Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T20:12:20.961681Z
Paper Citation Record · LEDGER
As of 9 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 2 inbound Pith citation observations for arXiv:2507.03541.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T20:12:20.961681Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-05T14:59:35.365366Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-13T16:53:00.079094Z
55 of 55 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation d278ade9-90d6-4838-9fe2-23a5f305782c · outbound
Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognition Technical report, National Institute of Standards and Technology, 2025
Reference 1
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Observation 5760f778-7b26-4287-867f-165a76228b2a · outbound
Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognition Face Recognition in the age of CLIP & Billion image datasets
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Observation d3dd8ade-dc4c-40a0-b345-f4e2040ea647 · outbound
Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognition On the Opportunities and Risks of Foundation Models
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Observation c4fb0193-fe4e-47a0-bd42-f7500050b7eb · outbound
Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognition Emerg- ing Properties in Self-Supervised Vision Transformers
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Observation cf8c6623-dd7e-4222-9dc1-a3b04c3e636b · outbound
Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognition InternVL: Scaling Up Vision Foundation Models and Aligning for Generic Visual-linguistic Tasks
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Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognition Reproducible Scal- ing Laws for Contrastive Language-Image Learning
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Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognition MS1MV2 Dataset
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Observation 90a828be-1838-4ecf-bd0c-46ade9e6ba13 · outbound
Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognition DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models
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Observation a4f95dd0-7af5-4c92-8836-ac2eecc21573 · outbound
Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognition How Good is ChatGPT at Face Biomet- rics? A First Look Into Recognition, Soft Biometrics, and Explainability
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Observation a778d4c4-4827-4939-88b3-23ef853aabdd · outbound
Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognition ArcFace: Additive Angular Margin Loss for Deep Face Recognition
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Observation f8b66350-a64f-4c1e-9432-fcebb8fc4bd9 · outbound
Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognition Lightweight Face Recognition Chal- lenge
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Observation b46c54f8-fbdc-478c-b71c-3cb23a1a321c · outbound
Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognition An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
Reference 13
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Observation f2381a6e-d629-49d7-90c9-1077f30fdd47 · outbound
Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognition ChatGPT Meets Iris Bio- metrics
Reference 14
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Observation fb33ebe4-88a5-4e29-ba10-75389577abf7 · outbound
Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognition Iris-SAM: Iris Segmenta- tion Using a Foundation Model
Reference 15
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Observation dc67984c-68dd-45d1-abaf-ae52f0264934 · outbound
Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognition ChatGPT and Biometrics: An Assessment of Face Recognition, Gender Detection, and Age Estimation Capabilities
Reference 16
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Observation 37aa7aea-1dfa-4560-9a52-d23da8998c81 · outbound
Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognition Huang, Marwan Mattar, Tamara Berg, and Eric Learned-Miller
Reference 17
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Observation b03541c1-a26f-4838-9544-b588d48be7ee · outbound
Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognition OpenCLIP: Open-Source CLIP Reproduction
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Observation d0ca887e-159f-4cf3-9a6a-ddce5a038041 · outbound
Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognition Jain, Arun A
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Observation 8f8fa273-5e88-48a3-a7fd-9eec2f67c68c · outbound
Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognition Scaling Up Visual and Vision-language Represen- tation Learning With Noisy Text Supervision
Reference 20
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Observation 52ead8fd-36ce-4eb2-990e-d14a4e7a3e3d · outbound
Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognition Kalka, Brianna Maze, James A
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Observation 1d035294-0c5b-4b03-8972-be27ef710072 · outbound
Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognition Jain, and Xiaoming Liu
Reference 22
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Observation 9c6a8ae8-1f22-46e5-a09e-07f6093319b6 · outbound
Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognition Jain, and Xiaoming Liu
Reference 23
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Observation a77a017c-a0b0-45e1-bc66-d0f0ea7c9da7 · outbound
Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognition Berg, Wan-Yen Lo, Piotr Dollar, and Ross Girshick
Reference 24
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Observation ba366a29-feef-45ca-a837-b244f9cc0d7f · outbound
Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognition Exploring ChatGPT for Face Presentation Attack Detection in Zero and Few-Shot in-Context Learning
Reference 25
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Observation 37936dc0-fe14-4191-b2c3-a0f4ebf3d492 · outbound
Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognition BLIP: Bootstrapping Language-image Pre-training for Uni- fied Vision-language Understanding and Generation
Reference 26
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Observation 84522745-a2c5-4658-93bd-389558d22b6b · outbound
Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognition BLIP-2: Bootstrapping Language-image Pre-training With Frozen Image Encoders and Large Language Models
Reference 27
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Observation 240e5c11-1f7e-468b-8b57-2234d3591774 · outbound
Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognition Improved Baselines With Visual Instruction Tuning
Reference 28
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Observation 7d6ecbd2-a35d-422a-9158-ae6b9be26fd6 · outbound
Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognition LLaV A-NeXT: Im- proved Reasoning, OCR, and World Knowledge, 2024
Reference 29
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Observation b6f21ef8-d293-41e1-844f-29c9a6069727 · outbound
Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognition SphereFace: Deep Hypersphere Embed- ding for Face Recognition
Reference 30
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Observation 13caee5f-af3e-44d4-ae08-5802f785670e · outbound
Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognition Duncan, Nathan Kalka, Tim Miller, Charles Otto, Anil K
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Observation 5beed6d8-1ca9-482e-aef6-4df3df06e100 · outbound
Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognition Segment Anything Model for Medical Image Analysis: An Experimental Study
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Observation 4ddd8112-d2fd-4019-a7d6-d64ee27c9fd1 · outbound
Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognition MagFace: A Universal Representation for Face Recognition and Quality Assessment
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Observation 2c26d694-76b2-4b79-b379-b15b3bb0ca7f · outbound
Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognition Unresolved cited work
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Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognition GPT-4 Technical Report
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Observation fae3f88d-758e-4108-867c-0f87b7d35c0c · outbound
Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognition GPT-4o System Card
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Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognition DINOv2: Learning Robust Visual Features without Supervision
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Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognition FoundPAD: Foundation Models Reloaded for Face Presen- tation Attack Detection, 2025
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Observation 73a3e708-d4c0-45dc-8c2e-59b9ea87119c · outbound
Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognition Kosmos-2: Grounding Multimodal Large Language Models to the World
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Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognition Learning Transferable Visual Models from Natural Language Super- vision
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Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognition SAM 2: Segment Anything in Images and Videos
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Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognition A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications
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Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognition FaceNet: A Unified Embedding for Face Recognition and Clustering
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Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognition Gemini: A Family of Highly Capable Multimodal Models
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Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognition CosFace: Large Margin Cosine Loss for Deep Face Recognition
Reference 48
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Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognition Sector Rotation by Factor Model and Fundamental Analysis
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Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognition Jain, James A
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Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognition DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding
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Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognition Cross-Pose LFW: A Database for Studying Cross-Pose Face Recognition in Un- constrained Environments
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Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognition InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models
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Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognition WebFace260M: A Benchmark Unveiling the Power of Million-Scale Deep Face Recognition
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Training a Student Expert via Semi-Supervised Foundation Model Distillation Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognition
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