{"as_of":"2026-08-09T16:53:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:c9f7e8c976c919e7f98999a00c872fc2753655fe987cf71c7acba63cbf6d6ec2","coverage":[{"denominator":17,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":17,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T18:20:53.640322Z","state":"measured"},{"denominator":19,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":19,"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":"2026-05-21T15:09:25.818449Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-21T15:10:16.528858Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2507.08505","last_updated":"2025-07-14T08:25:14Z","snapshot_observed_at":"2026-08-07T08:50:41.054794Z","submitted_at":"2025-07-11T11:30:57Z","title":"Efficient Deployment of Vision-Language Models on Mobile Devices: A Case Study on OnePlus 13R","version":2},"cited_work":{"arxiv_id":"2507.08505","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2507.08505","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"R., Pan, Y ., and Kashyap, S","venue":null,"work_id":"9d8d0bc4-74ac-4188-82b1-fe13246d72f1","year":2025},"citing_paper":{"arxiv_id":"2601.21531","last_updated":"2026-05-17T03:22:07Z","snapshot_observed_at":"2026-07-06T22:43:26.250071Z","submitted_at":"2026-01-29T10:47:21Z","title":"On the Adversarial Robustness of Large Vision-Language Models under Visual Token Compression","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-21T15:09:25.818449Z"},"links":{"cited_paper":"/paper/2507.08505","citing_paper":"/paper/2601.21531"},"observation_digest":"sha256:fb527a17d66f71802b9e61fade5fc2a4e6021f55938a48836a36f8bff8c47576","observation_id":"e49eea97-df3d-4f89-bd72-36e15061fbb6","resolution":{"observed_at":"2026-05-21T15:10:16.531308Z","resolver_source":"arxiv_id","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"}},{"citation":{"cited_paper":{"arxiv_id":"2507.08505","last_updated":"2025-07-14T08:25:14Z","snapshot_observed_at":"2026-08-07T08:50:41.054794Z","submitted_at":"2025-07-11T11:30:57Z","title":"Efficient Deployment of Vision-Language Models on Mobile Devices: A Case Study on OnePlus 13R","version":2},"cited_work":{"arxiv_id":"2507.08505","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2507.08505","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"R., Pan, Y ., and Kashyap, S","venue":null,"work_id":"9d8d0bc4-74ac-4188-82b1-fe13246d72f1","year":2025},"citing_paper":{"arxiv_id":"2604.26508","last_updated":"2026-04-29T10:16:06Z","snapshot_observed_at":"2026-08-05T14:54:14.668473Z","submitted_at":"2026-04-29T10:16:06Z","title":"Progressive Semantic Communication for Efficient Edge-Cloud Vision-Language Models","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-07T10:45:20.829708Z"},"links":{"cited_paper":"/paper/2507.08505","citing_paper":"/paper/2604.26508"},"observation_digest":"sha256:d63f793b03f3f893a17e5e3a796c2a0450713015bbc75a31df644d3788d3be98","observation_id":"c821ae7c-d33c-4712-a469-b2b649ef2ddd","resolution":{"observed_at":"2026-05-12T09:31:25.578099Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"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/2507.08505/citation-record","integrity":"/paper/2507.08505/integrity","json":"/paper/2507.08505/citation-record.json","paper":"/paper/2507.08505"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2407.08303","last_updated":"2024-11-24T13:14:47Z","snapshot_observed_at":"2026-08-09T13:25:19.616883Z","submitted_at":"2024-07-11T08:48:06Z","title":"DenseFusion-1M: Merging Vision Experts for Comprehensive Multimodal Perception","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.08303","snapshot_observed_at":"2026-08-06T18:20:53.520305Z","title":"Densefusion-1m: Merging vision experts for comprehensive multimodal perception","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.08505","last_updated":"2025-07-14T08:25:14Z","snapshot_observed_at":"2026-08-07T08:50:41.054794Z","submitted_at":"2025-07-11T11:30:57Z","title":"Efficient Deployment of Vision-Language Models on Mobile Devices: A Case Study on OnePlus 13R","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T18:20:53.520305Z"},"links":{"cited_paper":"/paper/2407.08303","citing_paper":"/paper/2507.08505"},"observation_digest":"sha256:4b33dff992000c1a34bf0ccf0be7f2a7af4ce129d28846a7203105a90306bbd9","observation_id":"75fc37fc-9c21-4d22-829f-a0592d761a66","resolution":{"observed_at":"2026-08-06T18:20:53.520305Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.15116","last_updated":"2024-02-23T06:04:23Z","snapshot_observed_at":"2026-07-06T17:34:24.337596Z","submitted_at":"2024-02-23T06:04:23Z","title":"Large Multimodal Agents: A Survey","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.15116","snapshot_observed_at":"2026-08-06T18:20:53.530368Z","title":"Large multimodal agents: A survey.arXiv preprint arXiv:2402.15116, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.08505","last_updated":"2025-07-14T08:25:14Z","snapshot_observed_at":"2026-08-07T08:50:41.054794Z","submitted_at":"2025-07-11T11:30:57Z","title":"Efficient Deployment of Vision-Language Models on Mobile Devices: A Case Study on OnePlus 13R","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T18:20:53.530368Z"},"links":{"cited_paper":"/paper/2402.15116","citing_paper":"/paper/2507.08505"},"observation_digest":"sha256:97b81333f36ce83a3428403b1b000bb609ed58f6e9da458da173af4ed74ff16a","observation_id":"6f975698-f196-4643-939a-8f482f3ce123","resolution":{"observed_at":"2026-08-06T18:20:53.530368Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.06282","last_updated":"2024-12-12T12:24:18Z","snapshot_observed_at":"2026-08-06T16:06:48.213787Z","submitted_at":"2024-06-10T14:01:21Z","title":"PowerInfer-2: Fast Large Language Model Inference on a Smartphone","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.06282","snapshot_observed_at":"2026-08-06T18:20:53.546644Z","title":"Powerinfer-2: Fast large language model inference on a smartphone","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.08505","last_updated":"2025-07-14T08:25:14Z","snapshot_observed_at":"2026-08-07T08:50:41.054794Z","submitted_at":"2025-07-11T11:30:57Z","title":"Efficient Deployment of Vision-Language Models on Mobile Devices: A Case Study on OnePlus 13R","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T18:20:53.546644Z"},"links":{"cited_paper":"/paper/2406.06282","citing_paper":"/paper/2507.08505"},"observation_digest":"sha256:e923ad76f2fdccfab38d5393d61b16db8eaef93de9c08844c5f713f837560ee6","observation_id":"0b428182-fc7c-427b-a729-c682db3579a5","resolution":{"observed_at":"2026-08-06T18:20:53.546644Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.05858","last_updated":"2024-12-15T15:26:41Z","snapshot_observed_at":"2026-08-07T08:50:10.407800Z","submitted_at":"2024-07-08T12:20:45Z","title":"Fast On-device LLM Inference with NPUs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.05858","snapshot_observed_at":"2026-08-06T18:20:53.553489Z","title":"Empowering 1000 tokens/second on-device llm prefilling with mllm-npu","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.08505","last_updated":"2025-07-14T08:25:14Z","snapshot_observed_at":"2026-08-07T08:50:41.054794Z","submitted_at":"2025-07-11T11:30:57Z","title":"Efficient Deployment of Vision-Language Models on Mobile Devices: A Case Study on OnePlus 13R","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T18:20:53.553489Z"},"links":{"cited_paper":"/paper/2407.05858","citing_paper":"/paper/2507.08505"},"observation_digest":"sha256:2a2469b8f89fc1d6d05c28806dbcbc9e6fb60ed4ef053e3c4eaa4b9de4a9ab0d","observation_id":"1a78480c-e864-413e-b8bf-b0e5b0bb2613","resolution":{"observed_at":"2026-08-06T18:20:53.553489Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2308.15030","last_updated":"2024-05-29T08:25:03Z","snapshot_observed_at":"2026-08-06T12:44:13.816721Z","submitted_at":"2023-08-29T05:25:21Z","title":"SwapMoE: Serving Off-the-shelf MoE-based Large Language Models with Tunable Memory Budget","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.15030","snapshot_observed_at":"2026-08-06T18:20:53.562080Z","title":"Swapmoe: Serving off-the-shelf moe-based large language models with tunable memory budget","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.08505","last_updated":"2025-07-14T08:25:14Z","snapshot_observed_at":"2026-08-07T08:50:41.054794Z","submitted_at":"2025-07-11T11:30:57Z","title":"Efficient Deployment of Vision-Language Models on Mobile Devices: A Case Study on OnePlus 13R","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T18:20:53.562080Z"},"links":{"cited_paper":"/paper/2308.15030","citing_paper":"/paper/2507.08505"},"observation_digest":"sha256:3f7308d4482a7f5163aaeb99e1ae04273e47f1be3584d296dd27e4d84bed6587","observation_id":"c42b0a87-959e-45bf-aacd-6126a805075a","resolution":{"observed_at":"2026-08-06T18:20:53.562080Z","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":"2026-08-06T18:20:54.088113Z","title":"llama.cpp: Efficient inference of llama models","venue":null,"work_id":"3362028d-38b3-48dc-8f1b-556098a697e4","year":2023},"citing_paper":{"arxiv_id":"2507.08505","last_updated":"2025-07-14T08:25:14Z","snapshot_observed_at":"2026-08-07T08:50:41.054794Z","submitted_at":"2025-07-11T11:30:57Z","title":"Efficient Deployment of Vision-Language Models on Mobile Devices: A Case Study on OnePlus 13R","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T18:20:53.569560Z"},"links":{"citing_paper":"/paper/2507.08505"},"observation_digest":"sha256:063246a2f6c4b350af32a6c16396d5f2dae3ab8f8e13ad3d7a5386858c7e033f","observation_id":"aec358dd-da61-41c0-857c-663e8702bc61","resolution":{"observed_at":"2026-08-06T18:20:54.099816Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:20:54.052562Z","title":null,"venue":null,"work_id":"f645cc3a-dfdb-4c42-a588-a751407664da","year":2024},"citing_paper":{"arxiv_id":"2507.08505","last_updated":"2025-07-14T08:25:14Z","snapshot_observed_at":"2026-08-07T08:50:41.054794Z","submitted_at":"2025-07-11T11:30:57Z","title":"Efficient Deployment of Vision-Language Models on Mobile Devices: A Case Study on OnePlus 13R","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T18:20:53.577311Z"},"links":{"citing_paper":"/paper/2507.08505"},"observation_digest":"sha256:dbd5bdccf9373ed56f4bd8afc19b21a7b0d38da0229222a5bc30bb1c3f13f007","observation_id":"8bad181b-2ad6-464e-a59e-c7f9cce8d3bc","resolution":{"observed_at":"2026-08-06T18:20:54.069315Z","resolver_source":"raw_fallback","status":"unresolved"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:20:54.019524Z","title":"mllm: On-device multimodal llm inference framework","venue":null,"work_id":"9bea7d8a-0d68-48d6-b7ab-83b29b2e10ab","year":2024},"citing_paper":{"arxiv_id":"2507.08505","last_updated":"2025-07-14T08:25:14Z","snapshot_observed_at":"2026-08-07T08:50:41.054794Z","submitted_at":"2025-07-11T11:30:57Z","title":"Efficient Deployment of Vision-Language Models on Mobile Devices: A Case Study on OnePlus 13R","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T18:20:53.583039Z"},"links":{"citing_paper":"/paper/2507.08505"},"observation_digest":"sha256:33b94f8772d3f46af3fd4cd1e7434b75f3a55d52d0fc48c37c154af0b6b9260e","observation_id":"b54822bb-a506-4592-a8f7-908cc4f01434","resolution":{"observed_at":"2026-08-06T18:20:54.027213Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":{"arxiv_id":"2304.08485","last_updated":"2023-12-11T17:46:14Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-04-17T17:59:25Z","title":"Visual Instruction Tuning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.08485","snapshot_observed_at":"2026-08-06T18:20:53.589256Z","title":"Llava: Visual instruction tuning","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.08505","last_updated":"2025-07-14T08:25:14Z","snapshot_observed_at":"2026-08-07T08:50:41.054794Z","submitted_at":"2025-07-11T11:30:57Z","title":"Efficient Deployment of Vision-Language Models on Mobile Devices: A Case Study on OnePlus 13R","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T18:20:53.589256Z"},"links":{"cited_paper":"/paper/2304.08485","citing_paper":"/paper/2507.08505"},"observation_digest":"sha256:ad2a8d99735acca15f911a99bfe788df5a15a54494ed43aac335dfce0a666379","observation_id":"0f6c3968-16de-4113-812a-3430a7501f25","resolution":{"observed_at":"2026-08-06T18:20:53.589256Z","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":"2026-08-06T18:20:53.993067Z","title":"Mobilevlm: An efficient vision-language model for mobile devices","venue":null,"work_id":"00ff441a-c77b-40df-9972-c1a154ffbd22","year":2024},"citing_paper":{"arxiv_id":"2507.08505","last_updated":"2025-07-14T08:25:14Z","snapshot_observed_at":"2026-08-07T08:50:41.054794Z","submitted_at":"2025-07-11T11:30:57Z","title":"Efficient Deployment of Vision-Language Models on Mobile Devices: A Case Study on OnePlus 13R","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T18:20:53.594658Z"},"links":{"citing_paper":"/paper/2507.08505"},"observation_digest":"sha256:a4c981b164c863bcc778a05ae8d9a9b5d269be4d041358a94a6c85da8da3076b","observation_id":"50ae9b4b-2809-41e9-8dd6-8d760fc22283","resolution":{"observed_at":"2026-08-06T18:20:54.000329Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":{"arxiv_id":"2405.12107","last_updated":"2024-05-30T02:47:10Z","snapshot_observed_at":"2026-07-06T18:16:46.770981Z","submitted_at":"2024-05-20T15:23:19Z","title":"Imp: Highly Capable Large Multimodal Models for Mobile Devices","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.12107","snapshot_observed_at":"2026-08-06T18:20:53.600924Z","title":"Imp: Highly capable large multimodal models for mobile devices","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.08505","last_updated":"2025-07-14T08:25:14Z","snapshot_observed_at":"2026-08-07T08:50:41.054794Z","submitted_at":"2025-07-11T11:30:57Z","title":"Efficient Deployment of Vision-Language Models on Mobile Devices: A Case Study on OnePlus 13R","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T18:20:53.600924Z"},"links":{"cited_paper":"/paper/2405.12107","citing_paper":"/paper/2507.08505"},"observation_digest":"sha256:7163fd6a0c7983bd422abfb5f07a83a3fc32d1c6d56df0d1f4f91e1ced7ee278","observation_id":"5371ee33-436e-4348-8600-c6c0b5f10cda","resolution":{"observed_at":"2026-08-06T18:20:53.600924Z","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":"2026-08-06T18:20:53.966874Z","title":"Gptq: Accurate post-training quantization for generative pretrained transformers","venue":null,"work_id":"bb2ae248-bc96-4832-89f0-efdb60b5d669","year":2022},"citing_paper":{"arxiv_id":"2507.08505","last_updated":"2025-07-14T08:25:14Z","snapshot_observed_at":"2026-08-07T08:50:41.054794Z","submitted_at":"2025-07-11T11:30:57Z","title":"Efficient Deployment of Vision-Language Models on Mobile Devices: A Case Study on OnePlus 13R","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T18:20:53.607060Z"},"links":{"citing_paper":"/paper/2507.08505"},"observation_digest":"sha256:e8e0fa87c84021a145d259da5787a9f96b06334bdd7cab3bc404086e3ce738d7","observation_id":"8cecdc0f-a379-4c9b-ab4d-abd5e6baebde","resolution":{"observed_at":"2026-08-06T18:20:53.974844Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":{"arxiv_id":"2306.00978","last_updated":"2026-04-25T06:58:16Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-06-01T17:59:10Z","title":"AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.00978","snapshot_observed_at":"2026-08-06T18:20:53.614221Z","title":"Awq: Activation-aware weight quanti- zation for llms","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.08505","last_updated":"2025-07-14T08:25:14Z","snapshot_observed_at":"2026-08-07T08:50:41.054794Z","submitted_at":"2025-07-11T11:30:57Z","title":"Efficient Deployment of Vision-Language Models on Mobile Devices: A Case Study on OnePlus 13R","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T18:20:53.614221Z"},"links":{"cited_paper":"/paper/2306.00978","citing_paper":"/paper/2507.08505"},"observation_digest":"sha256:0f1b7c22c783e184e82fb6e987d8ebf7c0be2e404b9b9fe382ad9648c993e073","observation_id":"9904750c-2caf-4e56-9628-c8946d734eb3","resolution":{"observed_at":"2026-08-06T18:20:53.614221Z","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":"2026-08-06T18:20:53.942411Z","title":"Learning both weights and connections for efficient neural networks","venue":null,"work_id":"ebef1258-da23-4ab8-8bf8-c4e4555a79a8","year":2015},"citing_paper":{"arxiv_id":"2507.08505","last_updated":"2025-07-14T08:25:14Z","snapshot_observed_at":"2026-08-07T08:50:41.054794Z","submitted_at":"2025-07-11T11:30:57Z","title":"Efficient Deployment of Vision-Language Models on Mobile Devices: A Case Study on OnePlus 13R","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T18:20:53.621874Z"},"links":{"citing_paper":"/paper/2507.08505"},"observation_digest":"sha256:82d9b07bb734b29a27d5e241a4a5a3067d586c2864597ff59edd546814641a47","observation_id":"5427bdbc-b356-4fc1-9b1e-151c1803ddb2","resolution":{"observed_at":"2026-08-06T18:20:53.950668Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":{"arxiv_id":"1503.02531","last_updated":"2015-03-09T15:44:49Z","snapshot_observed_at":"2026-07-06T04:11:24.157003Z","submitted_at":"2015-03-09T15:44:49Z","title":"Distilling the Knowledge in a Neural Network","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1503.02531","snapshot_observed_at":"2026-08-06T18:20:53.627325Z","title":"Distilling the knowledge in a neural network","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2507.08505","last_updated":"2025-07-14T08:25:14Z","snapshot_observed_at":"2026-08-07T08:50:41.054794Z","submitted_at":"2025-07-11T11:30:57Z","title":"Efficient Deployment of Vision-Language Models on Mobile Devices: A Case Study on OnePlus 13R","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T18:20:53.627325Z"},"links":{"cited_paper":"/paper/1503.02531","citing_paper":"/paper/2507.08505"},"observation_digest":"sha256:986572c683d942e8310f134ca4d4147de63b2cfdeb699ed2e6a51fe2bf6dd622","observation_id":"619e70b8-35e7-429d-b039-91618cb9a3cf","resolution":{"observed_at":"2026-08-06T18:20:53.627325Z","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":"2026-08-06T18:20:53.907234Z","title":"Fu, Stefano Ermon, Atri Rudra, and Christopher Ré","venue":null,"work_id":"4f8a125f-8298-4476-b098-10a118166814","year":2022},"citing_paper":{"arxiv_id":"2507.08505","last_updated":"2025-07-14T08:25:14Z","snapshot_observed_at":"2026-08-07T08:50:41.054794Z","submitted_at":"2025-07-11T11:30:57Z","title":"Efficient Deployment of Vision-Language Models on Mobile Devices: A Case Study on OnePlus 13R","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T18:20:53.633849Z"},"links":{"citing_paper":"/paper/2507.08505"},"observation_digest":"sha256:4497b67570e759d965e49171604ceb8198bff5e1e43f4b8baa848b60d07f541f","observation_id":"e1d43d0f-ccd4-4afc-984e-af0d9b6b9c7c","resolution":{"observed_at":"2026-08-06T18:20:53.920708Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":{"arxiv_id":"2412.10302","last_updated":"2024-12-13T17:37:48Z","snapshot_observed_at":"2026-08-07T03:01:29.031129Z","submitted_at":"2024-12-13T17:37:48Z","title":"DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.10302","snapshot_observed_at":"2026-08-06T18:20:53.640322Z","title":"Deepseek-vl 2: Mixture- of-experts vision-language models for advanced multimodal understanding","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.08505","last_updated":"2025-07-14T08:25:14Z","snapshot_observed_at":"2026-08-07T08:50:41.054794Z","submitted_at":"2025-07-11T11:30:57Z","title":"Efficient Deployment of Vision-Language Models on Mobile Devices: A Case Study on OnePlus 13R","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T18:20:53.640322Z"},"links":{"cited_paper":"/paper/2412.10302","citing_paper":"/paper/2507.08505"},"observation_digest":"sha256:2ad960dae73dc15261e2c42a2ca65912287885333f74df0ff4269e1ab9aaeeca","observation_id":"0cf8702f-7a58-4cd4-9568-d9fee0740a68","resolution":{"observed_at":"2026-08-06T18:20:53.640322Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2507.08505","last_updated":"2025-07-14T08:25:14Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-07T08:50:41.054794Z","submitted_at":"2025-07-11T11:30:57Z","title":"Efficient Deployment of Vision-Language Models on Mobile Devices: A Case Study on OnePlus 13R"},"reference_resolution":{"displayed":17,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":11,"verified_exact":0,"verified_fuzzy":6},"total_outbound_references":17},"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 17 of 17 outbound references and 2 inbound Pith citation observations for arXiv:2507.08505."}