mlsanityData to 14 Oct 2026

Benchmarking Multimodal Large Language Models for Face Recognition

arXiv 2510.14866 ↗First posted 16 Oct 2025cs.CV cs.AI cs.CLcited by 5

On the map: Multimodal LLMs / vision-language models → Social bias and fairness in VLMs

Abstract (arXiv)

Multimodal large language models (MLLMs) have achieved remarkable performance across diverse vision-and-language tasks. However, their potential in face recognition remains underexplored. In particular, the performance of open-source MLLMs needs to be evaluated and compared with existing face recognition models on standard benchmarks with similar protocol. In this work, we present a systematic benchmark of state-of-the-art MLLMs for face recognition on several face recognition datasets, including LFW, CALFW, CPLFW, CFP, AgeDB and RFW. Experimental results reveal that while MLLMs capture rich semantic cues useful for face-related tasks, they lag behind specialized models in high-precision recognition scenarios in zero-shot applications. This benchmark provides a foundation for advancing MLLM-based face recognition, offering insights for the design of next-generation models with higher accuracy and generalization. The source code of our benchmark is publicly available in the project page.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Placed in Social bias and fairness in VLMs, one of 16 directions in Multimodal LLMs / vision-language models. Builds on 31 of its 38 references that are in the map. First posted on arXiv 16 Oct 2025.

Builds on

31 of 38 references.

Closest ancestors · 3

Same direction, newest first

  1. 2025FaceLLM: A Multimodal Large Language Model for Face Understanding14 Jul
  2. 2025FaceBench: A Multi-View Multi-Level Facial Attribute VQA Dataset for Benchmarking Face Perception MLLMs27 Mar
  3. 2025FaceXBench: Evaluating Multimodal LLMs on Face Understanding17 Jan

Other references · 28

  1. 2024The Llama 3 Herd of Modelscited by 14,715
  2. 2023Visual Instruction Tuningcited by 7,869
  3. 2024Qwen2.5 Technical Reportcited by 4,942
  4. 2024GPT-4o System Cardcited by 4,588
  5. 2023Improved Baselines with Visual Instruction Tuningcited by 4,418
  6. 2022Flamingo: a Visual Language Model for Few-Shot Learningcited by 4,386
  7. 2024Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolutioncited by 4,234
  8. 2025InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Modelscited by 1,834
  9. 2024Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scalingcited by 1,599
  10. 2024ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Toolscited by 1,121
  11. 2023ShareGPT4V: Improving Large Multi-Modal Models with Better Captionscited by 1,005
  12. 2024PaliGemma: A versatile 3B VLM for transfercited by 696
16 more
  1. 2016MS-Celeb-1M: A Dataset and Benchmark for Large-Scale Face Recognitioncited by 624
  2. 2022AdaFace: Quality Adaptive Margin for Face Recognitioncited by 391
  3. 2024What matters when building vision-language models?cited by 326
  4. 2023OBELICS: An Open Web-Scale Filtered Dataset of Interleaved Image-Text Documentscited by 316
  5. 2017Cross-Age LFW: A Database for Studying Cross-Age Face Recognition in Unconstrained Environmentscited by 260
  6. 2024Building and better understanding vision-language models: insights and future directionscited by 173
  7. 2024Ovis: Structural Embedding Alignment for Multimodal Large Language Modelcited by 169
  8. 2024Can ChatGPT Detect DeepFakes? A Study of Using Multimodal Large Language Models for Media Forensicscited by 69
  9. 2024SHIELD : An Evaluation Benchmark for Face Spoofing and Forgery Detection with Multimodal Large Language Modelscited by 40
  10. 2023EdgeFace: Efficient Face Recognition Model for Edge Devicescited by 33
  11. 2024ChatGPT and biometrics: an assessment of face recognition, gender detection, and age estimation capabilitiescited by 21
  12. 2025Valley2: Exploring Multimodal Models with Scalable Vision-Language Designcited by 21
  13. 2024HyperFace: Generating Synthetic Face Recognition Datasets by Exploring Face Embedding Hyperspherecited by 12
  14. 2025Face-Human-Bench: A Comprehensive Benchmark of Face and Human Understanding for Multi-modal Assistantscited by 12
  15. 2025Exploring ChatGPT for Face Presentation Attack Detection in Zero and Few-Shot in-Context Learningcited by 12
  16. 2025Foundation versus Domain-specific Models: Performance Comparison, Fusion, and Explainability in Face Recognitioncited by 8

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 5.

5 papers.

  1. 2026Evaluating Multimodal Large Language Models for Heterogeneous Face Recognitioncited by 3
  2. 2026Demographic Fairness in Multimodal LLMs: A Benchmark of Gender and Ethnicity Bias in Face Verificationcited by 1
  3. 2026SLAPBench: Benchmarking Multimodal Large Language Models for Four-Finger SLAP Fingerprint Verificationcited by 0
  4. 2026Vision Language Model Fusion for Explainable Face Recognitioncited by 0
  5. 2026Foundation and Multimodal Large Language Models for Face Presentation and Morph Attack Detectioncited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2024Face-MLLM: A Large Face Perception Model
  2. 2026Multimodal Large Language Models as Image Classifiers
  3. 2026MLLM-based Textual Explanations for Face Comparison
  4. 2024A Survey on Benchmarks of Multimodal Large Language Models
  5. 2026Benchmarking the Explanatory Quality of Open-Weight Vision-Language Models in Face Recognition
  6. 2025Benchmarking Foundation Models for Zero-Shot Biometric Tasks
  7. 2025Benchmarking Large Vision-Language Models on Fine-Grained Image Tasks: A Comprehensive Evaluation
  8. 2025Benchmarking Large and Small MLLMs