{"as_of":"2026-08-09T09:20:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:87ee90a55de71a3f56fa5183e3ab66c720ef6150dbd00b3218d2e63c2c978659","coverage":[{"denominator":37,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":37,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-01T18:56:22.340947Z","state":"measured"},{"denominator":39,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":39,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-05T00:38:34.613440Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-05T00:37:29.136165Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2607.17154","last_updated":"2026-07-19T09:20:21Z","snapshot_observed_at":"2026-08-09T05:23:39.588966Z","submitted_at":"2026-07-19T09:20:21Z","title":"OrderMoE: An expert similarity driven distributed edge MoE inference","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2607.17154","snapshot_observed_at":"2026-08-05T00:38:34.613440Z","title":"OrderMoE: An Expert Similarity Driven Distributed Edge MoE Inference,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2608.00573","last_updated":"2026-08-01T10:19:02Z","snapshot_observed_at":"2026-08-06T23:17:28.405762Z","submitted_at":"2026-08-01T10:19:02Z","title":"TrimMoE A communication aware and adaptive depth framework for distributed edge inference","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-05T00:38:34.613440Z"},"links":{"cited_paper":"/paper/2607.17154","citing_paper":"/paper/2608.00573"},"observation_digest":"sha256:08500680b503f6416d0d94e9b223482a41cd7784af4d88e40b4ad41ce9b76bab","observation_id":"91d0d88d-1bfb-44de-b5cd-6a351b33cabf","resolution":{"observed_at":"2026-08-05T00:38:34.613440Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2607.17154","last_updated":"2026-07-19T09:20:21Z","snapshot_observed_at":"2026-08-09T05:23:39.588966Z","submitted_at":"2026-07-19T09:20:21Z","title":"OrderMoE: An expert similarity driven distributed edge MoE inference","version":1},"cited_work":{"arxiv_id":"2607.17154","doi":null,"metadata_source":"pith","pith_arxiv_id":"2607.17154","snapshot_observed_at":"2026-08-05T00:37:29.136165Z","title":"OrderMoE: An expert similarity driven distributed edge MoE inference","venue":"cs.NI","work_id":"13daac8d-219d-4868-bbcf-3caf0fa3d266","year":2026},"citing_paper":{"arxiv_id":"2608.00577","last_updated":"2026-08-01T10:30:01Z","snapshot_observed_at":"2026-08-09T05:23:12.352763Z","submitted_at":"2026-08-01T10:30:01Z","title":"HetRoute Heterogeneous and Cost-aware Collaborative Routing Framework for Distributed Edge MoE Inference","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-05T00:37:29.109326Z"},"links":{"cited_paper":"/paper/2607.17154","citing_paper":"/paper/2608.00577"},"observation_digest":"sha256:c05c26cd34d54084ac37dd15a8d802a647742924b6a5decd490da75013578d9f","observation_id":"515cb431-8843-43a2-b2ee-80e4056a1c95","resolution":{"observed_at":"2026-08-05T00:37:29.141479Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2607.17154/citation-record","integrity":"/paper/2607.17154/integrity","json":"/paper/2607.17154/citation-record.json","paper":"/paper/2607.17154"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T18:56:18.816248Z","title":"Mobile Edge Intelligence for Large Language Models: A Contemporary Survey,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.17154","last_updated":"2026-07-19T09:20:21Z","snapshot_observed_at":"2026-08-09T05:23:39.588966Z","submitted_at":"2026-07-19T09:20:21Z","title":"OrderMoE: An expert similarity driven distributed edge MoE inference","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-01T18:56:18.816248Z"},"links":{"citing_paper":"/paper/2607.17154"},"observation_digest":"sha256:62d51b1046f9775c73ae9dde055adb849b903462fc61683445c17b241affb49c","observation_id":"03a4c933-9e44-401a-91c9-502b0e2382ef","resolution":{"observed_at":"2026-08-01T18:56:18.816248Z","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":"2026-08-01T18:56:18.966613Z","title":"A Review on Edge Large Language Models: Design, Execution, and Applications,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.17154","last_updated":"2026-07-19T09:20:21Z","snapshot_observed_at":"2026-08-09T05:23:39.588966Z","submitted_at":"2026-07-19T09:20:21Z","title":"OrderMoE: An expert similarity driven distributed edge MoE inference","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-01T18:56:18.966613Z"},"links":{"citing_paper":"/paper/2607.17154"},"observation_digest":"sha256:de6b46acefcfc49f2ce606237fc0e7890fa57d43285d2e9c78282d3e8abed2c6","observation_id":"e1211f22-d93a-4000-8bab-68cd2392c1b2","resolution":{"observed_at":"2026-08-01T18:56:18.966613Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.04088","last_updated":"2024-01-08T18:47:34Z","snapshot_observed_at":"2026-08-08T06:16:25.839566Z","submitted_at":"2024-01-08T18:47:34Z","title":"Mixtral of Experts","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.04088","snapshot_observed_at":"2026-08-01T18:56:19.089487Z","title":"Mixtral of Experts,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.17154","last_updated":"2026-07-19T09:20:21Z","snapshot_observed_at":"2026-08-09T05:23:39.588966Z","submitted_at":"2026-07-19T09:20:21Z","title":"OrderMoE: An expert similarity driven distributed edge MoE inference","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-01T18:56:19.089487Z"},"links":{"cited_paper":"/paper/2401.04088","citing_paper":"/paper/2607.17154"},"observation_digest":"sha256:2348b8b9980b3eb68c690ad4238e450e8876584be8226a439b500193d74a2fbb","observation_id":"a69edd35-609b-474f-868e-1dfa99b39477","resolution":{"observed_at":"2026-08-01T18:56:19.089487Z","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":"2026-08-01T18:56:19.208543Z","title":"SparseGPT: Massive Language Models Can Be Accurately Pruned in One-Shot,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.17154","last_updated":"2026-07-19T09:20:21Z","snapshot_observed_at":"2026-08-09T05:23:39.588966Z","submitted_at":"2026-07-19T09:20:21Z","title":"OrderMoE: An expert similarity driven distributed edge MoE inference","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-01T18:56:19.208543Z"},"links":{"citing_paper":"/paper/2607.17154"},"observation_digest":"sha256:7fdd5e77af3104c6aff86ad538b0d7b22dbd48c983fa68cded457c5dec71f0db","observation_id":"30d22c05-4306-424a-a193-ff535b597456","resolution":{"observed_at":"2026-08-01T18:56:19.208543Z","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":"2026-08-01T18:56:19.314739Z","title":"Survey on Efficient Large Language Models: Principles, Algorithms, Applications, and Open Issues,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.17154","last_updated":"2026-07-19T09:20:21Z","snapshot_observed_at":"2026-08-09T05:23:39.588966Z","submitted_at":"2026-07-19T09:20:21Z","title":"OrderMoE: An expert similarity driven distributed edge MoE inference","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-01T18:56:19.314739Z"},"links":{"citing_paper":"/paper/2607.17154"},"observation_digest":"sha256:f4360e1435d226566904aeea6e59a1c112880ac3c383f8e4a9533b2f1af2f0cf","observation_id":"265f4d25-21d5-492f-b56c-cfca6bfe0bfb","resolution":{"observed_at":"2026-08-01T18:56:19.314739Z","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":"2026-08-01T18:56:19.519025Z","title":"SVD-LLM: Truncation-aware Singular Value Decomposition for Large Language Model Compression,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.17154","last_updated":"2026-07-19T09:20:21Z","snapshot_observed_at":"2026-08-09T05:23:39.588966Z","submitted_at":"2026-07-19T09:20:21Z","title":"OrderMoE: An expert similarity driven distributed edge MoE inference","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-01T18:56:19.519025Z"},"links":{"citing_paper":"/paper/2607.17154"},"observation_digest":"sha256:895ff68c5e20f1560571b864eeca6c7c39cffec281c418f4277b88f87e5e7f5d","observation_id":"4bcafe77-0533-4479-850e-ab9e24010538","resolution":{"observed_at":"2026-08-01T18:56:19.519025Z","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":"2026-08-01T18:56:19.662310Z","title":"FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.17154","last_updated":"2026-07-19T09:20:21Z","snapshot_observed_at":"2026-08-09T05:23:39.588966Z","submitted_at":"2026-07-19T09:20:21Z","title":"OrderMoE: An expert similarity driven distributed edge MoE inference","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-01T18:56:19.662310Z"},"links":{"citing_paper":"/paper/2607.17154"},"observation_digest":"sha256:46a10985c09502aa2d28ae952bae4f8574a22f33650d99aa9b107a39245d5b0a","observation_id":"844bf373-e481-42ed-b962-7f4bcacd1cc0","resolution":{"observed_at":"2026-08-01T18:56:19.662310Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2508.12851","last_updated":"2026-04-15T14:22:25Z","snapshot_observed_at":"2026-07-06T22:14:25.511807Z","submitted_at":"2025-08-18T11:41:17Z","title":"Accelerating Edge Inference for Distributed MoE Models with Latency-Optimized Expert Placement","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2508.12851","snapshot_observed_at":"2026-08-01T18:56:19.766584Z","title":"Accelerating Edge Inference for Distributed MoE Models with Latency-Optimized Expert Placement,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.17154","last_updated":"2026-07-19T09:20:21Z","snapshot_observed_at":"2026-08-09T05:23:39.588966Z","submitted_at":"2026-07-19T09:20:21Z","title":"OrderMoE: An expert similarity driven distributed edge MoE inference","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-01T18:56:19.766584Z"},"links":{"cited_paper":"/paper/2508.12851","citing_paper":"/paper/2607.17154"},"observation_digest":"sha256:1b7dae0a1a6e5bc1e82724860ab5988d9b44f2f523a800f4f2a1409531dd1f94","observation_id":"f0ba5b1d-6ddb-4152-bc87-f0d5573af3fa","resolution":{"observed_at":"2026-08-01T18:56:19.766584Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.13421","last_updated":"2025-03-17T17:51:49Z","snapshot_observed_at":"2026-08-07T16:57:07.136160Z","submitted_at":"2025-03-17T17:51:49Z","title":"Optimal Expert Selection for Distributed Mixture-of-Experts at the Wireless Edge","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.13421","snapshot_observed_at":"2026-08-01T18:56:19.943380Z","title":"Optimal Expert Selection for Distributed Mixture-of-Experts at the Wireless Edge,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.17154","last_updated":"2026-07-19T09:20:21Z","snapshot_observed_at":"2026-08-09T05:23:39.588966Z","submitted_at":"2026-07-19T09:20:21Z","title":"OrderMoE: An expert similarity driven distributed edge MoE inference","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-01T18:56:19.943380Z"},"links":{"cited_paper":"/paper/2503.13421","citing_paper":"/paper/2607.17154"},"observation_digest":"sha256:aa77b77b0e12980cf099076ec91f1444d5e2e7604a0b6f56cd3e31d82a4ed7b3","observation_id":"1dac2f50-4e5f-439d-8643-bd68e60c9aa8","resolution":{"observed_at":"2026-08-01T18:56:19.943380Z","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":"2026-08-01T18:56:20.079409Z","title":"Scalable Training of Mixture-of-Experts Models with Megatron Core,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.17154","last_updated":"2026-07-19T09:20:21Z","snapshot_observed_at":"2026-08-09T05:23:39.588966Z","submitted_at":"2026-07-19T09:20:21Z","title":"OrderMoE: An expert similarity driven distributed edge MoE inference","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-01T18:56:20.079409Z"},"links":{"citing_paper":"/paper/2607.17154"},"observation_digest":"sha256:e21f2bbc103623f0a2a687ec42ddd6485ccd6f329be94d7a394e13bee9e27807","observation_id":"bc1b80df-5196-409f-b256-0774372e532f","resolution":{"observed_at":"2026-08-01T18:56:20.079409Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.17307","last_updated":"2025-08-04T19:35:34Z","snapshot_observed_at":"2026-08-07T15:59:37.808930Z","submitted_at":"2025-04-24T07:01:44Z","title":"An Extensible Software Transport Layer for GPU Networking","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.17307","snapshot_observed_at":"2026-08-01T18:56:20.248826Z","title":"An Extensible Software Transport Layer for GPU Networking,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.17154","last_updated":"2026-07-19T09:20:21Z","snapshot_observed_at":"2026-08-09T05:23:39.588966Z","submitted_at":"2026-07-19T09:20:21Z","title":"OrderMoE: An expert similarity driven distributed edge MoE inference","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-01T18:56:20.248826Z"},"links":{"cited_paper":"/paper/2504.17307","citing_paper":"/paper/2607.17154"},"observation_digest":"sha256:61bef9af87471e7758d70642ede2ccafb2f8c54ebf4c776699256ffa6b891854","observation_id":"35a921ad-da5d-4dfe-ac2e-262c1cae5297","resolution":{"observed_at":"2026-08-01T18:56:20.248826Z","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":"2026-08-01T18:56:20.342179Z","title":"The MoE-Empowered Edge LLMs Deployment: Architecture, Challenges, and Opportunities,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.17154","last_updated":"2026-07-19T09:20:21Z","snapshot_observed_at":"2026-08-09T05:23:39.588966Z","submitted_at":"2026-07-19T09:20:21Z","title":"OrderMoE: An expert similarity driven distributed edge MoE inference","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-01T18:56:20.342179Z"},"links":{"citing_paper":"/paper/2607.17154"},"observation_digest":"sha256:347099d18aabdba0bbe030e699a42bfef64c7f285e63506bf411f73417de8afb","observation_id":"3d9d8a01-1e12-48e9-9983-6771920060c4","resolution":{"observed_at":"2026-08-01T18:56:20.342179Z","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":"2026-08-01T18:56:20.410755Z","title":"Serving Long-Context LLMs at the Mobile Edge: Test-time Reinforcement Learning based Model Caching and Inference Offloading","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.17154","last_updated":"2026-07-19T09:20:21Z","snapshot_observed_at":"2026-08-09T05:23:39.588966Z","submitted_at":"2026-07-19T09:20:21Z","title":"OrderMoE: An expert similarity driven distributed edge MoE inference","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-01T18:56:20.410755Z"},"links":{"citing_paper":"/paper/2607.17154"},"observation_digest":"sha256:ddce84af52d94b5f84eeab94480e298b9a02e5070e95c2c0c0010db6d7beba0f","observation_id":"1f99ae7d-f057-4056-9c2e-be3f3c4db500","resolution":{"observed_at":"2026-08-01T18:56:20.410755Z","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":"2026-08-01T18:56:20.503692Z","title":"Layerwise Recurrent Router for Mixture-of-Experts,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.17154","last_updated":"2026-07-19T09:20:21Z","snapshot_observed_at":"2026-08-09T05:23:39.588966Z","submitted_at":"2026-07-19T09:20:21Z","title":"OrderMoE: An expert similarity driven distributed edge MoE inference","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-01T18:56:20.503692Z"},"links":{"citing_paper":"/paper/2607.17154"},"observation_digest":"sha256:6166bff59683ceba0f418e639170cdcb58d44b8fea27538be473943064c5daf6","observation_id":"6ed1faf4-2a54-4457-b947-c75e65b53944","resolution":{"observed_at":"2026-08-01T18:56:20.503692Z","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":"2026-08-01T18:56:20.596191Z","title":"Geometric Regularization in MoEs: The Disconnect Between Weights and Activations in MoE Models,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.17154","last_updated":"2026-07-19T09:20:21Z","snapshot_observed_at":"2026-08-09T05:23:39.588966Z","submitted_at":"2026-07-19T09:20:21Z","title":"OrderMoE: An expert similarity driven distributed edge MoE inference","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-01T18:56:20.596191Z"},"links":{"citing_paper":"/paper/2607.17154"},"observation_digest":"sha256:1cf7eeebe194b540a36f1b5c67bcabe5c6911c108cc71fbf59e66191e16464f2","observation_id":"3531801d-266c-4ae1-acfb-5dd27c181bab","resolution":{"observed_at":"2026-08-01T18:56:20.596191Z","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":"2026-08-01T18:56:20.692683Z","title":"Distributed inference acceleration with adaptive DNN partitioning and offloading,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.17154","last_updated":"2026-07-19T09:20:21Z","snapshot_observed_at":"2026-08-09T05:23:39.588966Z","submitted_at":"2026-07-19T09:20:21Z","title":"OrderMoE: An expert similarity driven distributed edge MoE inference","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-01T18:56:20.692683Z"},"links":{"citing_paper":"/paper/2607.17154"},"observation_digest":"sha256:4640b077238cce8215025dc8a7748a51ddb70efdb4366db9a0f93bb3e2f11d64","observation_id":"1f88ad24-1848-4849-a273-84a19b1cb636","resolution":{"observed_at":"2026-08-01T18:56:20.692683Z","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":"2026-08-01T18:56:20.757938Z","title":"PArtNNer: Platform-Agnostic Adaptive Edge-Cloud DNN Partitioning for Minimizing End-to-End Latency,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.17154","last_updated":"2026-07-19T09:20:21Z","snapshot_observed_at":"2026-08-09T05:23:39.588966Z","submitted_at":"2026-07-19T09:20:21Z","title":"OrderMoE: An expert similarity driven distributed edge MoE inference","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-01T18:56:20.757938Z"},"links":{"citing_paper":"/paper/2607.17154"},"observation_digest":"sha256:4a11c92b980ea213629606f612e9c16d51e6875c7e0f9436e85ad595e6fad2a8","observation_id":"dad84c46-b378-4662-b941-ed357087ebac","resolution":{"observed_at":"2026-08-01T18:56:20.757938Z","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":"2026-08-01T18:56:20.827119Z","title":"DNN Partitioning for Cooperative Inference in Edge Intelligence: Modeling, Solutions, Toolchains,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.17154","last_updated":"2026-07-19T09:20:21Z","snapshot_observed_at":"2026-08-09T05:23:39.588966Z","submitted_at":"2026-07-19T09:20:21Z","title":"OrderMoE: An expert similarity driven distributed edge MoE inference","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-01T18:56:20.827119Z"},"links":{"citing_paper":"/paper/2607.17154"},"observation_digest":"sha256:eda41b108d706d2f824d9dd646520ada94a0dacdeb71923a2d3fdd1b745a5b15","observation_id":"e6795ce9-f976-4750-8379-13ff3afc8997","resolution":{"observed_at":"2026-08-01T18:56:20.827119Z","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":"2026-08-01T18:56:20.897799Z","title":"Edge-LLM: A Collaborative Framework for Large Language Model Serving in Edge Computing,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.17154","last_updated":"2026-07-19T09:20:21Z","snapshot_observed_at":"2026-08-09T05:23:39.588966Z","submitted_at":"2026-07-19T09:20:21Z","title":"OrderMoE: An expert similarity driven distributed edge MoE inference","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-01T18:56:20.897799Z"},"links":{"citing_paper":"/paper/2607.17154"},"observation_digest":"sha256:4b6f39bf1f5d9617cb3781738085b3ac569e99dc2ef4df8f59bf492b51475233","observation_id":"f59c9c1e-d2b0-48da-94ec-aa844f0f493e","resolution":{"observed_at":"2026-08-01T18:56:20.897799Z","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":"2026-08-01T18:56:20.974583Z","title":"EdgeShard: Efficient LLM Inference via Collaborative Edge Computing,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.17154","last_updated":"2026-07-19T09:20:21Z","snapshot_observed_at":"2026-08-09T05:23:39.588966Z","submitted_at":"2026-07-19T09:20:21Z","title":"OrderMoE: An expert similarity driven distributed edge MoE inference","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-01T18:56:20.974583Z"},"links":{"citing_paper":"/paper/2607.17154"},"observation_digest":"sha256:f4466661a84bac5599bb04cdd9dba8adc37b1541e2b300022b7651088a90c84d","observation_id":"781e175a-fc62-4f8c-9212-4522074cfa8b","resolution":{"observed_at":"2026-08-01T18:56:20.974583Z","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":"2026-08-01T18:56:21.054827Z","title":"Communication-Efficient Distributed On-Device LLM Inference Over Wireless Networks,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.17154","last_updated":"2026-07-19T09:20:21Z","snapshot_observed_at":"2026-08-09T05:23:39.588966Z","submitted_at":"2026-07-19T09:20:21Z","title":"OrderMoE: An expert similarity driven distributed edge MoE inference","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-01T18:56:21.054827Z"},"links":{"citing_paper":"/paper/2607.17154"},"observation_digest":"sha256:ecc56a9d90a10f96419d725a9834aeae2613a3393649b162305fc5a433157264","observation_id":"ccef881a-526a-4106-8bbd-3cd9a633d0d2","resolution":{"observed_at":"2026-08-01T18:56:21.054827Z","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":"2026-08-01T18:56:21.149022Z","title":"Jupiter: Fast and Resource-Efficient Collaborative Inference of Generative LLMs on Edge Devices,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.17154","last_updated":"2026-07-19T09:20:21Z","snapshot_observed_at":"2026-08-09T05:23:39.588966Z","submitted_at":"2026-07-19T09:20:21Z","title":"OrderMoE: An expert similarity driven distributed edge MoE inference","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-01T18:56:21.149022Z"},"links":{"citing_paper":"/paper/2607.17154"},"observation_digest":"sha256:cc5655500c9f995fdcc09ad086281211564a92c2bb755734da08ccf9d9115544","observation_id":"c0cc6423-5a40-4e1b-8fb8-d1b715d2d475","resolution":{"observed_at":"2026-08-01T18:56:21.149022Z","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":"2026-08-01T18:56:21.242836Z","title":"Birds in Cages: Edge Inference Allocation for Distributed LLM Deployment,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.17154","last_updated":"2026-07-19T09:20:21Z","snapshot_observed_at":"2026-08-09T05:23:39.588966Z","submitted_at":"2026-07-19T09:20:21Z","title":"OrderMoE: An expert similarity driven distributed edge MoE inference","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-01T18:56:21.242836Z"},"links":{"citing_paper":"/paper/2607.17154"},"observation_digest":"sha256:886bfd99abd11c57251924b6cc71407c00cc01996362ae1013a9ca147f1b0d9e","observation_id":"d8e79b99-3b5f-45f9-8796-52f88bf63d83","resolution":{"observed_at":"2026-08-01T18:56:21.242836Z","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":"2026-08-01T18:56:21.332081Z","title":"Cloud-Edge-End Collaborative Inference in Mobile Networks: Challenges and Solutions,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.17154","last_updated":"2026-07-19T09:20:21Z","snapshot_observed_at":"2026-08-09T05:23:39.588966Z","submitted_at":"2026-07-19T09:20:21Z","title":"OrderMoE: An expert similarity driven distributed edge MoE inference","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-01T18:56:21.332081Z"},"links":{"citing_paper":"/paper/2607.17154"},"observation_digest":"sha256:8e31952a11667771b126342f31fee8237684794dcdfc761ae777632ce136950f","observation_id":"ea29b4e5-84e6-44ba-aadc-3796b2faa7df","resolution":{"observed_at":"2026-08-01T18:56:21.332081Z","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":"2026-08-01T18:56:21.392970Z","title":"ERA: A QoE-Aware Collaborative Inference Algorithm for NOMA-based Edge Intelligence,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.17154","last_updated":"2026-07-19T09:20:21Z","snapshot_observed_at":"2026-08-09T05:23:39.588966Z","submitted_at":"2026-07-19T09:20:21Z","title":"OrderMoE: An expert similarity driven distributed edge MoE inference","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-01T18:56:21.392970Z"},"links":{"citing_paper":"/paper/2607.17154"},"observation_digest":"sha256:7d7e7387bf60048eaf194c563ba461d791094f70af214962765d116f108ee122","observation_id":"a23e4ebe-0133-4a6f-a81e-c473f1e23f67","resolution":{"observed_at":"2026-08-01T18:56:21.392970Z","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":"2026-08-01T18:56:21.460913Z","title":"Mobility and Cost Aware Inference Accelerating Algorithm for Edge Intelligence,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.17154","last_updated":"2026-07-19T09:20:21Z","snapshot_observed_at":"2026-08-09T05:23:39.588966Z","submitted_at":"2026-07-19T09:20:21Z","title":"OrderMoE: An expert similarity driven distributed edge MoE inference","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-01T18:56:21.460913Z"},"links":{"citing_paper":"/paper/2607.17154"},"observation_digest":"sha256:65842594d9417167189b688be0f123dc7a0eea54e1a1f2089ec9ac4ffffe5a36","observation_id":"38fb18eb-04c9-4e4b-9ae6-424fb2d725be","resolution":{"observed_at":"2026-08-01T18:56:21.460913Z","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":"2026-08-01T18:56:21.531844Z","title":"High Efficiency Inference Accelerating Algorithm for NOMA-based Edge Intelligence,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.17154","last_updated":"2026-07-19T09:20:21Z","snapshot_observed_at":"2026-08-09T05:23:39.588966Z","submitted_at":"2026-07-19T09:20:21Z","title":"OrderMoE: An expert similarity driven distributed edge MoE inference","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-01T18:56:21.531844Z"},"links":{"citing_paper":"/paper/2607.17154"},"observation_digest":"sha256:7a2b342064417ade0f46b8a3be1e96d0cd947fe9baafeeb8f0c6dfb92833dd1b","observation_id":"1dd50359-987e-4fe5-8321-313c2cf3299a","resolution":{"observed_at":"2026-08-01T18:56:21.531844Z","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":"2026-08-01T18:56:21.608422Z","title":"AdapMoE: Adaptive Sensitivity-Based Expert Gating and Management for Efficient MoE Inference,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.17154","last_updated":"2026-07-19T09:20:21Z","snapshot_observed_at":"2026-08-09T05:23:39.588966Z","submitted_at":"2026-07-19T09:20:21Z","title":"OrderMoE: An expert similarity driven distributed edge MoE inference","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-01T18:56:21.608422Z"},"links":{"citing_paper":"/paper/2607.17154"},"observation_digest":"sha256:72fe1ae071ac8f3ab59e4bf645af882a9ec41724421f593d7a1c9468c895f9d0","observation_id":"b4dbaf1b-d660-4f60-80db-2971b54fe40e","resolution":{"observed_at":"2026-08-01T18:56:21.608422Z","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":"2026-08-01T18:56:21.710702Z","title":"SlimCaching: Edge Caching of Mixture-of-Experts for Distributed Inference,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.17154","last_updated":"2026-07-19T09:20:21Z","snapshot_observed_at":"2026-08-09T05:23:39.588966Z","submitted_at":"2026-07-19T09:20:21Z","title":"OrderMoE: An expert similarity driven distributed edge MoE inference","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-01T18:56:21.710702Z"},"links":{"citing_paper":"/paper/2607.17154"},"observation_digest":"sha256:29b587155c9af71d25f9b4cc7bb88ea8a3e6e260284e93f28d62c3f12c09c024","observation_id":"eeb20a04-b27b-448d-86e7-9cb4ebf2d11d","resolution":{"observed_at":"2026-08-01T18:56:21.710702Z","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":"2026-08-01T18:56:21.778260Z","title":"Diff-MoE: Efficient Batched MoE Inference with Priority-Driven Differential Expert Caching,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.17154","last_updated":"2026-07-19T09:20:21Z","snapshot_observed_at":"2026-08-09T05:23:39.588966Z","submitted_at":"2026-07-19T09:20:21Z","title":"OrderMoE: An expert similarity driven distributed edge MoE inference","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-01T18:56:21.778260Z"},"links":{"citing_paper":"/paper/2607.17154"},"observation_digest":"sha256:3305a08c36a31f9545e84ad784d9bfa2075f3597800a804da983f268b008f49e","observation_id":"84093702-b44d-4e70-923c-8f093009c22a","resolution":{"observed_at":"2026-08-01T18:56:21.778260Z","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":"2026-08-01T18:56:21.844535Z","title":"PROBE: Co-Balancing Computation and Communication in MoE Inference via Real-Time Predictive Prefetching,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.17154","last_updated":"2026-07-19T09:20:21Z","snapshot_observed_at":"2026-08-09T05:23:39.588966Z","submitted_at":"2026-07-19T09:20:21Z","title":"OrderMoE: An expert similarity driven distributed edge MoE inference","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-01T18:56:21.844535Z"},"links":{"citing_paper":"/paper/2607.17154"},"observation_digest":"sha256:a876916ac0e60190395467d66557fe06ae2be6b8b7271dbfda2dfdee0c046825","observation_id":"66746b93-b60d-4c6f-bd02-ded51e356423","resolution":{"observed_at":"2026-08-01T18:56:21.844535Z","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":"2026-08-01T18:56:21.924538Z","title":"MegaScale-Infer: Efficient Mixture-of-Experts Model Serving with Disaggregated Expert Parallelism,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.17154","last_updated":"2026-07-19T09:20:21Z","snapshot_observed_at":"2026-08-09T05:23:39.588966Z","submitted_at":"2026-07-19T09:20:21Z","title":"OrderMoE: An expert similarity driven distributed edge MoE inference","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-01T18:56:21.924538Z"},"links":{"citing_paper":"/paper/2607.17154"},"observation_digest":"sha256:250f0845c6cb48467a45181ce1de0e9546a6a5a240eafa2e004bda5638c13ee3","observation_id":"b17f9dc4-f738-46a1-880a-df572e7e9752","resolution":{"observed_at":"2026-08-01T18:56:21.924538Z","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":"2026-08-01T18:56:22.001704Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.17154","last_updated":"2026-07-19T09:20:21Z","snapshot_observed_at":"2026-08-09T05:23:39.588966Z","submitted_at":"2026-07-19T09:20:21Z","title":"OrderMoE: An expert similarity driven distributed edge MoE inference","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-01T18:56:22.001704Z"},"links":{"citing_paper":"/paper/2607.17154"},"observation_digest":"sha256:db6e1e141adb50ca143ca5c9b1b68224ba1ae2728f7cdbe67ed6404c6d13d232","observation_id":"e1373164-500e-48dd-a73c-babed1681611","resolution":{"observed_at":"2026-08-01T18:56:22.001704Z","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":"2026-08-01T18:56:22.079952Z","title":"MoE2: Optimizing Collaborative Inference for Edge Large Language Models,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.17154","last_updated":"2026-07-19T09:20:21Z","snapshot_observed_at":"2026-08-09T05:23:39.588966Z","submitted_at":"2026-07-19T09:20:21Z","title":"OrderMoE: An expert similarity driven distributed edge MoE inference","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-01T18:56:22.079952Z"},"links":{"citing_paper":"/paper/2607.17154"},"observation_digest":"sha256:77223878b6f8055227d25c2c9d0fe385b4020756eeb303c5df6b3ffcec8ef5b5","observation_id":"144c197c-795c-4fba-ae68-1dace95a639f","resolution":{"observed_at":"2026-08-01T18:56:22.079952Z","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":"2026-08-01T18:56:22.152411Z","title":"Breaking the MoE LLM Trilemma: Dynamic Expert Clustering with Structured Compression,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.17154","last_updated":"2026-07-19T09:20:21Z","snapshot_observed_at":"2026-08-09T05:23:39.588966Z","submitted_at":"2026-07-19T09:20:21Z","title":"OrderMoE: An expert similarity driven distributed edge MoE inference","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-01T18:56:22.152411Z"},"links":{"citing_paper":"/paper/2607.17154"},"observation_digest":"sha256:329fb4e75b380f5d27234a5bda9298d7b5b9d48fe3bd4f83ebb25d66b21b7d23","observation_id":"4cd28106-eda9-4dd5-ad94-db5237fef424","resolution":{"observed_at":"2026-08-01T18:56:22.152411Z","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":"2026-08-01T18:56:22.248998Z","title":"A Survey on Inference Optimization Techniques for Mixture of Experts Models,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.17154","last_updated":"2026-07-19T09:20:21Z","snapshot_observed_at":"2026-08-09T05:23:39.588966Z","submitted_at":"2026-07-19T09:20:21Z","title":"OrderMoE: An expert similarity driven distributed edge MoE inference","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-01T18:56:22.248998Z"},"links":{"citing_paper":"/paper/2607.17154"},"observation_digest":"sha256:52833503e46a20e09dd03bb9c060a1c5936a7e8253652168c33c5173f78b8977","observation_id":"6dc1ac4b-4807-40eb-8947-b3803a43dc4c","resolution":{"observed_at":"2026-08-01T18:56:22.248998Z","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":"2026-08-01T18:56:22.340947Z","title":"Towards Efficient Generative Large Language Model Serving: A Survey from Algorithms to Systems,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.17154","last_updated":"2026-07-19T09:20:21Z","snapshot_observed_at":"2026-08-09T05:23:39.588966Z","submitted_at":"2026-07-19T09:20:21Z","title":"OrderMoE: An expert similarity driven distributed edge MoE inference","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-01T18:56:22.340947Z"},"links":{"citing_paper":"/paper/2607.17154"},"observation_digest":"sha256:5250994b330746fd6bb22c294815e398412d6f00c8d885f1990ead308dbed656","observation_id":"bc2d32d7-060e-4e5d-beac-d94f033e5be5","resolution":{"observed_at":"2026-08-01T18:56:22.340947Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2607.17154","last_updated":"2026-07-19T09:20:21Z","latest_version":1,"primary_category":"cs.NI","snapshot_observed_at":"2026-08-09T05:23:39.588966Z","submitted_at":"2026-07-19T09:20:21Z","title":"OrderMoE: An expert similarity driven distributed edge MoE inference"},"reference_resolution":{"displayed":37,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":37,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":37},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 2 inbound Pith citation observations for arXiv:2607.17154."}