{"as_of":"2026-08-14T17:07:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:8a8c3605f87a0ca8f956a66544963e3fc557b4ff87ef9446cc54694e3d654e81","coverage":[{"denominator":36,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":36,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T15:42:23.582268Z","state":"measured"},{"denominator":36,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":36,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-14T06:32:32.682623+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/2505.14085/citation-record","integrity":"/paper/2505.14085/integrity","json":"/paper/2505.14085/citation-record.json","paper":"/paper/2505.14085"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:42:19.945014Z","title":"6g wireless communication systems: Applications, requirements, technolo- gies, challenges, and research directions,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2505.14085","last_updated":"2025-05-20T08:46:23Z","snapshot_observed_at":"2026-08-12T20:33:35.976987Z","submitted_at":"2025-05-20T08:46:23Z","title":"CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:19.945014Z"},"links":{"citing_paper":"/paper/2505.14085"},"observation_digest":"sha256:6d539f8df6291aef6f37796ac6c40552c899481aefa64dffebe012661edb2caf","observation_id":"c86273b6-479b-4f88-b177-5d17cecd19d0","resolution":{"observed_at":"2026-08-07T15:42:19.945014Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2004.14247","last_updated":"2020-04-29T14:52:32Z","snapshot_observed_at":"2026-08-07T12:20:36.473792Z","submitted_at":"2020-04-29T14:52:32Z","title":"White Paper on Broadband Connectivity in 6G","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2004.14247","snapshot_observed_at":"2026-08-07T15:42:20.110811Z","title":"White paper on broadband connectivity in 6g,","venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"2505.14085","last_updated":"2025-05-20T08:46:23Z","snapshot_observed_at":"2026-08-12T20:33:35.976987Z","submitted_at":"2025-05-20T08:46:23Z","title":"CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:20.110811Z"},"links":{"cited_paper":"/paper/2004.14247","citing_paper":"/paper/2505.14085"},"observation_digest":"sha256:c902621e0ec13ce9fb69ccad2470172dd1d5ae7ab18420f6fa3b879e16437e1f","observation_id":"3a715e3e-690f-4f32-997b-9cf3b6109eb0","resolution":{"observed_at":"2026-08-07T15:42:20.110811Z","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":"2026-08-07T15:42:26.097842Z","title":"Ai-native network slicing for 6g networks,","venue":null,"work_id":"313da58d-f2e0-421f-b886-2117aea2ac61","year":2022},"citing_paper":{"arxiv_id":"2505.14085","last_updated":"2025-05-20T08:46:23Z","snapshot_observed_at":"2026-08-12T20:33:35.976987Z","submitted_at":"2025-05-20T08:46:23Z","title":"CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:20.265390Z"},"links":{"citing_paper":"/paper/2505.14085"},"observation_digest":"sha256:4a0c1957d92d1bad505eead846dd193a3e645a3bd8481aea09c2603eac555ecf","observation_id":"11bedb4e-9721-4d3d-ab78-bd7c0e58505f","resolution":{"observed_at":"2026-08-07T15:42:26.152214Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-07T15:42:25.975053Z","title":"Towards 6g wireless communication networks: Vision, enabling technologies, and new paradigm shifts,","venue":null,"work_id":"3d14ec74-8d0d-463e-9910-80e92269ad14","year":2021},"citing_paper":{"arxiv_id":"2505.14085","last_updated":"2025-05-20T08:46:23Z","snapshot_observed_at":"2026-08-12T20:33:35.976987Z","submitted_at":"2025-05-20T08:46:23Z","title":"CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:20.403688Z"},"links":{"citing_paper":"/paper/2505.14085"},"observation_digest":"sha256:8a7f655aa46e46d29919b7dd28fd27859123e0d08acbba0fec664a663b665df9","observation_id":"8ae12871-c2b9-44fc-a741-3ef16b254497","resolution":{"observed_at":"2026-08-07T15:42:26.033118Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-07T15:42:25.838778Z","title":"Optimizing llm inference clusters for enhanced performance and energy efficiency,","venue":null,"work_id":"51fa7300-4106-4133-926a-2bc862e7cdba","year":2024},"citing_paper":{"arxiv_id":"2505.14085","last_updated":"2025-05-20T08:46:23Z","snapshot_observed_at":"2026-08-12T20:33:35.976987Z","submitted_at":"2025-05-20T08:46:23Z","title":"CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:20.554930Z"},"links":{"citing_paper":"/paper/2505.14085"},"observation_digest":"sha256:98c34a77356832f55880e6c4514e225adeddb65ee13fe22a6285d159a98e2fc6","observation_id":"3aaa0cb3-ba2d-4600-bde1-edcc9012da77","resolution":{"observed_at":"2026-08-07T15:42:25.898092Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-07T15:42:25.697559Z","title":"Performance modeling and workload analysis of dis- tributed large language model training and inference,","venue":null,"work_id":"1ac979c2-b707-46f8-b425-8e74bfc5b83a","year":2024},"citing_paper":{"arxiv_id":"2505.14085","last_updated":"2025-05-20T08:46:23Z","snapshot_observed_at":"2026-08-12T20:33:35.976987Z","submitted_at":"2025-05-20T08:46:23Z","title":"CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:20.647476Z"},"links":{"citing_paper":"/paper/2505.14085"},"observation_digest":"sha256:f5f9c0bfa4eb06a0b5e3343578b3429b9fc4197862a74ac5c38e4ce0470485d5","observation_id":"baca5998-54b7-4d72-ad0a-dd51c56179a4","resolution":{"observed_at":"2026-08-07T15:42:25.769395Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-07T15:42:25.556505Z","title":"Deepspeed: System optimizations enable training deep learning models with over 100 billion parameters,","venue":null,"work_id":"99038d1e-a1a9-47cf-855d-2c9246606105","year":2020},"citing_paper":{"arxiv_id":"2505.14085","last_updated":"2025-05-20T08:46:23Z","snapshot_observed_at":"2026-08-12T20:33:35.976987Z","submitted_at":"2025-05-20T08:46:23Z","title":"CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:20.736238Z"},"links":{"citing_paper":"/paper/2505.14085"},"observation_digest":"sha256:e1b47fb596f75aaad29621ae8557c3df07e74e33e0fe19308f33688c1d5cc656","observation_id":"171f39d0-57f8-4d81-b5ed-c4e50d2e374b","resolution":{"observed_at":"2026-08-07T15:42:25.614564Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-07T15:42:20.837495Z","title":"Reducing activation recomputation in large transformer models,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.14085","last_updated":"2025-05-20T08:46:23Z","snapshot_observed_at":"2026-08-12T20:33:35.976987Z","submitted_at":"2025-05-20T08:46:23Z","title":"CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:20.837495Z"},"links":{"citing_paper":"/paper/2505.14085"},"observation_digest":"sha256:aecb9245796f92ccadb2a98ab21bfd338a9f9f742e93b7c17576baf30a22ca61","observation_id":"3cffd5d7-2ef3-4502-84bf-5bfca4a043d6","resolution":{"observed_at":"2026-08-07T15:42:20.837495Z","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":"2026-08-07T15:42:20.925708Z","title":"Efficient large-scale language model training on gpu clusters using megatron-lm,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2505.14085","last_updated":"2025-05-20T08:46:23Z","snapshot_observed_at":"2026-08-12T20:33:35.976987Z","submitted_at":"2025-05-20T08:46:23Z","title":"CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:20.925708Z"},"links":{"citing_paper":"/paper/2505.14085"},"observation_digest":"sha256:8e5d78f79a1103dc98c2890b851df12c6c7d9137fc829e26eca05426b8606f8f","observation_id":"f5aed8f0-a8e7-435c-8072-a37046d6fe4c","resolution":{"observed_at":"2026-08-07T15:42:20.925708Z","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":"2026-08-07T15:42:21.025575Z","title":"Efficient memory management for large language model serving with pagedattention,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.14085","last_updated":"2025-05-20T08:46:23Z","snapshot_observed_at":"2026-08-12T20:33:35.976987Z","submitted_at":"2025-05-20T08:46:23Z","title":"CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:21.025575Z"},"links":{"citing_paper":"/paper/2505.14085"},"observation_digest":"sha256:a39a10109fee4f3eb1da2a84e494e76b2f3b668e17baa5644bda06f2d9d77932","observation_id":"2252d4ab-9b9f-4f5d-ab01-f409ad64ac1e","resolution":{"observed_at":"2026-08-07T15:42:21.025575Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.14808","last_updated":"2024-05-30T05:09:25Z","snapshot_observed_at":"2026-08-13T04:12:37.012194Z","submitted_at":"2024-02-22T18:58:28Z","title":"RelayAttention for Efficient Large Language Model Serving with Long System Prompts","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.14808","snapshot_observed_at":"2026-08-07T15:42:21.128740Z","title":"Relayattention for efficient large language model serving with long system prompts,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.14085","last_updated":"2025-05-20T08:46:23Z","snapshot_observed_at":"2026-08-12T20:33:35.976987Z","submitted_at":"2025-05-20T08:46:23Z","title":"CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:21.128740Z"},"links":{"cited_paper":"/paper/2402.14808","citing_paper":"/paper/2505.14085"},"observation_digest":"sha256:a4d47fa99c9142f52df19c945c7df9404461123aeb9ffe3905c95041ae826c48","observation_id":"83d66fd5-4371-4bd0-b743-0b6af6ac3726","resolution":{"observed_at":"2026-08-07T15:42:21.128740Z","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":"2026-08-07T15:42:25.395460Z","title":"Prompt cache: Modular attention reuse for low-latency inference,","venue":null,"work_id":"d62e98b5-9b14-486d-9218-87a4525c36ed","year":2024},"citing_paper":{"arxiv_id":"2505.14085","last_updated":"2025-05-20T08:46:23Z","snapshot_observed_at":"2026-08-12T20:33:35.976987Z","submitted_at":"2025-05-20T08:46:23Z","title":"CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:21.231655Z"},"links":{"citing_paper":"/paper/2505.14085"},"observation_digest":"sha256:08a884150af77e9824e2957dbde823ce5a3175a8a52e6329de1b8af91c204758","observation_id":"4db954af-3db0-403d-8890-0f273a857ee4","resolution":{"observed_at":"2026-08-07T15:42:25.454317Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-07T15:42:25.252640Z","title":"Model pruning enables efficient federated learning on edge devices,","venue":null,"work_id":"69b8f95f-76e4-4a30-87a3-7de5d43f0f34","year":2022},"citing_paper":{"arxiv_id":"2505.14085","last_updated":"2025-05-20T08:46:23Z","snapshot_observed_at":"2026-08-12T20:33:35.976987Z","submitted_at":"2025-05-20T08:46:23Z","title":"CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:21.339035Z"},"links":{"citing_paper":"/paper/2505.14085"},"observation_digest":"sha256:5f2f64719626ab74296b4b3bd44b8233fd44c64a6e265663e02be99709033d9b","observation_id":"ece9a834-b1c9-4f7d-a5cb-c5cd559267ec","resolution":{"observed_at":"2026-08-07T15:42:25.318794Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.15758","last_updated":"2024-06-22T06:51:47Z","snapshot_observed_at":"2026-08-12T23:37:05.407757Z","submitted_at":"2024-06-22T06:51:47Z","title":"EDGE-LLM: Enabling Efficient Large Language Model Adaptation on Edge Devices via Layerwise Unified Compression and Adaptive Layer Tuning and Voting","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.15758","snapshot_observed_at":"2026-08-07T15:42:21.452363Z","title":"Edge-llm: Enabling efficient large language model adaptation on edge devices via layerwise unified compression and adaptive layer tuning and voting,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.14085","last_updated":"2025-05-20T08:46:23Z","snapshot_observed_at":"2026-08-12T20:33:35.976987Z","submitted_at":"2025-05-20T08:46:23Z","title":"CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:21.452363Z"},"links":{"cited_paper":"/paper/2406.15758","citing_paper":"/paper/2505.14085"},"observation_digest":"sha256:ba7071e1f020a1e8cc700e9216d3067e12b749f97e70ae3b830b9a74fec84868","observation_id":"94330cc7-8d05-49a8-8d41-dbe980d5b3e6","resolution":{"observed_at":"2026-08-07T15:42:21.452363Z","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":"2026-08-07T15:42:25.126455Z","title":"Optimizing mobile-edge ai-generated everything (aigx) services by prompt engineering: Fundamental, framework, and case study,","venue":null,"work_id":"3f5aba15-c49c-4f7c-a0dd-d8c427a01a3e","year":2023},"citing_paper":{"arxiv_id":"2505.14085","last_updated":"2025-05-20T08:46:23Z","snapshot_observed_at":"2026-08-12T20:33:35.976987Z","submitted_at":"2025-05-20T08:46:23Z","title":"CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:21.553679Z"},"links":{"citing_paper":"/paper/2505.14085"},"observation_digest":"sha256:74dfe775d19b6d1173b4d20c7e2474dc6fc2bcfc522534089f1f967bd360b229","observation_id":"5614e127-983e-4639-b28f-1dc4facfd617","resolution":{"observed_at":"2026-08-07T15:42:25.167837Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2411.02829","last_updated":"2025-06-08T00:57:21Z","snapshot_observed_at":"2026-08-14T15:18:10.240510Z","submitted_at":"2024-11-05T06:00:27Z","title":"CE-CoLLM: Efficient and Adaptive Large Language Models Through Cloud-Edge Collaboration","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.02829","snapshot_observed_at":"2026-08-07T15:42:21.669588Z","title":"Ce-collm: Efficient and adaptive large language mod- els through cloud-edge collaboration,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.14085","last_updated":"2025-05-20T08:46:23Z","snapshot_observed_at":"2026-08-12T20:33:35.976987Z","submitted_at":"2025-05-20T08:46:23Z","title":"CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:21.669588Z"},"links":{"cited_paper":"/paper/2411.02829","citing_paper":"/paper/2505.14085"},"observation_digest":"sha256:c65176d16e9ec3d2e6a62a56ae8907e24bc17f575f045c7672f16e3ca9b7d868","observation_id":"9d0856ff-9b02-4b2d-80a0-05f524d75af0","resolution":{"observed_at":"2026-08-07T15:42:21.669588Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.02669","last_updated":"2024-07-04T15:12:54Z","snapshot_observed_at":"2026-08-13T04:48:37.453735Z","submitted_at":"2024-01-05T06:53:00Z","title":"Infinite-LLM: Efficient LLM Service for Long Context with DistAttention and Distributed KVCache","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.02669","snapshot_observed_at":"2026-08-07T15:42:21.786114Z","title":"Infinite-llm: Efficient llm service for long context with distattention and distributed kvcache,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.14085","last_updated":"2025-05-20T08:46:23Z","snapshot_observed_at":"2026-08-12T20:33:35.976987Z","submitted_at":"2025-05-20T08:46:23Z","title":"CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:21.786114Z"},"links":{"cited_paper":"/paper/2401.02669","citing_paper":"/paper/2505.14085"},"observation_digest":"sha256:891a921e0827fe0b925a152718aa1568b271cd67d7e5bcad627e456752618339","observation_id":"c6e991f7-3307-4c1a-9155-e0b38881e6c1","resolution":{"observed_at":"2026-08-07T15:42:21.786114Z","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":"2026-08-07T15:42:21.863335Z","title":"Zero: Memory optimizations toward training trillion parameter models,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2505.14085","last_updated":"2025-05-20T08:46:23Z","snapshot_observed_at":"2026-08-12T20:33:35.976987Z","submitted_at":"2025-05-20T08:46:23Z","title":"CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:21.863335Z"},"links":{"citing_paper":"/paper/2505.14085"},"observation_digest":"sha256:676626a43fcad1fdd0de8212c08430189380ce5e85fc9111420a2b9e8431380b","observation_id":"e009fbe8-b573-4466-92ef-600fb12c5026","resolution":{"observed_at":"2026-08-07T15:42:21.863335Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.11627","last_updated":"2023-09-28T03:59:27Z","snapshot_observed_at":"2026-08-13T11:38:48.514086Z","submitted_at":"2023-05-19T12:10:53Z","title":"LLM-Pruner: On the Structural Pruning of Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.11627","snapshot_observed_at":"2026-08-07T15:42:21.943627Z","title":"Llm-pruner: On the structural pruning of large language models,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.14085","last_updated":"2025-05-20T08:46:23Z","snapshot_observed_at":"2026-08-12T20:33:35.976987Z","submitted_at":"2025-05-20T08:46:23Z","title":"CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:21.943627Z"},"links":{"cited_paper":"/paper/2305.11627","citing_paper":"/paper/2505.14085"},"observation_digest":"sha256:b0a22c083689f95eed70668370b9e1fed61b2edf5016b27f22b077a83a750e53","observation_id":"6b6e9b1d-0818-485e-b782-db74ee69e692","resolution":{"observed_at":"2026-08-07T15:42:21.943627Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2301.00774","last_updated":"2023-03-22T12:33:46Z","snapshot_observed_at":"2026-08-13T13:10:46.067160Z","submitted_at":"2023-01-02T17:48:56Z","title":"SparseGPT: Massive Language Models Can Be Accurately Pruned in One-Shot","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2301.00774","snapshot_observed_at":"2026-08-07T15:42:22.002271Z","title":"Sparsegpt: Massive language models can be accurately pruned in one-shot,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.14085","last_updated":"2025-05-20T08:46:23Z","snapshot_observed_at":"2026-08-12T20:33:35.976987Z","submitted_at":"2025-05-20T08:46:23Z","title":"CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:22.002271Z"},"links":{"cited_paper":"/paper/2301.00774","citing_paper":"/paper/2505.14085"},"observation_digest":"sha256:b7a4ed2e29aef42855a340a441b86d188883d8a17a02622c5078c8c6a153087b","observation_id":"c59d05b9-46f2-4c8f-9be7-de32966817b3","resolution":{"observed_at":"2026-08-07T15:42:22.002271Z","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":"2026-08-07T15:42:22.098511Z","title":"Cachegen: Kv cache compression and streaming for fast large language model serving,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.14085","last_updated":"2025-05-20T08:46:23Z","snapshot_observed_at":"2026-08-12T20:33:35.976987Z","submitted_at":"2025-05-20T08:46:23Z","title":"CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:22.098511Z"},"links":{"citing_paper":"/paper/2505.14085"},"observation_digest":"sha256:03bc792bb2a499737f8867384bc85f8805515a2e74c8a8e627801c6798d26059","observation_id":"a5d6b63f-1400-4643-a2f9-df03bc2f9948","resolution":{"observed_at":"2026-08-07T15:42:22.098511Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.18517","last_updated":"2024-10-24T08:06:41Z","snapshot_observed_at":"2026-08-12T22:16:07.563966Z","submitted_at":"2024-10-24T08:06:41Z","title":"KVSharer: Efficient Inference via Layer-Wise Dissimilar KV Cache Sharing","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.18517","snapshot_observed_at":"2026-08-07T15:42:22.203859Z","title":"Kvsharer: Efficient inference via layer-wise dissimilar kv cache sharing,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.14085","last_updated":"2025-05-20T08:46:23Z","snapshot_observed_at":"2026-08-12T20:33:35.976987Z","submitted_at":"2025-05-20T08:46:23Z","title":"CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:22.203859Z"},"links":{"cited_paper":"/paper/2410.18517","citing_paper":"/paper/2505.14085"},"observation_digest":"sha256:614faa4e133f05cebabf896b56db47a6c944abd6c9b47b7aefb836172c7fbe82","observation_id":"cb0bdeff-ff8b-439d-9382-c80aa88a7e44","resolution":{"observed_at":"2026-08-07T15:42:22.203859Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.11550","last_updated":"2025-10-16T13:25:38Z","snapshot_observed_at":"2026-08-12T20:32:53.188699Z","submitted_at":"2024-07-16T09:53:32Z","title":"Ada-KV: Optimizing KV Cache Eviction by Adaptive Budget Allocation for Efficient LLM Inference","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.11550","snapshot_observed_at":"2026-08-07T15:42:22.280390Z","title":"Ada-kv: Optimizing kv cache eviction by adaptive budget allocation for efficient llm inference,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.14085","last_updated":"2025-05-20T08:46:23Z","snapshot_observed_at":"2026-08-12T20:33:35.976987Z","submitted_at":"2025-05-20T08:46:23Z","title":"CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:22.280390Z"},"links":{"cited_paper":"/paper/2407.11550","citing_paper":"/paper/2505.14085"},"observation_digest":"sha256:465ab9299618c356ac785f4c1973ebad175763a0daa6674060e34d5d9cef7b4f","observation_id":"9f5775f5-be36-4c5c-9531-eba11776302d","resolution":{"observed_at":"2026-08-07T15:42:22.280390Z","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":"2026-08-07T15:42:24.979832Z","title":"Model tells you what to discard: Adaptive kv cache compression for llms,","venue":null,"work_id":"f9a6eb9e-73e6-4a4b-8cc7-fcf118c48b6a","year":2023},"citing_paper":{"arxiv_id":"2505.14085","last_updated":"2025-05-20T08:46:23Z","snapshot_observed_at":"2026-08-12T20:33:35.976987Z","submitted_at":"2025-05-20T08:46:23Z","title":"CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:22.355802Z"},"links":{"citing_paper":"/paper/2505.14085"},"observation_digest":"sha256:256e89d2f2ed090141500e19e4854fc5868e2f1e4edf1d7e6d2980d1bb577189","observation_id":"cfcd4484-3cb2-4f0a-8378-cbbd363a2109","resolution":{"observed_at":"2026-08-07T15:42:25.041301Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-07T15:42:24.833893Z","title":"Netgpt: An ai-native network architecture for provisioning beyond personalized generative services,","venue":null,"work_id":"4a072089-1d66-4994-bd7f-a550b6e83d5d","year":2024},"citing_paper":{"arxiv_id":"2505.14085","last_updated":"2025-05-20T08:46:23Z","snapshot_observed_at":"2026-08-12T20:33:35.976987Z","submitted_at":"2025-05-20T08:46:23Z","title":"CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:22.452645Z"},"links":{"citing_paper":"/paper/2505.14085"},"observation_digest":"sha256:cfeff42dca36bb2690c4a55a0766fdc0a87157eb96c6a8e50f2a6612a6137b64","observation_id":"6d872b2c-9fbb-48cc-aec1-fa9723b252f4","resolution":{"observed_at":"2026-08-07T15:42:24.897865Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.03065","last_updated":"2025-02-20T23:28:01Z","snapshot_observed_at":"2026-08-12T22:31:08.153347Z","submitted_at":"2024-10-04T01:11:09Z","title":"Compute Or Load KV Cache? Why Not Both?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.03065","snapshot_observed_at":"2026-08-07T15:42:22.542928Z","title":"Compute or load kv cache? why not both?","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.14085","last_updated":"2025-05-20T08:46:23Z","snapshot_observed_at":"2026-08-12T20:33:35.976987Z","submitted_at":"2025-05-20T08:46:23Z","title":"CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:22.542928Z"},"links":{"cited_paper":"/paper/2410.03065","citing_paper":"/paper/2505.14085"},"observation_digest":"sha256:f73c5395b323e568c2decf10edb02868a6ffdbb05d7d8102873ca0f7dfd040d9","observation_id":"a974abcd-187d-46b9-9315-854d348d651f","resolution":{"observed_at":"2026-08-07T15:42:22.542928Z","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":"2026-08-07T15:42:24.661245Z","title":"{OSCA}: An{Online-Model}based cache allocation scheme in cloud block storage systems,","venue":null,"work_id":"f6483927-b4d4-47cf-b2c1-f3b4f6edba2a","year":2020},"citing_paper":{"arxiv_id":"2505.14085","last_updated":"2025-05-20T08:46:23Z","snapshot_observed_at":"2026-08-12T20:33:35.976987Z","submitted_at":"2025-05-20T08:46:23Z","title":"CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:22.623389Z"},"links":{"citing_paper":"/paper/2505.14085"},"observation_digest":"sha256:f733a571cb33bcc13a3687e7ba80fc47d8b35dc93f9fc5d3dcdb25b4aad1a058","observation_id":"d64e7a03-6e3a-4b0d-90ca-73cfd009e03b","resolution":{"observed_at":"2026-08-07T15:42:24.751323Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-07T15:42:22.690741Z","title":"Similarity of neural network models: A survey of functional and representational measures,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.14085","last_updated":"2025-05-20T08:46:23Z","snapshot_observed_at":"2026-08-12T20:33:35.976987Z","submitted_at":"2025-05-20T08:46:23Z","title":"CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:22.690741Z"},"links":{"citing_paper":"/paper/2505.14085"},"observation_digest":"sha256:dcdd5ebe2fce424023769b0c49481c175f4b7e845b7eeec5b7d11a8fa0be19a7","observation_id":"9278466e-630c-4ef2-beb6-d14d133d7670","resolution":{"observed_at":"2026-08-07T15:42:22.690741Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.21018","last_updated":"2025-02-27T12:30:43Z","snapshot_observed_at":"2026-08-12T23:11:48.101497Z","submitted_at":"2024-07-30T17:59:08Z","title":"ThinK: Thinner Key Cache by Query-Driven Pruning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.21018","snapshot_observed_at":"2026-08-07T15:42:22.978471Z","title":"Think: Thinner key cache by query-driven pruning,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.14085","last_updated":"2025-05-20T08:46:23Z","snapshot_observed_at":"2026-08-12T20:33:35.976987Z","submitted_at":"2025-05-20T08:46:23Z","title":"CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:22.978471Z"},"links":{"cited_paper":"/paper/2407.21018","citing_paper":"/paper/2505.14085"},"observation_digest":"sha256:b846084a85eef3e7be7f83ac0cb8d23d01a80cef29f6bb36a0bb70239aea3b61","observation_id":"2972a50a-33da-4f1c-a58f-be2f92ce2e4c","resolution":{"observed_at":"2026-08-07T15:42:22.978471Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.18223","last_updated":"2026-03-18T05:34:39Z","snapshot_observed_at":"2026-08-14T10:40:26.323157Z","submitted_at":"2023-03-31T17:28:46Z","title":"A Survey of Large Language Models","version":19},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.18223","snapshot_observed_at":"2026-08-07T15:42:23.082239Z","title":"A survey of large language models,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.14085","last_updated":"2025-05-20T08:46:23Z","snapshot_observed_at":"2026-08-12T20:33:35.976987Z","submitted_at":"2025-05-20T08:46:23Z","title":"CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:23.082239Z"},"links":{"cited_paper":"/paper/2303.18223","citing_paper":"/paper/2505.14085"},"observation_digest":"sha256:5390b58a8c968e4239e692500f582f556c16c52adcb3de5d155e403644dd3149","observation_id":"9f91f44f-fe55-4ee4-8225-5ed1061ea45e","resolution":{"observed_at":"2026-08-07T15:42:23.082239Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1808.08745","last_updated":"2018-08-27T09:08:18Z","snapshot_observed_at":"2026-07-06T06:57:36.335954Z","submitted_at":"2018-08-27T09:08:18Z","title":"Don't Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarization","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1808.08745","snapshot_observed_at":"2026-08-07T15:42:23.171221Z","title":"Don’t give me the details, just the summary! topic-aware convolutional neural networks for extreme summarization,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2505.14085","last_updated":"2025-05-20T08:46:23Z","snapshot_observed_at":"2026-08-12T20:33:35.976987Z","submitted_at":"2025-05-20T08:46:23Z","title":"CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:23.171221Z"},"links":{"cited_paper":"/paper/1808.08745","citing_paper":"/paper/2505.14085"},"observation_digest":"sha256:d7827f34c5f3669de2f10f20b5ccbc76c06e758557646adfb9f9dd4a3a39a2fb","observation_id":"f2d31dae-3178-4f20-bd3b-9b124471e737","resolution":{"observed_at":"2026-08-07T15:42:23.171221Z","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":"2026-08-07T15:42:24.471728Z","title":"Aligning ai with shared human values,","venue":null,"work_id":"a71c84ca-8df9-44c8-80de-681c209c5968","year":2021},"citing_paper":{"arxiv_id":"2505.14085","last_updated":"2025-05-20T08:46:23Z","snapshot_observed_at":"2026-08-12T20:33:35.976987Z","submitted_at":"2025-05-20T08:46:23Z","title":"CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:23.272726Z"},"links":{"citing_paper":"/paper/2505.14085"},"observation_digest":"sha256:32672b89188649daa138703aefc0b575c68b101915476988e863692f4ca5f590","observation_id":"e72d29dd-9468-4454-bdb9-2060b6317fcc","resolution":{"observed_at":"2026-08-07T15:42:24.548872Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-07T15:42:24.239640Z","title":null,"venue":null,"work_id":"c2b4d5de-4bfe-4523-8c2f-4efdf648d997","year":null},"citing_paper":{"arxiv_id":"2505.14085","last_updated":"2025-05-20T08:46:23Z","snapshot_observed_at":"2026-08-12T20:33:35.976987Z","submitted_at":"2025-05-20T08:46:23Z","title":"CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:23.380463Z"},"links":{"citing_paper":"/paper/2505.14085"},"observation_digest":"sha256:417a993110be9bda40c540fc7039d84340c4a098ff1faec8fbff983d9ccdcc34","observation_id":"e423a7f1-e62a-48d2-961a-bf5cf2914e95","resolution":{"observed_at":"2026-08-07T15:42:24.395352Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-07T15:42:24.057859Z","title":"After applying an orthogonal trans- formation, it becomes: Oc =O eQ(26) whereQ T Q=I","venue":null,"work_id":"46c8c82a-ce5f-4060-912e-e96907a0ebfd","year":null},"citing_paper":{"arxiv_id":"2505.14085","last_updated":"2025-05-20T08:46:23Z","snapshot_observed_at":"2026-08-12T20:33:35.976987Z","submitted_at":"2025-05-20T08:46:23Z","title":"CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:23.478704Z"},"links":{"citing_paper":"/paper/2505.14085"},"observation_digest":"sha256:60be0785ab4a53a931c4ca1322ad0dbccc2a107234ce6ebe224d4e75a78e5f12","observation_id":"3c155ec4-fc16-4007-a30a-75c7b896324c","resolution":{"observed_at":"2026-08-07T15:42:24.153525Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-07T15:42:23.899434Z","title":null,"venue":null,"work_id":"78ba5838-4a4b-4f80-8659-2e71ca7d37d7","year":null},"citing_paper":{"arxiv_id":"2505.14085","last_updated":"2025-05-20T08:46:23Z","snapshot_observed_at":"2026-08-12T20:33:35.976987Z","submitted_at":"2025-05-20T08:46:23Z","title":"CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:23.582268Z"},"links":{"citing_paper":"/paper/2505.14085"},"observation_digest":"sha256:ac2616dd239a039516b56218cda270c3ba96d16abfd7a3e62d85f0749898d2b4","observation_id":"6d10a037-0e94-40d0-9f0b-61708886f2f2","resolution":{"observed_at":"2026-08-07T15:42:23.976496Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1905.00414","last_updated":"2019-07-19T14:59:45Z","snapshot_observed_at":"2026-08-14T16:38:38.742173Z","submitted_at":"2019-05-01T17:57:26Z","title":"Similarity of Neural Network Representations Revisited","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1905.00414","snapshot_observed_at":"2026-08-07T15:42:22.865614Z","title":"Available: http://arxiv.org/abs/1905.00414","venue":null,"work_id":null,"year":1905},"citing_paper":{"arxiv_id":"2505.14085","last_updated":"2025-05-20T08:46:23Z","snapshot_observed_at":"2026-08-12T20:33:35.976987Z","submitted_at":"2025-05-20T08:46:23Z","title":"CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration","version":1},"reference_index":2019,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:22.865614Z"},"links":{"cited_paper":"/paper/1905.00414","citing_paper":"/paper/2505.14085"},"observation_digest":"sha256:fb14e34be79f3369fa0c55f3bfa83bacc876b247358cf18037b49752f79f07c2","observation_id":"496173f2-1f8a-4559-8dc3-3e891f1321ef","resolution":{"observed_at":"2026-08-07T15:42:22.865614Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2505.14085","last_updated":"2025-05-20T08:46:23Z","latest_version":1,"primary_category":"cs.NI","snapshot_observed_at":"2026-08-12T20:33:35.976987Z","submitted_at":"2025-05-20T08:46:23Z","title":"CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration"},"reference_resolution":{"displayed":36,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":23,"verified_exact":0,"verified_fuzzy":13},"total_outbound_references":36},"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":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"thesis":"As of 14 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2505.14085."}