{"as_of":"2026-08-20T16:38:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:b5e437cfd9d8a48d92eb690a5982acd1bfeff080a723f7d661062266a1685ae9","coverage":[{"denominator":38,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":38,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-05T16:31:34.399190Z","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":"2026-08-20T06:33:59.587034+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":"2026-07-13T05:10:19.996629Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2508.18430","last_updated":"2025-08-25T19:22:16Z","snapshot_observed_at":"2026-08-13T20:43:30.915084Z","submitted_at":"2025-08-25T19:22:16Z","title":"CLARIFY: A Specialist-Generalist Framework for Accurate and Lightweight Dermatological Visual Question Answering","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2508.18430","snapshot_observed_at":"2026-07-13T05:10:19.996629Z","title":"Clarify: A specialist-generalist framework for accurate and lightweight dermatological visual question answering.arXiv preprint arXiv:2508.18430, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.09135","last_updated":"2026-07-10T06:47:02Z","snapshot_observed_at":"2026-08-14T07:58:46.067403Z","submitted_at":"2026-07-10T06:47:02Z","title":"Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-07-13T05:10:19.996629Z"},"links":{"cited_paper":"/paper/2508.18430","citing_paper":"/paper/2607.09135"},"observation_digest":"sha256:d6d26ca3434f1b056beda8740077ea6de1b9584463bf67fe978c911407fcb83c","observation_id":"476139ac-6c04-480f-be32-8e0ddd2a7e18","resolution":{"observed_at":"2026-07-13T05:10:19.996629Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2508.18430/citation-record","integrity":"/paper/2508.18430/integrity","json":"/paper/2508.18430/citation-record.json","paper":"/paper/2508.18430"},"outbound":[{"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":"2026-08-05T16:31:34.195134Z","title":"Visual instruction tuning,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2508.18430","last_updated":"2025-08-25T19:22:16Z","snapshot_observed_at":"2026-08-13T20:43:30.915084Z","submitted_at":"2025-08-25T19:22:16Z","title":"CLARIFY: A Specialist-Generalist Framework for Accurate and Lightweight Dermatological Visual Question Answering","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-05T16:31:34.195134Z"},"links":{"cited_paper":"/paper/2304.08485","citing_paper":"/paper/2508.18430"},"observation_digest":"sha256:c68af3cfd19e950686a1e97a14ea301bc7d061db62571ff8b7f622f95635e1e7","observation_id":"2f67ea1e-4c20-468b-a9ec-732d5b2c0993","resolution":{"observed_at":"2026-08-05T16:31:34.195134Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2308.12966","last_updated":"2023-10-13T02:41:28Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-08-24T17:59:17Z","title":"Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.12966","snapshot_observed_at":"2026-08-05T16:31:34.201791Z","title":"Qwen-vl: A versatile vision-language model for understanding, localization, text reading, and beyond,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2508.18430","last_updated":"2025-08-25T19:22:16Z","snapshot_observed_at":"2026-08-13T20:43:30.915084Z","submitted_at":"2025-08-25T19:22:16Z","title":"CLARIFY: A Specialist-Generalist Framework for Accurate and Lightweight Dermatological Visual Question Answering","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-05T16:31:34.201791Z"},"links":{"cited_paper":"/paper/2308.12966","citing_paper":"/paper/2508.18430"},"observation_digest":"sha256:e7a4eec408ee06923172322cc651938712aa0285c10dcfbbf996c3dc30f79e43","observation_id":"6584dcf1-32a9-4e2d-9886-e9d277e0a25e","resolution":{"observed_at":"2026-08-05T16:31:34.201791Z","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":"2026-08-05T16:31:35.335244Z","title":"Vision-language models for vision tasks: A survey,","venue":null,"work_id":"f5c792b0-d9d8-4bf4-8894-df445a61ba90","year":2024},"citing_paper":{"arxiv_id":"2508.18430","last_updated":"2025-08-25T19:22:16Z","snapshot_observed_at":"2026-08-13T20:43:30.915084Z","submitted_at":"2025-08-25T19:22:16Z","title":"CLARIFY: A Specialist-Generalist Framework for Accurate and Lightweight Dermatological Visual Question Answering","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-05T16:31:34.208936Z"},"links":{"citing_paper":"/paper/2508.18430"},"observation_digest":"sha256:9a8b6cbf018a1eaf35429b695a2db3670a6c5f6a60749a0a030b84f610bff93d","observation_id":"e4dc143b-df8c-4247-aaa5-0dded723f2d6","resolution":{"observed_at":"2026-08-05T16:31:35.340792Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.10799","last_updated":"2023-05-18T08:19:33Z","snapshot_observed_at":"2026-08-16T20:39:35.396650Z","submitted_at":"2023-05-18T08:19:33Z","title":"MedBLIP: Bootstrapping Language-Image Pre-training from 3D Medical Images and Texts","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.10799","snapshot_observed_at":"2026-08-05T16:31:34.214793Z","title":"Medblip: Bootstrapping language-image pre-training from 3d medical images and texts,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2508.18430","last_updated":"2025-08-25T19:22:16Z","snapshot_observed_at":"2026-08-13T20:43:30.915084Z","submitted_at":"2025-08-25T19:22:16Z","title":"CLARIFY: A Specialist-Generalist Framework for Accurate and Lightweight Dermatological Visual Question Answering","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-05T16:31:34.214793Z"},"links":{"cited_paper":"/paper/2305.10799","citing_paper":"/paper/2508.18430"},"observation_digest":"sha256:9d576f299f510763bc3a7fdfed95d288f8d59b3913bcf3ba6eab3830c0d40b72","observation_id":"0b60dd36-81d6-4508-aeaf-f7696fd045e6","resolution":{"observed_at":"2026-08-05T16:31:34.214793Z","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":"2026-08-05T16:31:35.317871Z","title":"Towards generalist biomedical ai,","venue":null,"work_id":"9f89da12-4b83-4446-b704-befe6e2b297b","year":2024},"citing_paper":{"arxiv_id":"2508.18430","last_updated":"2025-08-25T19:22:16Z","snapshot_observed_at":"2026-08-13T20:43:30.915084Z","submitted_at":"2025-08-25T19:22:16Z","title":"CLARIFY: A Specialist-Generalist Framework for Accurate and Lightweight Dermatological Visual Question Answering","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-05T16:31:34.220156Z"},"links":{"citing_paper":"/paper/2508.18430"},"observation_digest":"sha256:b2a3412aeb57bdddcaf40b7bd5fc1b63b0171a1660a919f6c6456bba4d384972","observation_id":"d2886206-c192-4dc2-9e35-2356677b8db7","resolution":{"observed_at":"2026-08-05T16:31:35.323331Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-05T16:31:35.299482Z","title":"Multimodal large language models: A survey,","venue":null,"work_id":"0ab15af8-7e8a-4455-ba7c-e760dc66033f","year":2023},"citing_paper":{"arxiv_id":"2508.18430","last_updated":"2025-08-25T19:22:16Z","snapshot_observed_at":"2026-08-13T20:43:30.915084Z","submitted_at":"2025-08-25T19:22:16Z","title":"CLARIFY: A Specialist-Generalist Framework for Accurate and Lightweight Dermatological Visual Question Answering","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-05T16:31:34.225994Z"},"links":{"citing_paper":"/paper/2508.18430"},"observation_digest":"sha256:939c4eef04a42a7e40c41330034ab9007b7a647c0799ca939e42acd0e29b5d20","observation_id":"f6ad24b4-a32b-475d-9fd9-22f58535583b","resolution":{"observed_at":"2026-08-05T16:31:35.305386Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-05T16:31:35.279681Z","title":"Enhancing medical image report generation through standard language models: Leveraging the power of llms in healthcare,","venue":null,"work_id":"16b725a4-3e59-4aee-9227-3609e98d15f8","year":2023},"citing_paper":{"arxiv_id":"2508.18430","last_updated":"2025-08-25T19:22:16Z","snapshot_observed_at":"2026-08-13T20:43:30.915084Z","submitted_at":"2025-08-25T19:22:16Z","title":"CLARIFY: A Specialist-Generalist Framework for Accurate and Lightweight Dermatological Visual Question Answering","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-05T16:31:34.231444Z"},"links":{"citing_paper":"/paper/2508.18430"},"observation_digest":"sha256:0b2ad7fbf9656d72f5b9b4aae92dedc773ebd92e12a876a85fb0dee9603974ac","observation_id":"9640cfc1-6909-4c00-92b7-f091132d25c1","resolution":{"observed_at":"2026-08-05T16:31:35.286516Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-05T16:31:34.236798Z","title":"Overcoming catastrophic forgetting in neural networks,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2508.18430","last_updated":"2025-08-25T19:22:16Z","snapshot_observed_at":"2026-08-13T20:43:30.915084Z","submitted_at":"2025-08-25T19:22:16Z","title":"CLARIFY: A Specialist-Generalist Framework for Accurate and Lightweight Dermatological Visual Question Answering","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-05T16:31:34.236798Z"},"links":{"citing_paper":"/paper/2508.18430"},"observation_digest":"sha256:fe3d446a0629b7fb314c0bc1fda002c9185db5ddcdbf78929cabfcb4cbc5b2af","observation_id":"1fb7cf42-f142-41c5-8535-1ea3030a13f5","resolution":{"observed_at":"2026-08-05T16:31:34.236798Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2308.08747","last_updated":"2025-01-05T04:09:00Z","snapshot_observed_at":"2026-08-16T00:12:56.001802Z","submitted_at":"2023-08-17T02:53:23Z","title":"An Empirical Study of Catastrophic Forgetting in Large Language Models During Continual Fine-tuning","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.08747","snapshot_observed_at":"2026-08-05T16:31:34.242346Z","title":"An empirical study of catastrophic forgetting in large language models during continual fine-tuning,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2508.18430","last_updated":"2025-08-25T19:22:16Z","snapshot_observed_at":"2026-08-13T20:43:30.915084Z","submitted_at":"2025-08-25T19:22:16Z","title":"CLARIFY: A Specialist-Generalist Framework for Accurate and Lightweight Dermatological Visual Question Answering","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-05T16:31:34.242346Z"},"links":{"cited_paper":"/paper/2308.08747","citing_paper":"/paper/2508.18430"},"observation_digest":"sha256:4207fcc65aa6c6006ff9feb969c96c4c108b8ad8e270f8bc82141cc71ed49565","observation_id":"e1e8fea1-d0a9-496a-acef-5ab744e253d0","resolution":{"observed_at":"2026-08-05T16:31:34.242346Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.11695","last_updated":"2024-05-06T17:47:01Z","snapshot_observed_at":"2026-08-20T04:15:03.506960Z","submitted_at":"2023-06-20T17:18:20Z","title":"A Simple and Effective Pruning Approach for Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.11695","snapshot_observed_at":"2026-08-05T16:31:34.247456Z","title":"A simple and effective pruning approach for large language models,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2508.18430","last_updated":"2025-08-25T19:22:16Z","snapshot_observed_at":"2026-08-13T20:43:30.915084Z","submitted_at":"2025-08-25T19:22:16Z","title":"CLARIFY: A Specialist-Generalist Framework for Accurate and Lightweight Dermatological Visual Question Answering","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-05T16:31:34.247456Z"},"links":{"cited_paper":"/paper/2306.11695","citing_paper":"/paper/2508.18430"},"observation_digest":"sha256:71ae5f39a9861506af00b219761f491f579b2c37d9ebf4ef7fae6388da90d11e","observation_id":"60e7324e-ab4e-4477-bf25-f8d1e60bdbbd","resolution":{"observed_at":"2026-08-05T16:31:34.247456Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.11627","last_updated":"2023-09-28T03:59:27Z","snapshot_observed_at":"2026-08-16T15:31:43.348408Z","submitted_at":"2023-05-19T12:10:53Z","title":"LLM-Pruner: On the Structural Pruning of Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.11627","snapshot_observed_at":"2026-08-05T16:31:34.252943Z","title":"Llm-pruner: On the structural pruning of large language models,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2508.18430","last_updated":"2025-08-25T19:22:16Z","snapshot_observed_at":"2026-08-13T20:43:30.915084Z","submitted_at":"2025-08-25T19:22:16Z","title":"CLARIFY: A Specialist-Generalist Framework for Accurate and Lightweight Dermatological Visual Question Answering","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-05T16:31:34.252943Z"},"links":{"cited_paper":"/paper/2305.11627","citing_paper":"/paper/2508.18430"},"observation_digest":"sha256:fccf6d75fa73b60e45b63d313e7c0554008deea91674a154950a12533ae204fb","observation_id":"2b01fd41-63b5-46fd-b96a-276f6c95ef06","resolution":{"observed_at":"2026-08-05T16:31:34.252943Z","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":"2026-08-05T16:31:34.258176Z","title":"Gptq: Accurate post-training quantization for generative pre-trained transformers,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2508.18430","last_updated":"2025-08-25T19:22:16Z","snapshot_observed_at":"2026-08-13T20:43:30.915084Z","submitted_at":"2025-08-25T19:22:16Z","title":"CLARIFY: A Specialist-Generalist Framework for Accurate and Lightweight Dermatological Visual Question Answering","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-05T16:31:34.258176Z"},"links":{"citing_paper":"/paper/2508.18430"},"observation_digest":"sha256:9ec6420d215ba27c6652cdfe2b6d16c86eb97d4f23d81466b9d20cb2bdd90f43","observation_id":"d6a5c57c-b94c-475a-abc3-b32aee14d4f1","resolution":{"observed_at":"2026-08-05T16:31:34.258176Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.02530","last_updated":"2024-10-30T04:55:26Z","snapshot_observed_at":"2026-08-17T01:30:14.271006Z","submitted_at":"2024-10-30T04:55:26Z","title":"A Comprehensive Study on Quantization Techniques for Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.02530","snapshot_observed_at":"2026-08-05T16:31:34.270028Z","title":"A comprehensive study on quantization techniques for large language models,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2508.18430","last_updated":"2025-08-25T19:22:16Z","snapshot_observed_at":"2026-08-13T20:43:30.915084Z","submitted_at":"2025-08-25T19:22:16Z","title":"CLARIFY: A Specialist-Generalist Framework for Accurate and Lightweight Dermatological Visual Question Answering","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-05T16:31:34.270028Z"},"links":{"cited_paper":"/paper/2411.02530","citing_paper":"/paper/2508.18430"},"observation_digest":"sha256:398259b9d2db63635c94b9ee2d3d07f170d67b23546804805427f4791209ca59","observation_id":"7bad31c2-5831-4d3b-b42c-421f4e331209","resolution":{"observed_at":"2026-08-05T16:31:34.270028Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2005.11401","last_updated":"2021-04-12T15:42:18Z","snapshot_observed_at":"2026-08-07T05:44:30.677502Z","submitted_at":"2020-05-22T21:34:34Z","title":"Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2005.11401","snapshot_observed_at":"2026-08-05T16:31:34.276075Z","title":"Retrieval-augmented generation for knowledge-intensive nlp tasks,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2508.18430","last_updated":"2025-08-25T19:22:16Z","snapshot_observed_at":"2026-08-13T20:43:30.915084Z","submitted_at":"2025-08-25T19:22:16Z","title":"CLARIFY: A Specialist-Generalist Framework for Accurate and Lightweight Dermatological Visual Question Answering","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-05T16:31:34.276075Z"},"links":{"cited_paper":"/paper/2005.11401","citing_paper":"/paper/2508.18430"},"observation_digest":"sha256:8417aa1b94b176e9c23653f989c712ce51c7294026e1fa570679ace3efdca64d","observation_id":"2d89c714-235a-472f-8097-d0b50141a792","resolution":{"observed_at":"2026-08-05T16:31:34.276075Z","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":"2026-08-05T16:31:34.282086Z","title":"Unifying large language models and knowledge graphs: A roadmap,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2508.18430","last_updated":"2025-08-25T19:22:16Z","snapshot_observed_at":"2026-08-13T20:43:30.915084Z","submitted_at":"2025-08-25T19:22:16Z","title":"CLARIFY: A Specialist-Generalist Framework for Accurate and Lightweight Dermatological Visual Question Answering","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-05T16:31:34.282086Z"},"links":{"citing_paper":"/paper/2508.18430"},"observation_digest":"sha256:d0459b78e64ca19db0921b64d5b1d971a0f15ffb1ad6bc53f1c2511d79df6143","observation_id":"a3397e30-f41e-4544-9caa-173eede7070d","resolution":{"observed_at":"2026-08-05T16:31:34.282086Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.00727","last_updated":"2024-10-11T01:00:48Z","snapshot_observed_at":"2026-08-16T13:29:09.455555Z","submitted_at":"2024-08-01T17:18:17Z","title":"Improving Retrieval-Augmented Generation in Medicine with Iterative Follow-up Questions","version":3},"cited_work":{"arxiv_id":"2408.00727","doi":null,"metadata_source":"pith","pith_arxiv_id":"2408.00727","snapshot_observed_at":"2026-08-05T16:31:34.857073Z","title":"Improving Retrieval-Augmented Generation in Medicine with Iterative Follow-up Questions","venue":"cs.CL","work_id":"771cda1f-65e5-41c9-bc95-a2ca644bff5f","year":2024},"citing_paper":{"arxiv_id":"2508.18430","last_updated":"2025-08-25T19:22:16Z","snapshot_observed_at":"2026-08-13T20:43:30.915084Z","submitted_at":"2025-08-25T19:22:16Z","title":"CLARIFY: A Specialist-Generalist Framework for Accurate and Lightweight Dermatological Visual Question Answering","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-05T16:31:34.287151Z"},"links":{"cited_paper":"/paper/2408.00727","citing_paper":"/paper/2508.18430"},"observation_digest":"sha256:00e612516fd0eb0eb4fea167fe6f8f9be802d1d68a199fb22b7df3cc39d87066","observation_id":"2b3d39fd-3d96-4226-8ea2-92e8fdb29e02","resolution":{"observed_at":"2026-08-05T16:31:34.863751Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-05T16:31:35.246699Z","title":"Dermatology resource,","venue":null,"work_id":"8ce4fafe-b908-46c4-bac6-3b6cd871887b","year":2025},"citing_paper":{"arxiv_id":"2508.18430","last_updated":"2025-08-25T19:22:16Z","snapshot_observed_at":"2026-08-13T20:43:30.915084Z","submitted_at":"2025-08-25T19:22:16Z","title":"CLARIFY: A Specialist-Generalist Framework for Accurate and Lightweight Dermatological Visual Question Answering","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-05T16:31:34.294317Z"},"links":{"citing_paper":"/paper/2508.18430"},"observation_digest":"sha256:f589ff5b22f0a2d53c9dbf19f083210613bbe5fd5f3747044c5bb9fd44774628","observation_id":"b141417b-85b8-41da-a750-de80ba266d1b","resolution":{"observed_at":"2026-08-05T16:31:35.252857Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2103.00020","last_updated":"2021-02-26T19:04:58Z","snapshot_observed_at":"2026-07-06T10:45:03.059688Z","submitted_at":"2021-02-26T19:04:58Z","title":"Learning Transferable Visual Models From Natural Language Supervision","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2103.00020","snapshot_observed_at":"2026-08-05T16:31:34.298939Z","title":"Learning transferable visual models from natural language supervision,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2508.18430","last_updated":"2025-08-25T19:22:16Z","snapshot_observed_at":"2026-08-13T20:43:30.915084Z","submitted_at":"2025-08-25T19:22:16Z","title":"CLARIFY: A Specialist-Generalist Framework for Accurate and Lightweight Dermatological Visual Question Answering","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-05T16:31:34.298939Z"},"links":{"cited_paper":"/paper/2103.00020","citing_paper":"/paper/2508.18430"},"observation_digest":"sha256:95eb4230d6729c4dfef253dfa908dc00acede9ffcedf3ea59ef4be51b8a20aa6","observation_id":"139774f5-f162-4308-ada5-1721be9bd317","resolution":{"observed_at":"2026-08-05T16:31:34.298939Z","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":"2026-08-05T16:31:35.229082Z","title":"Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation,","venue":null,"work_id":"ce5a4b4a-58a1-4490-ba06-db009b973a40","year":null},"citing_paper":{"arxiv_id":"2508.18430","last_updated":"2025-08-25T19:22:16Z","snapshot_observed_at":"2026-08-13T20:43:30.915084Z","submitted_at":"2025-08-25T19:22:16Z","title":"CLARIFY: A Specialist-Generalist Framework for Accurate and Lightweight Dermatological Visual Question Answering","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-05T16:31:34.303817Z"},"links":{"citing_paper":"/paper/2508.18430"},"observation_digest":"sha256:c78af6564e1a3f3bfbffef293a5817a802c050a9f73e68be42bc3eaa11e32058","observation_id":"538b1c44-f7cf-4274-be23-54fd06727e18","resolution":{"observed_at":"2026-08-05T16:31:35.234981Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1512.03385","last_updated":"2015-12-10T19:51:55Z","snapshot_observed_at":"2026-07-06T04:39:28.429064Z","submitted_at":"2015-12-10T19:51:55Z","title":"Deep Residual Learning for Image Recognition","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1512.03385","snapshot_observed_at":"2026-08-05T16:31:34.314516Z","title":"Deep residual learning for image recognition,","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2508.18430","last_updated":"2025-08-25T19:22:16Z","snapshot_observed_at":"2026-08-13T20:43:30.915084Z","submitted_at":"2025-08-25T19:22:16Z","title":"CLARIFY: A Specialist-Generalist Framework for Accurate and Lightweight Dermatological Visual Question Answering","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-05T16:31:34.314516Z"},"links":{"cited_paper":"/paper/1512.03385","citing_paper":"/paper/2508.18430"},"observation_digest":"sha256:e58b81121dc9278134d099b8e705320862f079d422a1ad98d16d68c2dc5b226b","observation_id":"62000d89-3e07-49fe-b6c3-3f2463cda32e","resolution":{"observed_at":"2026-08-05T16:31:34.314516Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2010.11929","last_updated":"2021-06-03T13:08:56Z","snapshot_observed_at":"2026-08-16T09:25:53.087782Z","submitted_at":"2020-10-22T17:55:59Z","title":"An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.11929","snapshot_observed_at":"2026-08-05T16:31:34.320053Z","title":"An image is worth 16x16 words: Transformers for image recognition at scale,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2508.18430","last_updated":"2025-08-25T19:22:16Z","snapshot_observed_at":"2026-08-13T20:43:30.915084Z","submitted_at":"2025-08-25T19:22:16Z","title":"CLARIFY: A Specialist-Generalist Framework for Accurate and Lightweight Dermatological Visual Question Answering","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-05T16:31:34.320053Z"},"links":{"cited_paper":"/paper/2010.11929","citing_paper":"/paper/2508.18430"},"observation_digest":"sha256:06b0b652d161d732af7a368b436689a6f844badca4e2d8467029a583ad97baf8","observation_id":"329bba7f-b2f8-4b24-a82e-091d369fdc9b","resolution":{"observed_at":"2026-08-05T16:31:34.320053Z","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":"2026-08-05T16:31:34.325688Z","title":"Dermatologist-level classification of skin cancer with deep neural networks,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2508.18430","last_updated":"2025-08-25T19:22:16Z","snapshot_observed_at":"2026-08-13T20:43:30.915084Z","submitted_at":"2025-08-25T19:22:16Z","title":"CLARIFY: A Specialist-Generalist Framework for Accurate and Lightweight Dermatological Visual Question Answering","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-05T16:31:34.325688Z"},"links":{"citing_paper":"/paper/2508.18430"},"observation_digest":"sha256:16bdba51fb5bdef3c85ff636fc43e0dfdf6d759cf917a1fc56fe0b234fc820fa","observation_id":"2e413a00-2370-457d-9228-1fcd5c919aed","resolution":{"observed_at":"2026-08-05T16:31:34.325688Z","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":"2026-08-05T16:31:35.200764Z","title":"A survey on model compression and accel- eration for pretrained language models,","venue":null,"work_id":"321883af-a38e-4423-8b64-608c7e785ed1","year":2023},"citing_paper":{"arxiv_id":"2508.18430","last_updated":"2025-08-25T19:22:16Z","snapshot_observed_at":"2026-08-13T20:43:30.915084Z","submitted_at":"2025-08-25T19:22:16Z","title":"CLARIFY: A Specialist-Generalist Framework for Accurate and Lightweight Dermatological Visual Question Answering","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-05T16:31:34.330478Z"},"links":{"citing_paper":"/paper/2508.18430"},"observation_digest":"sha256:cc39b162f3a7d3bd027b8ce01ca470d445bcfe0d45782fae6044053a7f38b2f8","observation_id":"8b4c82ad-6bdc-4030-bef1-6c4d61f15289","resolution":{"observed_at":"2026-08-05T16:31:35.207092Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.02834","last_updated":"2024-06-23T08:45:33Z","snapshot_observed_at":"2026-08-18T12:31:28.811633Z","submitted_at":"2024-02-05T09:44:49Z","title":"Shortened LLaMA: Depth Pruning for Large Language Models with Comparison of Retraining Methods","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.02834","snapshot_observed_at":"2026-08-05T16:31:34.335602Z","title":"Shortened llama: A simple depth pruning for large language models,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2508.18430","last_updated":"2025-08-25T19:22:16Z","snapshot_observed_at":"2026-08-13T20:43:30.915084Z","submitted_at":"2025-08-25T19:22:16Z","title":"CLARIFY: A Specialist-Generalist Framework for Accurate and Lightweight Dermatological Visual Question Answering","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-05T16:31:34.335602Z"},"links":{"cited_paper":"/paper/2402.02834","citing_paper":"/paper/2508.18430"},"observation_digest":"sha256:a7411989b5fc1fd0dc28943ba2ae33970135d2d5e7cd270f5e16921b27c3b739","observation_id":"24041e78-9eb1-43c6-8dd5-78e1f0903ec3","resolution":{"observed_at":"2026-08-05T16:31:34.335602Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.03853","last_updated":"2024-10-11T09:43:32Z","snapshot_observed_at":"2026-08-16T14:12:14.696997Z","submitted_at":"2024-03-06T17:04:18Z","title":"ShortGPT: Layers in Large Language Models are More Redundant Than You Expect","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.03853","snapshot_observed_at":"2026-08-05T16:31:34.340742Z","title":"Shortgpt: Layers in large language models are more redundant than you expect,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2508.18430","last_updated":"2025-08-25T19:22:16Z","snapshot_observed_at":"2026-08-13T20:43:30.915084Z","submitted_at":"2025-08-25T19:22:16Z","title":"CLARIFY: A Specialist-Generalist Framework for Accurate and Lightweight Dermatological Visual Question Answering","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-05T16:31:34.340742Z"},"links":{"cited_paper":"/paper/2403.03853","citing_paper":"/paper/2508.18430"},"observation_digest":"sha256:a25fd72d7b5e9acf5e227633a4c7db93ae29c7494942aecbf9369e7873d110d8","observation_id":"f11b8b16-4588-4569-a3ef-0f0b91528736","resolution":{"observed_at":"2026-08-05T16:31:34.340742Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.04413","last_updated":"2025-06-27T12:06:42Z","snapshot_observed_at":"2026-08-13T11:33:15.231169Z","submitted_at":"2025-02-06T12:27:35Z","title":"MedRAG: Enhancing Retrieval-augmented Generation with Knowledge Graph-Elicited Reasoning for Healthcare Copilot","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.04413","snapshot_observed_at":"2026-08-05T16:31:34.346498Z","title":"Medrag: Enhancing retrieval-augmented generation with knowledge graph-elicited reasoning for healthcare copilot,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2508.18430","last_updated":"2025-08-25T19:22:16Z","snapshot_observed_at":"2026-08-13T20:43:30.915084Z","submitted_at":"2025-08-25T19:22:16Z","title":"CLARIFY: A Specialist-Generalist Framework for Accurate and Lightweight Dermatological Visual Question Answering","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-05T16:31:34.346498Z"},"links":{"cited_paper":"/paper/2502.04413","citing_paper":"/paper/2508.18430"},"observation_digest":"sha256:180c3dd9572c917063f6d22f71f10dcaff9961a3ac34c04745451106262ad1c9","observation_id":"172caef8-3faa-4bfe-a546-897f75e66c27","resolution":{"observed_at":"2026-08-05T16:31:34.346498Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.12035","last_updated":"2024-05-20T14:03:05Z","snapshot_observed_at":"2026-08-20T14:42:08.490541Z","submitted_at":"2024-05-20T14:03:05Z","title":"KG-RAG: Bridging the Gap Between Knowledge and Creativity","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.12035","snapshot_observed_at":"2026-08-05T16:31:34.351981Z","title":"Kg-rag: Bridging the gap between knowledge and creativity,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2508.18430","last_updated":"2025-08-25T19:22:16Z","snapshot_observed_at":"2026-08-13T20:43:30.915084Z","submitted_at":"2025-08-25T19:22:16Z","title":"CLARIFY: A Specialist-Generalist Framework for Accurate and Lightweight Dermatological Visual Question Answering","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-05T16:31:34.351981Z"},"links":{"cited_paper":"/paper/2405.12035","citing_paper":"/paper/2508.18430"},"observation_digest":"sha256:d1bd0267cfd4822c719fc9ba419f68d667a704943d37d4ba3fa8485245957f0e","observation_id":"89b20ed2-040a-4944-8b74-ae96ead3371a","resolution":{"observed_at":"2026-08-05T16:31:34.351981Z","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":"2026-08-05T16:31:35.171130Z","title":"Gregg and D","venue":null,"work_id":"22b75697-2add-4864-94cb-73e895580660","year":2022},"citing_paper":{"arxiv_id":"2508.18430","last_updated":"2025-08-25T19:22:16Z","snapshot_observed_at":"2026-08-13T20:43:30.915084Z","submitted_at":"2025-08-25T19:22:16Z","title":"CLARIFY: A Specialist-Generalist Framework for Accurate and Lightweight Dermatological Visual Question Answering","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-05T16:31:34.357292Z"},"links":{"citing_paper":"/paper/2508.18430"},"observation_digest":"sha256:ffc987e059d974c463db0d0f6067d0691cea0ad36b2aae1852e01828b3684632","observation_id":"0fdd1051-b9ab-4424-be3a-654e28fd3d20","resolution":{"observed_at":"2026-08-05T16:31:35.179947Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"dsv/1284531","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T16:31:34.680722Z","title":"Small-derma-vqa,","venue":null,"work_id":"ef203721-87e5-47b3-b02c-5b3838ff5f78","year":2025},"citing_paper":{"arxiv_id":"2508.18430","last_updated":"2025-08-25T19:22:16Z","snapshot_observed_at":"2026-08-13T20:43:30.915084Z","submitted_at":"2025-08-25T19:22:16Z","title":"CLARIFY: A Specialist-Generalist Framework for Accurate and Lightweight Dermatological Visual Question Answering","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-05T16:31:34.362568Z"},"links":{"citing_paper":"/paper/2508.18430"},"observation_digest":"sha256:60ac315526fc291e93abd49bdc1c558db07cf880ed03cc5f7b05a46c96a418c8","observation_id":"955c74c9-c42f-4b0f-b507-dc336e06c93b","resolution":{"observed_at":"2026-08-05T16:31:34.690147Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2304.07193","last_updated":"2024-02-02T10:24:09Z","snapshot_observed_at":"2026-08-17T13:03:40.359628Z","submitted_at":"2023-04-14T15:12:19Z","title":"DINOv2: Learning Robust Visual Features without Supervision","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.07193","snapshot_observed_at":"2026-08-05T16:31:34.367173Z","title":"Dinov2: Learning robust visual features without supervision,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2508.18430","last_updated":"2025-08-25T19:22:16Z","snapshot_observed_at":"2026-08-13T20:43:30.915084Z","submitted_at":"2025-08-25T19:22:16Z","title":"CLARIFY: A Specialist-Generalist Framework for Accurate and Lightweight Dermatological Visual Question Answering","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-05T16:31:34.367173Z"},"links":{"cited_paper":"/paper/2304.07193","citing_paper":"/paper/2508.18430"},"observation_digest":"sha256:f15c86d2bcfbae97b039ea5067ac508b60498d520656e57f43308a90cf94c81b","observation_id":"953f5270-d6c9-4512-8711-90c4b197f902","resolution":{"observed_at":"2026-08-05T16:31:34.367173Z","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":"2026-08-05T16:31:34.372375Z","title":"Llm-pruner: On the structural pruning of large language models,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2508.18430","last_updated":"2025-08-25T19:22:16Z","snapshot_observed_at":"2026-08-13T20:43:30.915084Z","submitted_at":"2025-08-25T19:22:16Z","title":"CLARIFY: A Specialist-Generalist Framework for Accurate and Lightweight Dermatological Visual Question Answering","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-05T16:31:34.372375Z"},"links":{"citing_paper":"/paper/2508.18430"},"observation_digest":"sha256:85eaf0ba5b3305fa6ab9a1459b1750be3c58bef60122439f5b04b218d571c107","observation_id":"9fbfe407-45bd-4655-88f0-d4b1e5dfbf0a","resolution":{"observed_at":"2026-08-05T16:31:34.372375Z","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":"2026-08-05T16:31:34.378008Z","title":"Kggen: Extracting knowledge graphs from plain text with language models,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2508.18430","last_updated":"2025-08-25T19:22:16Z","snapshot_observed_at":"2026-08-13T20:43:30.915084Z","submitted_at":"2025-08-25T19:22:16Z","title":"CLARIFY: A Specialist-Generalist Framework for Accurate and Lightweight Dermatological Visual Question Answering","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-05T16:31:34.378008Z"},"links":{"citing_paper":"/paper/2508.18430"},"observation_digest":"sha256:c5e5eb0d73c70e5a24998b1305355077674e04ab76261c782f88d836ae7586a2","observation_id":"db076370-4a8e-457b-a52f-0c14aa836414","resolution":{"observed_at":"2026-08-05T16:31:34.378008Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.11805","last_updated":"2025-05-09T21:04:06Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-12-19T02:39:27Z","title":"Gemini: A Family of Highly Capable Multimodal Models","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.11805","snapshot_observed_at":"2026-08-05T16:31:34.383783Z","title":"Gemini: a family of highly capable multimodal models,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2508.18430","last_updated":"2025-08-25T19:22:16Z","snapshot_observed_at":"2026-08-13T20:43:30.915084Z","submitted_at":"2025-08-25T19:22:16Z","title":"CLARIFY: A Specialist-Generalist Framework for Accurate and Lightweight Dermatological Visual Question Answering","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-05T16:31:34.383783Z"},"links":{"cited_paper":"/paper/2312.11805","citing_paper":"/paper/2508.18430"},"observation_digest":"sha256:da04ccfd40077e730f76a08e3698651ab205149e855ad39d1da0bdb7153cab44","observation_id":"b25e8794-6edc-4c1b-9c26-671425bf873d","resolution":{"observed_at":"2026-08-05T16:31:34.383783Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.03714","last_updated":"2023-10-05T17:37:25Z","snapshot_observed_at":"2026-08-04T05:21:05.846165Z","submitted_at":"2023-10-05T17:37:25Z","title":"DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.03714","snapshot_observed_at":"2026-08-05T16:31:34.388561Z","title":"Dspy: Compiling declarative language model calls into self-improving pipelines,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2508.18430","last_updated":"2025-08-25T19:22:16Z","snapshot_observed_at":"2026-08-13T20:43:30.915084Z","submitted_at":"2025-08-25T19:22:16Z","title":"CLARIFY: A Specialist-Generalist Framework for Accurate and Lightweight Dermatological Visual Question Answering","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-05T16:31:34.388561Z"},"links":{"cited_paper":"/paper/2310.03714","citing_paper":"/paper/2508.18430"},"observation_digest":"sha256:e6c9e4b9da277017183e7d11d1b412f0ad2b9db4e29621ef75b986729f9060b1","observation_id":"ef15e2ae-477e-43c9-a6c3-73cbbd07fd07","resolution":{"observed_at":"2026-08-05T16:31:34.388561Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2002.10957","last_updated":"2020-04-06T02:53:18Z","snapshot_observed_at":"2026-08-14T23:23:42.318384Z","submitted_at":"2020-02-25T15:21:10Z","title":"MiniLM: Deep Self-Attention Distillation for Task-Agnostic Compression of Pre-Trained Transformers","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2002.10957","snapshot_observed_at":"2026-08-05T16:31:34.394103Z","title":"Minilm: Deep self-attention distillation for task-agnostic compression of pre-trained transformers,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2508.18430","last_updated":"2025-08-25T19:22:16Z","snapshot_observed_at":"2026-08-13T20:43:30.915084Z","submitted_at":"2025-08-25T19:22:16Z","title":"CLARIFY: A Specialist-Generalist Framework for Accurate and Lightweight Dermatological Visual Question Answering","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-05T16:31:34.394103Z"},"links":{"cited_paper":"/paper/2002.10957","citing_paper":"/paper/2508.18430"},"observation_digest":"sha256:a7defd365cbb856269e458acc0b4c20caa8050f540bbe1811b1cf2ba97520f40","observation_id":"280ecb61-a271-425e-a450-55d0eb7bdb44","resolution":{"observed_at":"2026-08-05T16:31:34.394103Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.15594","last_updated":"2025-10-19T10:32:43Z","snapshot_observed_at":"2026-08-20T12:52:29.141935Z","submitted_at":"2024-11-23T16:03:35Z","title":"A Survey on LLM-as-a-Judge","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.15594","snapshot_observed_at":"2026-08-05T16:31:34.399190Z","title":"A survey on llm-as-a-judge,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2508.18430","last_updated":"2025-08-25T19:22:16Z","snapshot_observed_at":"2026-08-13T20:43:30.915084Z","submitted_at":"2025-08-25T19:22:16Z","title":"CLARIFY: A Specialist-Generalist Framework for Accurate and Lightweight Dermatological Visual Question Answering","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-05T16:31:34.399190Z"},"links":{"cited_paper":"/paper/2411.15594","citing_paper":"/paper/2508.18430"},"observation_digest":"sha256:1ba1481598d0c13f249ea2692532b183354c0f9320ce8b6744ac87af976ec5a5","observation_id":"1fab7d36-3d4e-449a-a3e9-87f25d62c6df","resolution":{"observed_at":"2026-08-05T16:31:34.399190Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2201.12086","last_updated":"2022-02-15T05:43:32Z","snapshot_observed_at":"2026-08-20T06:46:31.583175Z","submitted_at":"2022-01-28T12:49:48Z","title":"BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2201.12086","snapshot_observed_at":"2026-08-05T16:31:34.309538Z","title":"Available: https://arxiv.org/abs/2201.12086 10","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2508.18430","last_updated":"2025-08-25T19:22:16Z","snapshot_observed_at":"2026-08-13T20:43:30.915084Z","submitted_at":"2025-08-25T19:22:16Z","title":"CLARIFY: A Specialist-Generalist Framework for Accurate and Lightweight Dermatological Visual Question Answering","version":1},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-08-05T16:31:34.309538Z"},"links":{"cited_paper":"/paper/2201.12086","citing_paper":"/paper/2508.18430"},"observation_digest":"sha256:6588e3bfa6acce2bfb37f71f8fd990696d7610bfdfeb0cad01e260e5d17dca8f","observation_id":"1d3e5fda-c22c-4f56-903e-f830935e267a","resolution":{"observed_at":"2026-08-05T16:31:34.309538Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.17323","last_updated":"2023-03-22T13:10:47Z","snapshot_observed_at":"2026-08-16T07:57:19.216626Z","submitted_at":"2022-10-31T13:42:40Z","title":"GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.17323","snapshot_observed_at":"2026-08-05T16:31:34.263973Z","title":"Available: https://arxiv.org/abs/2210.17323","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2508.18430","last_updated":"2025-08-25T19:22:16Z","snapshot_observed_at":"2026-08-13T20:43:30.915084Z","submitted_at":"2025-08-25T19:22:16Z","title":"CLARIFY: A Specialist-Generalist Framework for Accurate and Lightweight Dermatological Visual Question Answering","version":1},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-05T16:31:34.263973Z"},"links":{"cited_paper":"/paper/2210.17323","citing_paper":"/paper/2508.18430"},"observation_digest":"sha256:1a3c345e2b2921bb97eb45f28fc597264f31b5aebdbd81d2692c28e6d282ba7f","observation_id":"27e8b102-b764-4bd1-8ed1-2d59704dd82e","resolution":{"observed_at":"2026-08-05T16:31:34.263973Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2508.18430","last_updated":"2025-08-25T19:22:16Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-13T20:43:30.915084Z","submitted_at":"2025-08-25T19:22:16Z","title":"CLARIFY: A Specialist-Generalist Framework for Accurate and Lightweight Dermatological Visual Question Answering"},"reference_resolution":{"displayed":38,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":27,"verified_exact":2,"verified_fuzzy":8},"total_outbound_references":38},"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":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"thesis":"As of 20 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 1 inbound Pith citation observation for arXiv:2508.18430."}