{"as_of":"2026-08-17T20:23:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:0fdb3df97d6f523550d7d58140ba8e738f261d0b4a3221e852e209a3aa1f64a0","coverage":[{"denominator":31,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":31,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T13:43:55.302873Z","state":"measured"},{"denominator":32,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":32,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-17T06:30:58.91139+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-09T10:29:38.504271Z","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":"2026-08-09T10:29:38.834487Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2411.16003","last_updated":"2024-11-24T22:50:02Z","snapshot_observed_at":"2026-08-13T22:40:43.804756Z","submitted_at":"2024-11-24T22:50:02Z","title":"eFedLLM: Efficient LLM Inference Based on Federated Learning","version":1},"cited_work":{"arxiv_id":"2411.16003","doi":null,"metadata_source":"pith","pith_arxiv_id":"2411.16003","snapshot_observed_at":"2026-08-09T10:29:38.834487Z","title":"eFedLLM: Efficient LLM Inference Based on Federated Learning","venue":"cs.LG","work_id":"87a0baa3-3818-4de0-8d7e-b5673b838587","year":2024},"citing_paper":{"arxiv_id":"2502.02982","last_updated":"2025-05-20T07:03:02Z","snapshot_observed_at":"2026-08-14T02:16:13.702439Z","submitted_at":"2025-02-05T08:26:17Z","title":"MobileA3gent: Training Mobile GUI Agents Using Decentralized Self-Sourced Data from Diverse Users","version":2},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-09T10:29:38.504271Z"},"links":{"cited_paper":"/paper/2411.16003","citing_paper":"/paper/2502.02982"},"observation_digest":"sha256:08fc9752df54580fb2f902535cae088107fbad470a0dc2c594d38aa29e66e496","observation_id":"347f4c4c-9c2c-4419-af76-8ece60e44da9","resolution":{"observed_at":"2026-08-09T10:29:38.840546Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2411.16003/citation-record","integrity":"/paper/2411.16003/integrity","json":"/paper/2411.16003/citation-record.json","paper":"/paper/2411.16003"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T13:43:56.054014Z","title":null,"venue":null,"work_id":"38b89c30-a71a-4d71-91bc-58d70308a0ee","year":2023},"citing_paper":{"arxiv_id":"2411.16003","last_updated":"2024-11-24T22:50:02Z","snapshot_observed_at":"2026-08-13T22:40:43.804756Z","submitted_at":"2024-11-24T22:50:02Z","title":"eFedLLM: Efficient LLM Inference Based on Federated Learning","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-12T13:43:55.146187Z"},"links":{"citing_paper":"/paper/2411.16003"},"observation_digest":"sha256:ef4048e15d02528a1feabb73faca7a0c6144c9d48f5619fcf4395d7fdfc375ea","observation_id":"f6f6f133-7c95-4305-9151-22d23f854298","resolution":{"observed_at":"2026-08-12T13:43:56.059196Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.14219","last_updated":"2024-08-30T21:17:17Z","snapshot_observed_at":"2026-08-17T03:25:04.404839Z","submitted_at":"2024-04-22T14:32:33Z","title":"Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.14219","snapshot_observed_at":"2026-08-12T13:43:55.151770Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.16003","last_updated":"2024-11-24T22:50:02Z","snapshot_observed_at":"2026-08-13T22:40:43.804756Z","submitted_at":"2024-11-24T22:50:02Z","title":"eFedLLM: Efficient LLM Inference Based on Federated Learning","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-12T13:43:55.151770Z"},"links":{"cited_paper":"/paper/2404.14219","citing_paper":"/paper/2411.16003"},"observation_digest":"sha256:498ac5e934b63ff341846f3c9a0fec0b8f9a30d62207a4ffc2c2f41c61847b6a","observation_id":"9d525c6f-0c75-4399-979d-3e39827cd5c8","resolution":{"observed_at":"2026-08-12T13:43:55.151770Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2209.01188","last_updated":"2023-03-02T19:33:31Z","snapshot_observed_at":"2026-08-16T16:35:03.571411Z","submitted_at":"2022-09-02T17:38:03Z","title":"Petals: Collaborative Inference and Fine-tuning of Large Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2209.01188","snapshot_observed_at":"2026-08-12T13:43:55.157274Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.16003","last_updated":"2024-11-24T22:50:02Z","snapshot_observed_at":"2026-08-13T22:40:43.804756Z","submitted_at":"2024-11-24T22:50:02Z","title":"eFedLLM: Efficient LLM Inference Based on Federated Learning","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-12T13:43:55.157274Z"},"links":{"cited_paper":"/paper/2209.01188","citing_paper":"/paper/2411.16003"},"observation_digest":"sha256:17e776a29a6206d9ce057a2885df90007754a67e6a60489069f47220a0bd704b","observation_id":"f1d03d2e-b163-4e9e-9d45-cb29792f4ade","resolution":{"observed_at":"2026-08-12T13:43:55.157274Z","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":"2026-08-12T13:43:55.162793Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2411.16003","last_updated":"2024-11-24T22:50:02Z","snapshot_observed_at":"2026-08-13T22:40:43.804756Z","submitted_at":"2024-11-24T22:50:02Z","title":"eFedLLM: Efficient LLM Inference Based on Federated Learning","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-12T13:43:55.162793Z"},"links":{"citing_paper":"/paper/2411.16003"},"observation_digest":"sha256:1cb8827159be9540e5d6ebc7b18e90caaf02c9554023811699e40433e069f74d","observation_id":"a26257bf-7a21-438c-b06e-2cd436534ebd","resolution":{"observed_at":"2026-08-12T13:43:55.162793Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.10774","last_updated":"2024-06-14T23:32:32Z","snapshot_observed_at":"2026-08-17T10:13:54.763177Z","submitted_at":"2024-01-19T15:48:40Z","title":"Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.10774","snapshot_observed_at":"2026-08-12T13:43:55.168622Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.16003","last_updated":"2024-11-24T22:50:02Z","snapshot_observed_at":"2026-08-13T22:40:43.804756Z","submitted_at":"2024-11-24T22:50:02Z","title":"eFedLLM: Efficient LLM Inference Based on Federated Learning","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-12T13:43:55.168622Z"},"links":{"cited_paper":"/paper/2401.10774","citing_paper":"/paper/2411.16003"},"observation_digest":"sha256:19695d94bde8770bef3175443c746ff8fffb222704517b0e2c4492627f88cccb","observation_id":"e9b0490c-3a67-4f57-80e9-910511a23713","resolution":{"observed_at":"2026-08-12T13:43:55.168622Z","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":"2026-08-12T13:43:56.024643Z","title":null,"venue":null,"work_id":"86e7ad8a-0fd3-44ae-80cc-f4a5ad05937b","year":2019},"citing_paper":{"arxiv_id":"2411.16003","last_updated":"2024-11-24T22:50:02Z","snapshot_observed_at":"2026-08-13T22:40:43.804756Z","submitted_at":"2024-11-24T22:50:02Z","title":"eFedLLM: Efficient LLM Inference Based on Federated Learning","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-12T13:43:55.173975Z"},"links":{"citing_paper":"/paper/2411.16003"},"observation_digest":"sha256:07e768d51c58ecc0ffd90211cd402fa6b2a1bc6ab9eb5a3974f25df192832647","observation_id":"5ad40308-938e-48dd-89c3-c9ae110d22bd","resolution":{"observed_at":"2026-08-12T13:43:56.030461Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-12T13:43:55.179605Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.16003","last_updated":"2024-11-24T22:50:02Z","snapshot_observed_at":"2026-08-13T22:40:43.804756Z","submitted_at":"2024-11-24T22:50:02Z","title":"eFedLLM: Efficient LLM Inference Based on Federated Learning","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-12T13:43:55.179605Z"},"links":{"citing_paper":"/paper/2411.16003"},"observation_digest":"sha256:7492f25936e66ba8cf6879d615b8b1e9a497b6b0dc503f4c3175c6d244ed8431","observation_id":"9c226577-1a12-4d1c-b687-954a9c67fedd","resolution":{"observed_at":"2026-08-12T13:43:55.179605Z","resolver_source":null,"status":"malformed_identifier"},"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":"2026-08-12T13:43:55.185771Z","title":"Vincent Poor, Yonina C","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2411.16003","last_updated":"2024-11-24T22:50:02Z","snapshot_observed_at":"2026-08-13T22:40:43.804756Z","submitted_at":"2024-11-24T22:50:02Z","title":"eFedLLM: Efficient LLM Inference Based on Federated Learning","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-12T13:43:55.185771Z"},"links":{"citing_paper":"/paper/2411.16003"},"observation_digest":"sha256:c7f64f8b5728a74237171718f0155052ed1892c1b31aa6e4237e6cba73680880","observation_id":"53e50904-4a14-4d01-ac38-275a788cd2ff","resolution":{"observed_at":"2026-08-12T13:43:55.185771Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1704.02086","last_updated":"2017-04-07T03:54:42Z","snapshot_observed_at":"2026-08-14T21:07:52.442554Z","submitted_at":"2017-04-07T03:54:42Z","title":"A Zero Knowledge Sumcheck and its Applications","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1704.02086","snapshot_observed_at":"2026-08-12T13:43:55.190317Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2411.16003","last_updated":"2024-11-24T22:50:02Z","snapshot_observed_at":"2026-08-13T22:40:43.804756Z","submitted_at":"2024-11-24T22:50:02Z","title":"eFedLLM: Efficient LLM Inference Based on Federated Learning","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-12T13:43:55.190317Z"},"links":{"cited_paper":"/paper/1704.02086","citing_paper":"/paper/2411.16003"},"observation_digest":"sha256:df6fd9561b3def93e64791378af39eeaeb0c6a4c3e2608f8f81bfe4f93325840","observation_id":"d18e4728-d1a4-4cfb-8885-2d69d9cd58e6","resolution":{"observed_at":"2026-08-12T13:43:55.190317Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.17555","last_updated":"2024-02-05T05:23:59Z","snapshot_observed_at":"2026-08-16T14:23:00.651423Z","submitted_at":"2024-01-31T02:43:38Z","title":"opML: Optimistic Machine Learning on Blockchain","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.17555","snapshot_observed_at":"2026-08-12T13:43:55.194767Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.16003","last_updated":"2024-11-24T22:50:02Z","snapshot_observed_at":"2026-08-13T22:40:43.804756Z","submitted_at":"2024-11-24T22:50:02Z","title":"eFedLLM: Efficient LLM Inference Based on Federated Learning","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-12T13:43:55.194767Z"},"links":{"cited_paper":"/paper/2401.17555","citing_paper":"/paper/2411.16003"},"observation_digest":"sha256:c22e7bd310f48af0ef5556084943ce13b125c52ab8e589817743d54c5c91254b","observation_id":"067a93ef-c904-4577-934e-d66838e47f25","resolution":{"observed_at":"2026-08-12T13:43:55.194767Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1810.04805","last_updated":"2019-05-24T20:37:26Z","snapshot_observed_at":"2026-08-14T18:16:28.847993Z","submitted_at":"2018-10-11T00:50:01Z","title":"BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1810.04805","snapshot_observed_at":"2026-08-12T13:43:55.199322Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2411.16003","last_updated":"2024-11-24T22:50:02Z","snapshot_observed_at":"2026-08-13T22:40:43.804756Z","submitted_at":"2024-11-24T22:50:02Z","title":"eFedLLM: Efficient LLM Inference Based on Federated Learning","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-12T13:43:55.199322Z"},"links":{"cited_paper":"/paper/1810.04805","citing_paper":"/paper/2411.16003"},"observation_digest":"sha256:fe0b82a80ae296c447a0fd35e8b4603f913943967460135c96acf5934d067060","observation_id":"3711ec63-df08-45d3-8ec2-2fffc619ee75","resolution":{"observed_at":"2026-08-12T13:43:55.199322Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2209.05017","last_updated":"2022-09-12T04:25:01Z","snapshot_observed_at":"2026-08-16T16:33:18.842734Z","submitted_at":"2022-09-12T04:25:01Z","title":"An Investigation of Smart Contract for Collaborative Machine Learning Model Training","version":1},"cited_work":{"arxiv_id":"2209.05017","doi":null,"metadata_source":"pith","pith_arxiv_id":"2209.05017","snapshot_observed_at":"2026-08-12T13:43:55.472851Z","title":"An Investigation of Smart Contract for Collaborative Machine Learning Model Training","venue":"cs.LG","work_id":"3baf6a76-aabf-41ea-8e0c-bab7472c41e1","year":2022},"citing_paper":{"arxiv_id":"2411.16003","last_updated":"2024-11-24T22:50:02Z","snapshot_observed_at":"2026-08-13T22:40:43.804756Z","submitted_at":"2024-11-24T22:50:02Z","title":"eFedLLM: Efficient LLM Inference Based on Federated Learning","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-12T13:43:55.204262Z"},"links":{"cited_paper":"/paper/2209.05017","citing_paper":"/paper/2411.16003"},"observation_digest":"sha256:518c537214b5d6f533115a30b47fab9a29541ccb0db72f839661c4b0092e94ab","observation_id":"8f5c08d1-cdf7-44dc-8c38-90e9a81dbe59","resolution":{"observed_at":"2026-08-12T13:43:55.478356Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-12T13:43:56.005608Z","title":null,"venue":null,"work_id":"e62413ba-314a-4c01-a4f6-f3420d44796f","year":2022},"citing_paper":{"arxiv_id":"2411.16003","last_updated":"2024-11-24T22:50:02Z","snapshot_observed_at":"2026-08-13T22:40:43.804756Z","submitted_at":"2024-11-24T22:50:02Z","title":"eFedLLM: Efficient LLM Inference Based on Federated Learning","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-12T13:43:55.209009Z"},"links":{"citing_paper":"/paper/2411.16003"},"observation_digest":"sha256:d459014f4f606fdc30b936e2e7b57fbb66d3d5f97a45aa0488dfe061ec6aea11","observation_id":"5fc84117-e276-4584-b27f-f276b6557697","resolution":{"observed_at":"2026-08-12T13:43:56.010542Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-12T13:43:55.987481Z","title":null,"venue":null,"work_id":"09f8f431-0b24-4aa0-90f1-6c17720171b0","year":2020},"citing_paper":{"arxiv_id":"2411.16003","last_updated":"2024-11-24T22:50:02Z","snapshot_observed_at":"2026-08-13T22:40:43.804756Z","submitted_at":"2024-11-24T22:50:02Z","title":"eFedLLM: Efficient LLM Inference Based on Federated Learning","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-12T13:43:55.213363Z"},"links":{"citing_paper":"/paper/2411.16003"},"observation_digest":"sha256:551932e6b36a10d7384ebcd719ac0a21238b9999a6f735617eb4410e85441203","observation_id":"0f0578bd-2d1d-4bc6-8db9-4ae78df24a0c","resolution":{"observed_at":"2026-08-12T13:43:55.993243Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-12T13:43:55.966089Z","title":null,"venue":null,"work_id":"acdeabe6-0322-46b6-9188-1358836d1b25","year":2019},"citing_paper":{"arxiv_id":"2411.16003","last_updated":"2024-11-24T22:50:02Z","snapshot_observed_at":"2026-08-13T22:40:43.804756Z","submitted_at":"2024-11-24T22:50:02Z","title":"eFedLLM: Efficient LLM Inference Based on Federated Learning","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-12T13:43:55.217932Z"},"links":{"citing_paper":"/paper/2411.16003"},"observation_digest":"sha256:b2750ee303027226b43931e4eeb54d7b5046273d5192feebf2b98b3a1d6f2722","observation_id":"27a871e1-caf1-4699-97d7-a33f0b60a452","resolution":{"observed_at":"2026-08-12T13:43:55.972070Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2106.09685","last_updated":"2021-10-16T18:40:34Z","snapshot_observed_at":"2026-08-17T18:04:53.578114Z","submitted_at":"2021-06-17T17:37:18Z","title":"LoRA: Low-Rank Adaptation of Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2106.09685","snapshot_observed_at":"2026-08-12T13:43:55.222810Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2411.16003","last_updated":"2024-11-24T22:50:02Z","snapshot_observed_at":"2026-08-13T22:40:43.804756Z","submitted_at":"2024-11-24T22:50:02Z","title":"eFedLLM: Efficient LLM Inference Based on Federated Learning","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-12T13:43:55.222810Z"},"links":{"cited_paper":"/paper/2106.09685","citing_paper":"/paper/2411.16003"},"observation_digest":"sha256:4d81f41afb559ff54c03f135d2302c3d42a9513864d7b70df04d429e73a963a4","observation_id":"1d7c9cb9-8eda-4b63-9271-5bb806e65bbd","resolution":{"observed_at":"2026-08-12T13:43:55.222810Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2001.08361","last_updated":"2020-01-23T03:59:20Z","snapshot_observed_at":"2026-08-13T17:41:53.092611Z","submitted_at":"2020-01-23T03:59:20Z","title":"Scaling Laws for Neural Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2001.08361","snapshot_observed_at":"2026-08-12T13:43:55.228313Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2411.16003","last_updated":"2024-11-24T22:50:02Z","snapshot_observed_at":"2026-08-13T22:40:43.804756Z","submitted_at":"2024-11-24T22:50:02Z","title":"eFedLLM: Efficient LLM Inference Based on Federated Learning","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-12T13:43:55.228313Z"},"links":{"cited_paper":"/paper/2001.08361","citing_paper":"/paper/2411.16003"},"observation_digest":"sha256:57f83396e89a522eba9ffef1569ed439fd6cabbc38e0cefa709058fdc126ed34","observation_id":"7c915dbf-2a5a-4b51-816a-3c395e09e1d9","resolution":{"observed_at":"2026-08-12T13:43:55.228313Z","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":"2026-08-12T13:43:55.947103Z","title":null,"venue":null,"work_id":"cb160e86-9bd2-4c62-8019-d1fe26fa6e39","year":2020},"citing_paper":{"arxiv_id":"2411.16003","last_updated":"2024-11-24T22:50:02Z","snapshot_observed_at":"2026-08-13T22:40:43.804756Z","submitted_at":"2024-11-24T22:50:02Z","title":"eFedLLM: Efficient LLM Inference Based on Federated Learning","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-12T13:43:55.233886Z"},"links":{"citing_paper":"/paper/2411.16003"},"observation_digest":"sha256:c4580dbb357c3ab153d22a6124a90f93d489e000e39cc8b19fc5025d4a2a1ddc","observation_id":"de171ca0-fa59-4d1d-99a5-d0bddad3f07c","resolution":{"observed_at":"2026-08-12T13:43:55.952954Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-12T13:43:55.928470Z","title":null,"venue":null,"work_id":"b6f3b766-d4fb-493e-896a-077a716cdce2","year":2020},"citing_paper":{"arxiv_id":"2411.16003","last_updated":"2024-11-24T22:50:02Z","snapshot_observed_at":"2026-08-13T22:40:43.804756Z","submitted_at":"2024-11-24T22:50:02Z","title":"eFedLLM: Efficient LLM Inference Based on Federated Learning","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-12T13:43:55.238703Z"},"links":{"citing_paper":"/paper/2411.16003"},"observation_digest":"sha256:edd7d5d8998660e6ae06c80a02800c3a716891f3ba27c8e5d620a2c74085bbe5","observation_id":"ea43ee50-aef6-4599-af79-5d0e63d0968b","resolution":{"observed_at":"2026-08-12T13:43:55.934234Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-12T13:43:55.244012Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2411.16003","last_updated":"2024-11-24T22:50:02Z","snapshot_observed_at":"2026-08-13T22:40:43.804756Z","submitted_at":"2024-11-24T22:50:02Z","title":"eFedLLM: Efficient LLM Inference Based on Federated Learning","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-12T13:43:55.244012Z"},"links":{"citing_paper":"/paper/2411.16003"},"observation_digest":"sha256:dd839b650323f29fa90649ff8456fe7c7367134492c4a64011c78e0ad06aba71","observation_id":"253d12ad-8459-4e31-9c8e-472b88a19a8d","resolution":{"observed_at":"2026-08-12T13:43:55.244012Z","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":"2026-08-12T13:43:55.248989Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2411.16003","last_updated":"2024-11-24T22:50:02Z","snapshot_observed_at":"2026-08-13T22:40:43.804756Z","submitted_at":"2024-11-24T22:50:02Z","title":"eFedLLM: Efficient LLM Inference Based on Federated Learning","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-12T13:43:55.248989Z"},"links":{"citing_paper":"/paper/2411.16003"},"observation_digest":"sha256:739188915060c787d2b087d7150f9166a7d287e1a998a1e9ed75712b2f1a155e","observation_id":"934eeed5-cdeb-45aa-aacd-f9d915dcf640","resolution":{"observed_at":"2026-08-12T13:43:55.248989Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.00240","last_updated":"2024-06-01T00:11:09Z","snapshot_observed_at":"2026-08-16T13:47:15.344802Z","submitted_at":"2024-06-01T00:11:09Z","title":"Exploring Vulnerabilities and Protections in Large Language Models: A Survey","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.00240","snapshot_observed_at":"2026-08-12T13:43:55.254209Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.16003","last_updated":"2024-11-24T22:50:02Z","snapshot_observed_at":"2026-08-13T22:40:43.804756Z","submitted_at":"2024-11-24T22:50:02Z","title":"eFedLLM: Efficient LLM Inference Based on Federated Learning","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-12T13:43:55.254209Z"},"links":{"cited_paper":"/paper/2406.00240","citing_paper":"/paper/2411.16003"},"observation_digest":"sha256:3131af5dd68d6b077a153c0bf1803ae0b69ea94542d53cd8cb19310d4cc2de25","observation_id":"803b4d65-225c-42ed-9a7d-9b0781d55408","resolution":{"observed_at":"2026-08-12T13:43:55.254209Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.21695","last_updated":"2024-10-29T03:25:20Z","snapshot_observed_at":"2026-08-17T11:42:24.789206Z","submitted_at":"2024-10-29T03:25:20Z","title":"CFSafety: Comprehensive Fine-grained Safety Assessment for LLMs","version":1},"cited_work":{"arxiv_id":"2410.21695","doi":null,"metadata_source":"pith","pith_arxiv_id":"2410.21695","snapshot_observed_at":"2026-08-12T13:43:55.394722Z","title":"CFSafety: Comprehensive Fine-grained Safety Assessment for LLMs","venue":"cs.CL","work_id":"f52cbf44-0423-4096-8c6d-6e3c58158269","year":2024},"citing_paper":{"arxiv_id":"2411.16003","last_updated":"2024-11-24T22:50:02Z","snapshot_observed_at":"2026-08-13T22:40:43.804756Z","submitted_at":"2024-11-24T22:50:02Z","title":"eFedLLM: Efficient LLM Inference Based on Federated Learning","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-12T13:43:55.259659Z"},"links":{"cited_paper":"/paper/2410.21695","citing_paper":"/paper/2411.16003"},"observation_digest":"sha256:50f5e43e7018aee12396921533077f6f3f3fd11db14d0a9237ff14439e8e9524","observation_id":"a86ea131-d8b7-43d9-ac7d-fe897cd27e30","resolution":{"observed_at":"2026-08-12T13:43:55.400712Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-12T13:43:55.879625Z","title":null,"venue":null,"work_id":"61731568-a3b6-4d79-af38-262d418cc5f8","year":2019},"citing_paper":{"arxiv_id":"2411.16003","last_updated":"2024-11-24T22:50:02Z","snapshot_observed_at":"2026-08-13T22:40:43.804756Z","submitted_at":"2024-11-24T22:50:02Z","title":"eFedLLM: Efficient LLM Inference Based on Federated Learning","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-12T13:43:55.265418Z"},"links":{"citing_paper":"/paper/2411.16003"},"observation_digest":"sha256:a0e588103b3a48d854b686a8b128629f9e51d9eb09f6aa13e70860625db35e4b","observation_id":"5bfd6db2-a382-481a-be27-5c98d5800b9d","resolution":{"observed_at":"2026-08-12T13:43:55.886373Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2104.07540","last_updated":"2021-10-04T14:56:28Z","snapshot_observed_at":"2026-08-17T17:20:12.540247Z","submitted_at":"2021-04-15T15:51:41Z","title":"Generating Datasets with Pretrained Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2104.07540","snapshot_observed_at":"2026-08-12T13:43:55.270451Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2411.16003","last_updated":"2024-11-24T22:50:02Z","snapshot_observed_at":"2026-08-13T22:40:43.804756Z","submitted_at":"2024-11-24T22:50:02Z","title":"eFedLLM: Efficient LLM Inference Based on Federated Learning","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-12T13:43:55.270451Z"},"links":{"cited_paper":"/paper/2104.07540","citing_paper":"/paper/2411.16003"},"observation_digest":"sha256:333dd15507fd1c0e7b032ec66f4d0c1e278e8164be8859d6e0054c1b07ccafc4","observation_id":"351bafd1-0c59-44a6-bd1c-f8bfbd84f416","resolution":{"observed_at":"2026-08-12T13:43:55.270451Z","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":"2026-08-12T13:43:55.860805Z","title":null,"venue":null,"work_id":"f059da2a-88b1-493a-bfd0-fa1e21ed669f","year":2024},"citing_paper":{"arxiv_id":"2411.16003","last_updated":"2024-11-24T22:50:02Z","snapshot_observed_at":"2026-08-13T22:40:43.804756Z","submitted_at":"2024-11-24T22:50:02Z","title":"eFedLLM: Efficient LLM Inference Based on Federated Learning","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-12T13:43:55.275714Z"},"links":{"citing_paper":"/paper/2411.16003"},"observation_digest":"sha256:83c863dc430eaa0accc4fc193a24350e34645ff2a4d98e9ac4d4bef157ef5660","observation_id":"c5e0b3eb-d8fa-4dd1-a19d-f44cee44906f","resolution":{"observed_at":"2026-08-12T13:43:55.866179Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-12T13:43:55.841847Z","title":null,"venue":null,"work_id":"db371afe-8823-4ee4-8abc-d51b11431495","year":2019},"citing_paper":{"arxiv_id":"2411.16003","last_updated":"2024-11-24T22:50:02Z","snapshot_observed_at":"2026-08-13T22:40:43.804756Z","submitted_at":"2024-11-24T22:50:02Z","title":"eFedLLM: Efficient LLM Inference Based on Federated Learning","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-12T13:43:55.281134Z"},"links":{"citing_paper":"/paper/2411.16003"},"observation_digest":"sha256:b79c772e2a904dc84227faa76518281d6c3d2e66bb448a88063f9edba29628ce","observation_id":"dc430483-1dfb-4d9c-8f85-9303a0f757ae","resolution":{"observed_at":"2026-08-12T13:43:55.848244Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-12T13:43:55.287035Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2411.16003","last_updated":"2024-11-24T22:50:02Z","snapshot_observed_at":"2026-08-13T22:40:43.804756Z","submitted_at":"2024-11-24T22:50:02Z","title":"eFedLLM: Efficient LLM Inference Based on Federated Learning","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-12T13:43:55.287035Z"},"links":{"citing_paper":"/paper/2411.16003"},"observation_digest":"sha256:c5b2e58babebfc6e836d82c4bd81f71bfa8d3962526167aac8fa2eff4c8f3d98","observation_id":"e9846436-e809-41c4-b6b3-20b2aa9ed815","resolution":{"observed_at":"2026-08-12T13:43:55.287035Z","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":"2026-08-12T13:43:55.808239Z","title":null,"venue":null,"work_id":"b6f51b47-e3fb-474e-bb6c-e852ab2a791d","year":2019},"citing_paper":{"arxiv_id":"2411.16003","last_updated":"2024-11-24T22:50:02Z","snapshot_observed_at":"2026-08-13T22:40:43.804756Z","submitted_at":"2024-11-24T22:50:02Z","title":"eFedLLM: Efficient LLM Inference Based on Federated Learning","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-12T13:43:55.292904Z"},"links":{"citing_paper":"/paper/2411.16003"},"observation_digest":"sha256:e4017041777048c9284a3ac1317323fd3f61c0ee8513c884ca68ccd15a47e689","observation_id":"4d4d7513-0277-4537-8f47-387d38e80ad4","resolution":{"observed_at":"2026-08-12T13:43:55.817317Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1093/nsr/nwad083","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T13:43:55.340744Z","title":null,"venue":null,"work_id":"a7ab6f2e-94a9-4999-ab8e-1bc4dbdbf5e3","year":2023},"citing_paper":{"arxiv_id":"2411.16003","last_updated":"2024-11-24T22:50:02Z","snapshot_observed_at":"2026-08-13T22:40:43.804756Z","submitted_at":"2024-11-24T22:50:02Z","title":"eFedLLM: Efficient LLM Inference Based on Federated Learning","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-12T13:43:55.297692Z"},"links":{"citing_paper":"/paper/2411.16003"},"observation_digest":"sha256:c695a301132dcbf97787197527957f94a0c64bc1f16b0c79ab4b5bc5dc83a498","observation_id":"afd8aebe-5d1e-44b5-82d9-08c669fa7d8e","resolution":{"observed_at":"2026-08-12T13:43:55.346508Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-12T13:43:55.787438Z","title":null,"venue":null,"work_id":"840409e0-09d1-4ecc-843e-7804edfb75be","year":2021},"citing_paper":{"arxiv_id":"2411.16003","last_updated":"2024-11-24T22:50:02Z","snapshot_observed_at":"2026-08-13T22:40:43.804756Z","submitted_at":"2024-11-24T22:50:02Z","title":"eFedLLM: Efficient LLM Inference Based on Federated Learning","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-12T13:43:55.302873Z"},"links":{"citing_paper":"/paper/2411.16003"},"observation_digest":"sha256:c7bd0f0cbbc906c4f483fd444b59b8821836bbe81a094a587533610d7fe09b1c","observation_id":"c55f1c20-2173-4afb-b8b1-e0d98013a2dd","resolution":{"observed_at":"2026-08-12T13:43:55.792527Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2411.16003","last_updated":"2024-11-24T22:50:02Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-13T22:40:43.804756Z","submitted_at":"2024-11-24T22:50:02Z","title":"eFedLLM: Efficient LLM Inference Based on Federated Learning"},"reference_resolution":{"displayed":31,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":27,"verified_exact":3,"verified_fuzzy":0},"total_outbound_references":31},"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":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"thesis":"As of 17 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 1 inbound Pith citation observation for arXiv:2411.16003."}