","resolution":{"observed_at":"2026-08-16T10:12:42.352771Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:43.350876Z","title":"Mistral OCR , 2025","venue":null,"work_id":"357a185e-7646-4cec-a120-0eff30b4c259","year":2025},"citing_paper":{"arxiv_id":"2504.18857","last_updated":"2025-04-26T08:46:10Z","snapshot_observed_at":"2026-08-17T00:01:03.539955Z","submitted_at":"2025-04-26T08:46:10Z","title":"Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-16T10:12:42.358309Z"},"links":{"citing_paper":"/paper/2504.18857"},"observation_digest":"sha256:a80cd8bcfe1da8d353d652992a7e6b959f915607dc5e8bae9dfae368c8ece114","observation_id":"2102f14e-1d4e-4dfa-987d-fa0a51a2b3c2","resolution":{"observed_at":"2026-08-16T10:12:43.355058Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:42.362859Z","title":"Llama 3 model card","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.18857","last_updated":"2025-04-26T08:46:10Z","snapshot_observed_at":"2026-08-17T00:01:03.539955Z","submitted_at":"2025-04-26T08:46:10Z","title":"Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-16T10:12:42.362859Z"},"links":{"citing_paper":"/paper/2504.18857"},"observation_digest":"sha256:f0884cb6463fa2e977c2c51d189cd4171120a2f72f0d3ba6108346fdf130f356","observation_id":"a8b48045-d8c6-492d-bf6e-e14f6f6dd26a","resolution":{"observed_at":"2026-08-16T10:12:42.362859Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:43.323052Z","title":"Training-free long-context scaling of large language models, 2024 a","venue":null,"work_id":"a8f26333-ba28-47f0-bcc0-abaa0395329b","year":2024},"citing_paper":{"arxiv_id":"2504.18857","last_updated":"2025-04-26T08:46:10Z","snapshot_observed_at":"2026-08-17T00:01:03.539955Z","submitted_at":"2025-04-26T08:46:10Z","title":"Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-16T10:12:42.367012Z"},"links":{"citing_paper":"/paper/2504.18857"},"observation_digest":"sha256:ca15330c46aa897cd78e0849b6beb9dbb7090df6698d4a3c3e2598310dd38da6","observation_id":"b60bf7b5-a616-47ef-a428-6fc438f4d616","resolution":{"observed_at":"2026-08-16T10:12:43.327548Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.18745","last_updated":"2024-10-24T13:51:50Z","snapshot_observed_at":"2026-08-16T13:06:16.669745Z","submitted_at":"2024-10-24T13:51:50Z","title":"Why Does the Effective Context Length of LLMs Fall Short?","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.18745","snapshot_observed_at":"2026-08-16T10:12:42.370953Z","title":"Why does the effective context length of llms fall short?, 2024 b","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.18857","last_updated":"2025-04-26T08:46:10Z","snapshot_observed_at":"2026-08-17T00:01:03.539955Z","submitted_at":"2025-04-26T08:46:10Z","title":"Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-16T10:12:42.370953Z"},"links":{"cited_paper":"/paper/2410.18745","citing_paper":"/paper/2504.18857"},"observation_digest":"sha256:ba31b5b4777dd794d84ac4bd91d7c5ef409c90354e12d145143b3f6737a527e6","observation_id":"3f8256ae-7200-4e76-8c14-7cd9db4447a3","resolution":{"observed_at":"2026-08-16T10:12:42.370953Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.06205","last_updated":"2025-05-13T14:11:59Z","snapshot_observed_at":"2026-08-16T13:11:25.569465Z","submitted_at":"2024-10-08T17:07:01Z","title":"Round and Round We Go! What makes Rotary Positional Encodings useful?","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.06205","snapshot_observed_at":"2026-08-16T10:12:42.375452Z","title":"Round and round we go! what makes rotary positional encodings useful?, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2504.18857","last_updated":"2025-04-26T08:46:10Z","snapshot_observed_at":"2026-08-17T00:01:03.539955Z","submitted_at":"2025-04-26T08:46:10Z","title":"Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-16T10:12:42.375452Z"},"links":{"cited_paper":"/paper/2410.06205","citing_paper":"/paper/2504.18857"},"observation_digest":"sha256:7f9c0adfa4b9494b1894e5d0ab33680a343b4b8e41551bde51688903bd471c0a","observation_id":"28b28619-2a90-4f6d-a3d4-dbe2489f69ff","resolution":{"observed_at":"2026-08-16T10:12:42.375452Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:43.308683Z","title":"NTK-Aware Scaled RoPE allows LLaMA models to have extended (8k+) context size without any fine-tuning and minimal perplexity degradation , 2023 a","venue":null,"work_id":"dbc68131-e032-4ae1-b596-9f9b024d63fa","year":2023},"citing_paper":{"arxiv_id":"2504.18857","last_updated":"2025-04-26T08:46:10Z","snapshot_observed_at":"2026-08-17T00:01:03.539955Z","submitted_at":"2025-04-26T08:46:10Z","title":"Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-16T10:12:42.379722Z"},"links":{"citing_paper":"/paper/2504.18857"},"observation_digest":"sha256:c08c27569169419c655805a7442bcf43ad3f1e7688f13a8bb530ac88f96a2429","observation_id":"1c6a90f7-07d5-437d-8944-beb434769481","resolution":{"observed_at":"2026-08-16T10:12:43.312969Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:43.294142Z","title":"by parts","venue":null,"work_id":"8b0c1f84-893a-4455-ac0e-e36f54323fd2","year":2023},"citing_paper":{"arxiv_id":"2504.18857","last_updated":"2025-04-26T08:46:10Z","snapshot_observed_at":"2026-08-17T00:01:03.539955Z","submitted_at":"2025-04-26T08:46:10Z","title":"Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-16T10:12:42.384224Z"},"links":{"citing_paper":"/paper/2504.18857"},"observation_digest":"sha256:0b721ef469b182cb5640ea3218339e7962ed48c15ed1c2050f754cffac89688d","observation_id":"38bc8e17-d958-449e-8023-b82e96c57015","resolution":{"observed_at":"2026-08-16T10:12:43.298900Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.16450","last_updated":"2024-03-24T17:14:11Z","snapshot_observed_at":"2026-08-16T14:49:04.022878Z","submitted_at":"2023-10-25T08:13:02Z","title":"CLEX: Continuous Length Extrapolation for Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.16450","snapshot_observed_at":"2026-08-16T10:12:42.388272Z","title":"Clex: Continuous length extrapolation for large language models, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.18857","last_updated":"2025-04-26T08:46:10Z","snapshot_observed_at":"2026-08-17T00:01:03.539955Z","submitted_at":"2025-04-26T08:46:10Z","title":"Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-16T10:12:42.388272Z"},"links":{"cited_paper":"/paper/2310.16450","citing_paper":"/paper/2504.18857"},"observation_digest":"sha256:7323cf9715fcae8c795202f731a10f53952f77a824fb7913b7def74dfe35ef28","observation_id":"b5f3191d-51c8-40ce-866d-822409673925","resolution":{"observed_at":"2026-08-16T10:12:42.388272Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:43.279855Z","title":"Extending context window of large language models via positional interpolation, 2023","venue":null,"work_id":"7ee4da77-c17b-42b5-b8c1-2c471916e6ea","year":2023},"citing_paper":{"arxiv_id":"2504.18857","last_updated":"2025-04-26T08:46:10Z","snapshot_observed_at":"2026-08-17T00:01:03.539955Z","submitted_at":"2025-04-26T08:46:10Z","title":"Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-16T10:12:42.392529Z"},"links":{"citing_paper":"/paper/2504.18857"},"observation_digest":"sha256:6b3567607e22afd8f1c11ad69d74cd336549bbd91f15e6cabb6314cb42ee54c6","observation_id":"6ed76ba7-2338-4616-9299-9c6c9027934b","resolution":{"observed_at":"2026-08-16T10:12:43.284094Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:42.396631Z","title":"Transformer-xl: Attentive language models beyond a fixed-length context","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2504.18857","last_updated":"2025-04-26T08:46:10Z","snapshot_observed_at":"2026-08-17T00:01:03.539955Z","submitted_at":"2025-04-26T08:46:10Z","title":"Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-16T10:12:42.396631Z"},"links":{"citing_paper":"/paper/2504.18857"},"observation_digest":"sha256:840c8fd12cd70e3adaf3d82f56e6a3200bf3dd97c55491cb8a8f41879674e950","observation_id":"5d05916b-12cd-4511-bee1-40e975a18895","resolution":{"observed_at":"2026-08-16T10:12:42.396631Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.08691","last_updated":"2023-07-17T17:50:36Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-07-17T17:50:36Z","title":"FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.08691","snapshot_observed_at":"2026-08-16T10:12:42.400847Z","title":"Flashattention-2: Faster attention with better parallelism and work partitioning, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2504.18857","last_updated":"2025-04-26T08:46:10Z","snapshot_observed_at":"2026-08-17T00:01:03.539955Z","submitted_at":"2025-04-26T08:46:10Z","title":"Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-16T10:12:42.400847Z"},"links":{"cited_paper":"/paper/2307.08691","citing_paper":"/paper/2504.18857"},"observation_digest":"sha256:724482f4d9a842be00684097e0ac880ff4ea6dfac634efb70d42e1b3f1db3056","observation_id":"8c15ce5e-7fde-4760-9929-fbf8d861a745","resolution":{"observed_at":"2026-08-16T10:12:42.400847Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.12948","last_updated":"2026-01-04T03:57:36Z","snapshot_observed_at":"2026-08-15T12:33:55.451951Z","submitted_at":"2025-01-22T15:19:35Z","title":"DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.12948","snapshot_observed_at":"2026-08-16T10:12:42.404957Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2504.18857","last_updated":"2025-04-26T08:46:10Z","snapshot_observed_at":"2026-08-17T00:01:03.539955Z","submitted_at":"2025-04-26T08:46:10Z","title":"Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-16T10:12:42.404957Z"},"links":{"cited_paper":"/paper/2501.12948","citing_paper":"/paper/2504.18857"},"observation_digest":"sha256:c3ba69720a9476a4d3485b2cb6a0d2c12ddb7812357b64778513fdc289e3e7b3","observation_id":"8f2f6fb2-a616-4c63-99bf-a857633b1491","resolution":{"observed_at":"2026-08-16T10:12:42.404957Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.13753","last_updated":"2024-02-21T12:30:33Z","snapshot_observed_at":"2026-08-02T12:47:57.325302Z","submitted_at":"2024-02-21T12:30:33Z","title":"LongRoPE: Extending LLM Context Window Beyond 2 Million Tokens","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.13753","snapshot_observed_at":"2026-08-16T10:12:42.409071Z","title":"Longrope: Extending llm context window beyond 2 million tokens, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.18857","last_updated":"2025-04-26T08:46:10Z","snapshot_observed_at":"2026-08-17T00:01:03.539955Z","submitted_at":"2025-04-26T08:46:10Z","title":"Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-16T10:12:42.409071Z"},"links":{"cited_paper":"/paper/2402.13753","citing_paper":"/paper/2504.18857"},"observation_digest":"sha256:af2bc8fdc0d4ff5646c8f9211b5453c8bfdfa4ddbe368e128d45889eb9422325","observation_id":"870e9f1a-b168-4010-a2d4-f64d85f622b3","resolution":{"observed_at":"2026-08-16T10:12:42.409071Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:43.265056Z","title":"Dynamically Scaled RoPE further increases performance of long context LLaMA with zero fine-tuning , 2023","venue":null,"work_id":"4d636265-5f8d-4ef5-a739-2800e03e99fd","year":2023},"citing_paper":{"arxiv_id":"2504.18857","last_updated":"2025-04-26T08:46:10Z","snapshot_observed_at":"2026-08-17T00:01:03.539955Z","submitted_at":"2025-04-26T08:46:10Z","title":"Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-16T10:12:42.417442Z"},"links":{"citing_paper":"/paper/2504.18857"},"observation_digest":"sha256:b8261ba510b03dbfee7569cb41c62bb56bd12e1cdf1b34d7c9a01564595c91bb","observation_id":"bf85c87c-a6f8-4443-9575-94b39884a988","resolution":{"observed_at":"2026-08-16T10:12:43.269619Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:42.421268Z","title":"Data engineering for scaling language models to 128k context, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.18857","last_updated":"2025-04-26T08:46:10Z","snapshot_observed_at":"2026-08-17T00:01:03.539955Z","submitted_at":"2025-04-26T08:46:10Z","title":"Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-16T10:12:42.421268Z"},"links":{"citing_paper":"/paper/2504.18857"},"observation_digest":"sha256:3d8e4c78fb1dc236cae137b9bb195f33d437da5de4dade3f85b7ce17bbfb9fa9","observation_id":"2a127ca6-e92b-4be2-8bd9-98aa483f4b73","resolution":{"observed_at":"2026-08-16T10:12:42.421268Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:43.239293Z","title":"Needle in a haystack - pressure testing llms, 2023","venue":null,"work_id":"f3162a91-4486-4359-8c44-599cc338b7dc","year":2023},"citing_paper":{"arxiv_id":"2504.18857","last_updated":"2025-04-26T08:46:10Z","snapshot_observed_at":"2026-08-17T00:01:03.539955Z","submitted_at":"2025-04-26T08:46:10Z","title":"Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-16T10:12:42.425075Z"},"links":{"citing_paper":"/paper/2504.18857"},"observation_digest":"sha256:1d77c22cd7a99d17df2bb4f5cf87dbfd97a0f1adc980c67bc780fce66c17a54a","observation_id":"0491d7e6-5b08-4640-9312-e5ce2f8fe9f3","resolution":{"observed_at":"2026-08-16T10:12:43.243591Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.21783","last_updated":"2024-11-23T23:27:33Z","snapshot_observed_at":"2026-08-13T17:20:44.002518Z","submitted_at":"2024-07-31T17:54:27Z","title":"The Llama 3 Herd of Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.21783","snapshot_observed_at":"2026-08-16T10:12:42.429335Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.18857","last_updated":"2025-04-26T08:46:10Z","snapshot_observed_at":"2026-08-17T00:01:03.539955Z","submitted_at":"2025-04-26T08:46:10Z","title":"Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-16T10:12:42.429335Z"},"links":{"cited_paper":"/paper/2407.21783","citing_paper":"/paper/2504.18857"},"observation_digest":"sha256:5b7564acae05dcbfd47fa8142fa257630d839ff67c6b5d64c2f04114119e8638","observation_id":"e5f6f9df-13fa-40fa-b675-dd30fdec1f82","resolution":{"observed_at":"2026-08-16T10:12:42.429335Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:43.225109Z","title":"Lm-infinite: Simple on-the-fly length generalization for large language models, 2023","venue":null,"work_id":"eb2107f6-fcf3-4e5c-bc3e-99e1e2ee68fe","year":2023},"citing_paper":{"arxiv_id":"2504.18857","last_updated":"2025-04-26T08:46:10Z","snapshot_observed_at":"2026-08-17T00:01:03.539955Z","submitted_at":"2025-04-26T08:46:10Z","title":"Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-16T10:12:42.433391Z"},"links":{"citing_paper":"/paper/2504.18857"},"observation_digest":"sha256:9b9079dd562af49d6cdc4fa15cc642c2c4a62d7055169c9a53ff5b2649d79b2c","observation_id":"f886ebbf-1a91-4ca0-bbae-5fcebb9834ab","resolution":{"observed_at":"2026-08-16T10:12:43.229529Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.08703","last_updated":"2024-10-21T08:49:18Z","snapshot_observed_at":"2026-08-16T13:10:22.992305Z","submitted_at":"2024-10-11T10:47:02Z","title":"On the token distance modeling ability of higher RoPE attention dimension","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.08703","snapshot_observed_at":"2026-08-16T10:12:42.437305Z","title":"On the token distance modeling ability of higher rope attention dimension, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.18857","last_updated":"2025-04-26T08:46:10Z","snapshot_observed_at":"2026-08-17T00:01:03.539955Z","submitted_at":"2025-04-26T08:46:10Z","title":"Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-16T10:12:42.437305Z"},"links":{"cited_paper":"/paper/2410.08703","citing_paper":"/paper/2504.18857"},"observation_digest":"sha256:cc9382893efdf74ad7b98ee9da592258405752600c3346ec050a2b23fe8cb6eb","observation_id":"d9744afc-b26d-45b2-961d-7f1411ef2124","resolution":{"observed_at":"2026-08-16T10:12:42.437305Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:42.441667Z","title":"Ruler: What's the real context size of your long-context language models?, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.18857","last_updated":"2025-04-26T08:46:10Z","snapshot_observed_at":"2026-08-17T00:01:03.539955Z","submitted_at":"2025-04-26T08:46:10Z","title":"Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-16T10:12:42.441667Z"},"links":{"citing_paper":"/paper/2504.18857"},"observation_digest":"sha256:a1e77a96f89fb0283d6a73921d4769a3cdf07e519a65935ff961853fd23551ab","observation_id":"0a2b6c40-5fd3-456f-b373-804deb320710","resolution":{"observed_at":"2026-08-16T10:12:42.441667Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:42.445669Z","title":"Towards economical inference: Enabling deepseek's multi-head latent attention in any transformer-based llms, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2504.18857","last_updated":"2025-04-26T08:46:10Z","snapshot_observed_at":"2026-08-17T00:01:03.539955Z","submitted_at":"2025-04-26T08:46:10Z","title":"Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-16T10:12:42.445669Z"},"links":{"citing_paper":"/paper/2504.18857"},"observation_digest":"sha256:827cb1f7540e7e948ce2c7469d1a869574ffcfbe5dc2cfce4ae917a992b2d7e5","observation_id":"2a275480-5e27-4231-9704-ca1e2441937f","resolution":{"observed_at":"2026-08-16T10:12:42.445669Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.06825","last_updated":"2023-10-10T17:54:58Z","snapshot_observed_at":"2026-08-17T20:30:34.016254Z","submitted_at":"2023-10-10T17:54:58Z","title":"Mistral 7B","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.06825","snapshot_observed_at":"2026-08-16T10:12:42.449571Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2504.18857","last_updated":"2025-04-26T08:46:10Z","snapshot_observed_at":"2026-08-17T00:01:03.539955Z","submitted_at":"2025-04-26T08:46:10Z","title":"Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-16T10:12:42.449571Z"},"links":{"cited_paper":"/paper/2310.06825","citing_paper":"/paper/2504.18857"},"observation_digest":"sha256:07b2819b93a2a0bc81b51a5746b307b2be280512f95741b30c563fa5eec2d18d","observation_id":"6f62d702-8760-44bd-822f-c75f1de29917","resolution":{"observed_at":"2026-08-16T10:12:42.449571Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.02490","last_updated":"2024-10-30T14:53:22Z","snapshot_observed_at":"2026-08-16T23:28:24.568924Z","submitted_at":"2024-07-02T17:59:56Z","title":"MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.02490","snapshot_observed_at":"2026-08-16T10:12:42.454100Z","title":"Abdi, Dongsheng Li, Chin-Yew Lin, Yuqing Yang, and Lili Qiu","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.18857","last_updated":"2025-04-26T08:46:10Z","snapshot_observed_at":"2026-08-17T00:01:03.539955Z","submitted_at":"2025-04-26T08:46:10Z","title":"Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-16T10:12:42.454100Z"},"links":{"cited_paper":"/paper/2407.02490","citing_paper":"/paper/2504.18857"},"observation_digest":"sha256:56e30bea2fe6050a772a2b2f05707e990d80448580f28e462de5e3fa5af317a6","observation_id":"1033f936-1941-4a9e-9745-7e5a7660e1f8","resolution":{"observed_at":"2026-08-16T10:12:42.454100Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:42.458824Z","title":"Llm maybe longlm: Self-extend llm context window without tuning, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.18857","last_updated":"2025-04-26T08:46:10Z","snapshot_observed_at":"2026-08-17T00:01:03.539955Z","submitted_at":"2025-04-26T08:46:10Z","title":"Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-16T10:12:42.458824Z"},"links":{"citing_paper":"/paper/2504.18857"},"observation_digest":"sha256:5dbd0e3f83e9f024a9043c469d3111f8bc51c7c91104a710d5e2da34b03d2441","observation_id":"117e5444-d0b9-48da-90bf-6fa905d6c59f","resolution":{"observed_at":"2026-08-16T10:12:42.458824Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:42.463018Z","title":"Thus spake long-context large language model, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2504.18857","last_updated":"2025-04-26T08:46:10Z","snapshot_observed_at":"2026-08-17T00:01:03.539955Z","submitted_at":"2025-04-26T08:46:10Z","title":"Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-16T10:12:42.463018Z"},"links":{"citing_paper":"/paper/2504.18857"},"observation_digest":"sha256:75348c0df610056b44eb75954048a23b06064a4e6630e10854c9cccb287361bf","observation_id":"8e1ebfe7-ead9-4c48-bbda-caf97c86806f","resolution":{"observed_at":"2026-08-16T10:12:42.463018Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.13189","last_updated":"2025-02-18T14:06:05Z","snapshot_observed_at":"2026-08-12T19:30:23.025771Z","submitted_at":"2025-02-18T14:06:05Z","title":"MoBA: Mixture of Block Attention for Long-Context LLMs","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.13189","snapshot_observed_at":"2026-08-16T10:12:42.467340Z","title":"Zhang, Zhilin Yang, Xinyu Zhou, Mingxing Zhang, and Jiezhong Qiu","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2504.18857","last_updated":"2025-04-26T08:46:10Z","snapshot_observed_at":"2026-08-17T00:01:03.539955Z","submitted_at":"2025-04-26T08:46:10Z","title":"Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-16T10:12:42.467340Z"},"links":{"cited_paper":"/paper/2502.13189","citing_paper":"/paper/2504.18857"},"observation_digest":"sha256:af74c10de8a6f2dbbc56dc7d4cc678ffbc92a2bf3df62572f7aaa94007a3605d","observation_id":"f726a072-3d49-4988-802a-ee11de44a5d0","resolution":{"observed_at":"2026-08-16T10:12:42.467340Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.12181","last_updated":"2024-09-23T14:39:07Z","snapshot_observed_at":"2026-08-16T13:17:24.768319Z","submitted_at":"2024-09-18T17:53:17Z","title":"A Controlled Study on Long Context Extension and Generalization in LLMs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.12181","snapshot_observed_at":"2026-08-16T10:12:42.471651Z","title":"Chiu, Siyu Ren, Fei Yuan, Wenting Zhao, Zhiyong Wu, and Alexander M","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.18857","last_updated":"2025-04-26T08:46:10Z","snapshot_observed_at":"2026-08-17T00:01:03.539955Z","submitted_at":"2025-04-26T08:46:10Z","title":"Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-16T10:12:42.471651Z"},"links":{"cited_paper":"/paper/2409.12181","citing_paper":"/paper/2504.18857"},"observation_digest":"sha256:4513a94e94d71c515b954af6a3e15d4fc38ec2d9b12bd231b104287dabeca8f6","observation_id":"329f6e91-48d9-4910-bc69-8f86c807b784","resolution":{"observed_at":"2026-08-16T10:12:42.471651Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.10685","last_updated":"2024-03-25T11:50:32Z","snapshot_observed_at":"2026-08-16T18:41:56.650989Z","submitted_at":"2024-02-16T13:39:34Z","title":"LongHeads: Multi-Head Attention is Secretly a Long Context Processor","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.10685","snapshot_observed_at":"2026-08-16T10:12:42.477713Z","title":"Longheads: Multi-head attention is secretly a long context processor","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.18857","last_updated":"2025-04-26T08:46:10Z","snapshot_observed_at":"2026-08-17T00:01:03.539955Z","submitted_at":"2025-04-26T08:46:10Z","title":"Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation","version":1},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-16T10:12:42.477713Z"},"links":{"cited_paper":"/paper/2402.10685","citing_paper":"/paper/2504.18857"},"observation_digest":"sha256:fa3c3904b652d7200c03f3f45ce1f74ff8d8585c51dcb9a92530c7cb151985df","observation_id":"e6d73cbd-b5c9-47a4-9098-5dbfaa4947a3","resolution":{"observed_at":"2026-08-16T10:12:42.477713Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:42.482113Z","title":"Learning to reason with llms, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.18857","last_updated":"2025-04-26T08:46:10Z","snapshot_observed_at":"2026-08-17T00:01:03.539955Z","submitted_at":"2025-04-26T08:46:10Z","title":"Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-16T10:12:42.482113Z"},"links":{"citing_paper":"/paper/2504.18857"},"observation_digest":"sha256:bc2c560167fada3a9b856ff24f15fd72d4d2bbb2e7653a0b7dcaa124aef15280","observation_id":"c0210d34-5ff6-47f3-b8db-7670e6dc0db4","resolution":{"observed_at":"2026-08-16T10:12:42.482113Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:42.486358Z","title":"Yarn: Efficient context window extension of large language models, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2504.18857","last_updated":"2025-04-26T08:46:10Z","snapshot_observed_at":"2026-08-17T00:01:03.539955Z","submitted_at":"2025-04-26T08:46:10Z","title":"Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-16T10:12:42.486358Z"},"links":{"citing_paper":"/paper/2504.18857"},"observation_digest":"sha256:c37efe8ae5dbbb756469ac79643b74510bcaa2ac24e2191d354d004d31ee7ebd","observation_id":"07b32765-411c-46e1-8205-0775921429d5","resolution":{"observed_at":"2026-08-16T10:12:42.486358Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.15115","last_updated":"2025-01-03T02:18:21Z","snapshot_observed_at":"2026-08-17T18:50:07.059564Z","submitted_at":"2024-12-19T17:56:09Z","title":"Qwen2.5 Technical Report","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.15115","snapshot_observed_at":"2026-08-16T10:12:42.490362Z","title":"Qwen2.5 technical report, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2504.18857","last_updated":"2025-04-26T08:46:10Z","snapshot_observed_at":"2026-08-17T00:01:03.539955Z","submitted_at":"2025-04-26T08:46:10Z","title":"Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation","version":1},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-16T10:12:42.490362Z"},"links":{"cited_paper":"/paper/2412.15115","citing_paper":"/paper/2504.18857"},"observation_digest":"sha256:265316d47a411270894872bbfda6401a257ec55b2bbfb5e4f2c6db1def6cb1f6","observation_id":"6f810eab-bc82-4f5c-bd46-dca2bc29b0b3","resolution":{"observed_at":"2026-08-16T10:12:42.490362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:42.494444Z","title":"Rae, Anna Potapenko, Siddhant M","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2504.18857","last_updated":"2025-04-26T08:46:10Z","snapshot_observed_at":"2026-08-17T00:01:03.539955Z","submitted_at":"2025-04-26T08:46:10Z","title":"Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation","version":1},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-16T10:12:42.494444Z"},"links":{"citing_paper":"/paper/2504.18857"},"observation_digest":"sha256:ff4b3892fbbe2510029eb49dfc9e4d21e0d73194352bdb0953be06fe3551bb39","observation_id":"792b28a0-dffa-4943-9593-6a7eef285e40","resolution":{"observed_at":"2026-08-16T10:12:42.494444Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:43.162167Z","title":"Rectified rotary position embeddings","venue":null,"work_id":"a061f148-3f33-41f1-96ab-f5339cc40a54","year":2023},"citing_paper":{"arxiv_id":"2504.18857","last_updated":"2025-04-26T08:46:10Z","snapshot_observed_at":"2026-08-17T00:01:03.539955Z","submitted_at":"2025-04-26T08:46:10Z","title":"Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-16T10:12:42.498579Z"},"links":{"citing_paper":"/paper/2504.18857"},"observation_digest":"sha256:48e3371ea24c7baf570f2f9204f5176dbd7fafe7fbd56288a78ba497bbb82af3","observation_id":"63db74f9-daeb-41d9-a7dd-a489301da04d","resolution":{"observed_at":"2026-08-16T10:12:43.166455Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:43.148248Z","title":"Roformer: Enhanced transformer with rotary position embedding","venue":null,"work_id":"8cc9cfcd-9d51-4ce7-9ab3-55ed9e0b8fc2","year":2021},"citing_paper":{"arxiv_id":"2504.18857","last_updated":"2025-04-26T08:46:10Z","snapshot_observed_at":"2026-08-17T00:01:03.539955Z","submitted_at":"2025-04-26T08:46:10Z","title":"Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation","version":1},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-16T10:12:42.502584Z"},"links":{"citing_paper":"/paper/2504.18857"},"observation_digest":"sha256:055b76bfc1b22caf4e1e72cb2367fe39137f2db458c6d95985c033536f97d038","observation_id":"0c3c1e17-384f-451c-967e-a9f48df6260c","resolution":{"observed_at":"2026-08-16T10:12:43.152505Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:42.506304Z","title":"Roformer: Enhanced transformer with rotary position embedding","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.18857","last_updated":"2025-04-26T08:46:10Z","snapshot_observed_at":"2026-08-17T00:01:03.539955Z","submitted_at":"2025-04-26T08:46:10Z","title":"Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation","version":1},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-16T10:12:42.506304Z"},"links":{"citing_paper":"/paper/2504.18857"},"observation_digest":"sha256:056669e527cc2186153dcf92bd1dbc1b1ea0f45e533ba3b8bda8df6b45533c4d","observation_id":"dfc18e16-2838-49b2-a324-37425d3b31d9","resolution":{"observed_at":"2026-08-16T10:12:42.506304Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:42.510452Z","title":"Attention is all you need","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2504.18857","last_updated":"2025-04-26T08:46:10Z","snapshot_observed_at":"2026-08-17T00:01:03.539955Z","submitted_at":"2025-04-26T08:46:10Z","title":"Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation","version":1},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-16T10:12:42.510452Z"},"links":{"citing_paper":"/paper/2504.18857"},"observation_digest":"sha256:6936158c419931ae202bb63c34571d504bd36f2810181bd72a872c584d1230c2","observation_id":"1ac0a85f-adb1-4743-8123-2c145d131f5c","resolution":{"observed_at":"2026-08-16T10:12:42.510452Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.04617","last_updated":"2024-05-28T12:05:12Z","snapshot_observed_at":"2026-08-16T14:20:44.078187Z","submitted_at":"2024-02-07T06:50:42Z","title":"InfLLM: Training-Free Long-Context Extrapolation for LLMs with an Efficient Context Memory","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.04617","snapshot_observed_at":"2026-08-16T10:12:42.514460Z","title":"Infllm: Unveiling the intrinsic capacity of llms for understanding extremely long sequences with training-free memory","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.18857","last_updated":"2025-04-26T08:46:10Z","snapshot_observed_at":"2026-08-17T00:01:03.539955Z","submitted_at":"2025-04-26T08:46:10Z","title":"Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation","version":1},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-16T10:12:42.514460Z"},"links":{"cited_paper":"/paper/2402.04617","citing_paper":"/paper/2504.18857"},"observation_digest":"sha256:70b08f5c0007e981849990a676648d9780ec5c691cbe937561202205b2d159a1","observation_id":"217f177c-89fe-47ce-be45-88682d1fd1ef","resolution":{"observed_at":"2026-08-16T10:12:42.514460Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:42.518720Z","title":"Efficient streaming language models with attention sinks, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2504.18857","last_updated":"2025-04-26T08:46:10Z","snapshot_observed_at":"2026-08-17T00:01:03.539955Z","submitted_at":"2025-04-26T08:46:10Z","title":"Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation","version":1},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-16T10:12:42.518720Z"},"links":{"citing_paper":"/paper/2504.18857"},"observation_digest":"sha256:0a91c8db27089203764428187bfc0fa1691298f4ec5fcd655c1d644d16c4dcba","observation_id":"8289a1a4-5a13-432d-9ae3-d14ad6e2e4c1","resolution":{"observed_at":"2026-08-16T10:12:42.518720Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:43.102135Z","title":"Efficient streaming language models with attention sinks, 2024 b","venue":null,"work_id":"e686d165-4c58-4775-9b88-5bc27a4dc0dd","year":2024},"citing_paper":{"arxiv_id":"2504.18857","last_updated":"2025-04-26T08:46:10Z","snapshot_observed_at":"2026-08-17T00:01:03.539955Z","submitted_at":"2025-04-26T08:46:10Z","title":"Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation","version":1},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-16T10:12:42.522701Z"},"links":{"citing_paper":"/paper/2504.18857"},"observation_digest":"sha256:be3b9f5175d970de6570289028d75d8f0a165e18bd220d009108a5d6e1af0abb","observation_id":"5b717c0d-3082-47ba-8a10-8fc05d96b389","resolution":{"observed_at":"2026-08-16T10:12:43.108736Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2309.16039","last_updated":"2023-11-14T01:40:13Z","snapshot_observed_at":"2026-08-16T14:57:02.846476Z","submitted_at":"2023-09-27T21:41:49Z","title":"Effective Long-Context Scaling of Foundation Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.16039","snapshot_observed_at":"2026-08-16T10:12:42.526808Z","title":"Effective long-context scaling of foundation models, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2504.18857","last_updated":"2025-04-26T08:46:10Z","snapshot_observed_at":"2026-08-17T00:01:03.539955Z","submitted_at":"2025-04-26T08:46:10Z","title":"Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation","version":1},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-16T10:12:42.526808Z"},"links":{"cited_paper":"/paper/2309.16039","citing_paper":"/paper/2504.18857"},"observation_digest":"sha256:6fda5adac95b60b7224cfc6de51fbbea74d63e5912b7f40b3695e1ea444284b5","observation_id":"8184d268-409a-4886-a8b4-19829f700d2e","resolution":{"observed_at":"2026-08-16T10:12:42.526808Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.02694","last_updated":"2025-03-06T18:41:54Z","snapshot_observed_at":"2026-08-16T21:34:35.394829Z","submitted_at":"2024-10-03T17:20:11Z","title":"HELMET: How to Evaluate Long-Context Language Models Effectively and Thoroughly","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.02694","snapshot_observed_at":"2026-08-16T10:12:42.531077Z","title":"Helmet: How to evaluate long-context language models effectively and thoroughly, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2504.18857","last_updated":"2025-04-26T08:46:10Z","snapshot_observed_at":"2026-08-17T00:01:03.539955Z","submitted_at":"2025-04-26T08:46:10Z","title":"Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation","version":1},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-08-16T10:12:42.531077Z"},"links":{"cited_paper":"/paper/2410.02694","citing_paper":"/paper/2504.18857"},"observation_digest":"sha256:95bcb56457ff9927525f8f4467ecd757bb599154cd012f2c0b6687c4bd499840","observation_id":"55c2d31b-d0cb-416f-a028-47b72315e428","resolution":{"observed_at":"2026-08-16T10:12:42.531077Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.11089","last_updated":"2025-02-27T09:01:21Z","snapshot_observed_at":"2026-08-16T16:29:35.500686Z","submitted_at":"2025-02-16T11:53:44Z","title":"Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.11089","snapshot_observed_at":"2026-08-16T10:12:42.535523Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2504.18857","last_updated":"2025-04-26T08:46:10Z","snapshot_observed_at":"2026-08-17T00:01:03.539955Z","submitted_at":"2025-04-26T08:46:10Z","title":"Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation","version":1},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-08-16T10:12:42.535523Z"},"links":{"cited_paper":"/paper/2502.11089","citing_paper":"/paper/2504.18857"},"observation_digest":"sha256:0609d37b8363a7432779b745c7a8b6ab2c32f4ec8b191135c1edd4af345f0744","observation_id":"72f9bd0a-50e7-41c6-b46f-1c61cc23fe39","resolution":{"observed_at":"2026-08-16T10:12:42.535523Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.12226","last_updated":"2025-09-08T07:04:17Z","snapshot_observed_at":"2026-08-16T14:17:18.108855Z","submitted_at":"2024-02-19T15:33:10Z","title":"AnyGPT: Unified Multimodal LLM with Discrete Sequence Modeling","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.12226","snapshot_observed_at":"2026-08-16T10:12:42.539584Z","title":"Anygpt: Unified multimodal llm with discrete sequence modeling, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.18857","last_updated":"2025-04-26T08:46:10Z","snapshot_observed_at":"2026-08-17T00:01:03.539955Z","submitted_at":"2025-04-26T08:46:10Z","title":"Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation","version":1},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-16T10:12:42.539584Z"},"links":{"cited_paper":"/paper/2402.12226","citing_paper":"/paper/2504.18857"},"observation_digest":"sha256:609f73a1953e7bfe84d57aab572cff52c361ae044d9643c0b7eac1cfb04e3795","observation_id":"39b10e82-740e-4244-9e2c-2e6846d08f3f","resolution":{"observed_at":"2026-08-16T10:12:42.539584Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.19115","last_updated":"2024-08-09T06:15:19Z","snapshot_observed_at":"2026-08-16T14:05:42.140546Z","submitted_at":"2024-03-28T03:11:38Z","title":"HiRoPE: Length Extrapolation for Code Models Using Hierarchical Position","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.19115","snapshot_observed_at":"2026-08-16T10:12:42.543716Z","title":"Hirope: Length extrapolation for code models using hierarchical position, 2024 a","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.18857","last_updated":"2025-04-26T08:46:10Z","snapshot_observed_at":"2026-08-17T00:01:03.539955Z","submitted_at":"2025-04-26T08:46:10Z","title":"Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation","version":1},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-08-16T10:12:42.543716Z"},"links":{"cited_paper":"/paper/2403.19115","citing_paper":"/paper/2504.18857"},"observation_digest":"sha256:2d67261cd03a0b64c8b5f41a71f3e285e49160ecca7cac457c54cd49f9514650","observation_id":"41c9c7cd-53ed-4a78-a32f-a4f30608091d","resolution":{"observed_at":"2026-08-16T10:12:42.543716Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.13718","last_updated":"2024-02-24T15:07:55Z","snapshot_observed_at":"2026-08-16T14:16:38.556803Z","submitted_at":"2024-02-21T11:30:29Z","title":"$\\infty$Bench: Extending Long Context Evaluation Beyond 100K Tokens","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.13718","snapshot_observed_at":"2026-08-16T10:12:42.548152Z","title":"bench: Extending long context evaluation beyond 100k tokens, 2024 b","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.18857","last_updated":"2025-04-26T08:46:10Z","snapshot_observed_at":"2026-08-17T00:01:03.539955Z","submitted_at":"2025-04-26T08:46:10Z","title":"Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation","version":1},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-08-16T10:12:42.548152Z"},"links":{"cited_paper":"/paper/2402.13718","citing_paper":"/paper/2504.18857"},"observation_digest":"sha256:195af3985f9beee2d04a504306e162a3c4d1d1c985e2f81795a337b2754a9984","observation_id":"fe77aa27-9888-4509-bd27-f504197bea84","resolution":{"observed_at":"2026-08-16T10:12:42.548152Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:42.552327Z","title":"@esa (Ref","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2504.18857","last_updated":"2025-04-26T08:46:10Z","snapshot_observed_at":"2026-08-17T00:01:03.539955Z","submitted_at":"2025-04-26T08:46:10Z","title":"Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation","version":1},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-08-16T10:12:42.552327Z"},"links":{"citing_paper":"/paper/2504.18857"},"observation_digest":"sha256:390b16dbf00ac5353da449f0988de3e3ac7688ec05087591a5c0a244761886e3","observation_id":"328a62cf-8d92-4c77-890b-80f22fe14004","resolution":{"observed_at":"2026-08-16T10:12:42.552327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:42.556599Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2504.18857","last_updated":"2025-04-26T08:46:10Z","snapshot_observed_at":"2026-08-17T00:01:03.539955Z","submitted_at":"2025-04-26T08:46:10Z","title":"Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation","version":1},"reference_index":49,"source":"arxiv_source","source_observed_at":"2026-08-16T10:12:42.556599Z"},"links":{"citing_paper":"/paper/2504.18857"},"observation_digest":"sha256:87c922bb621cb0676270f4a227280997d65819c3847911b8da9792f33e524fa8","observation_id":"ea97e65b-14cd-4d34-808d-c93abcd269b1","resolution":{"observed_at":"2026-08-16T10:12:42.556599Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2005.14165","last_updated":"2020-07-22T19:47:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2020-05-28T17:29:03Z","title":"Language Models are Few-Shot Learners","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2005.14165","snapshot_observed_at":"2026-08-16T10:12:42.560499Z","title":"https://www.reddit.com/r/LocalLLaMA/comments/14lz7j5/ntkaware_scaled_rope_allows_llama_models_to_have/","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2504.18857","last_updated":"2025-04-26T08:46:10Z","snapshot_observed_at":"2026-08-17T00:01:03.539955Z","submitted_at":"2025-04-26T08:46:10Z","title":"Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation","version":1},"reference_index":50,"source":"arxiv_source","source_observed_at":"2026-08-16T10:12:42.560499Z"},"links":{"cited_paper":"/paper/2005.14165","citing_paper":"/paper/2504.18857"},"observation_digest":"sha256:c24f52df2c9aca60a4bc27fb0ed4e5ea03aa5a603c211abb1b690b7397413fbf","observation_id":"08c2d335-f43a-4c69-adc8-45a8241267fb","resolution":{"observed_at":"2026-08-16T10:12:42.560499Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2504.18857","last_updated":"2025-04-26T08:46:10Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-17T00:01:03.539955Z","submitted_at":"2025-04-26T08:46:10Z","title":"Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation"},"reference_resolution":{"displayed":49,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":38,"verified_exact":0,"verified_fuzzy":11},"total_outbound_references":49},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 0 inbound Pith citation observations for arXiv:2504.18857."}