mlsanityData to 14 Oct 2026

MLLM-Fabric: Multimodal Large Language Model-Driven Robotic Framework for Fabric Sorting and Selection

arXiv 2507.04351 ↗First posted 6 Jul 2025cs.RO cs.AIcited by 0

On the map: Multimodal LLMs / vision-language models → Embodied and 3D vision-language models

Abstract (arXiv)

Choosing appropriate fabrics is critical for meeting functional and quality demands in robotic textile manufacturing, apparel production, and smart retail. We propose MLLM-Fabric, a robotic framework leveraging multimodal large language models (MLLMs) for fabric sorting and selection. Built on a multimodal robotic platform, the system is trained through supervised fine-tuning and explanation-guided distillation to rank fabric properties. We also release a dataset of 220 diverse fabrics, each with RGB images and synchronized visuotactile and pressure data. Experiments show that our Fabric-Llama-90B consistently outperforms pretrained vision-language baselines in both attribute ranking and selection reliability. Code and dataset are publicly available at https://github.com/limanwang/MLLM-Fabric.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Embodied and 3D vision-language models, one of 16 directions in Multimodal LLMs / vision-language models. Builds on 15 of its 20 references that are in the map. First posted on arXiv 6 Jul 2025.

Builds on

15 of 20 references.

References · 15

  1. 2023GPT-4 Technical Reportcited by 18,396
  2. 2024The Llama 3 Herd of Modelscited by 14,715
  3. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,380
  4. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,459
  5. 2023Segment Anythingcited by 8,234
  6. 2025Janus-Pro: Unified Multimodal Understanding and Generation with Data and Model Scalingcited by 812
  7. 2024Binding Touch to Everything: Learning Unified Multimodal Tactile Representationscited by 95
  8. 2024A Touch, Vision, and Language Dataset for Multimodal Alignmentcited by 69
  9. 2024Do LLMs Know When to NOT Answer? Investigating Abstention Abilities of Large Language Modelscited by 57
  10. 2024Octopi: Object Property Reasoning with Large Tactile-Language Modelscited by 48
  11. 2017Active Clothing Material Perception using Tactile Sensing and Deep Learningcited by 30
  12. 2018ViTac: Feature Sharing between Vision and Tactile Sensing for Cloth Texture Recognitioncited by 27
3 more
  1. 2017Connecting Look and Feel: Associating the visual and tactile properties of physical materialscited by 22
  2. 2024Unfolding the Literature: A Review of Robotic Cloth Manipulationcited by 17
  3. 2023Multimodal Zero-Shot Learning for Tactile Texture Recognitioncited by 7

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  1. 2026Digital Twin Driven Textile Classification and Foreign Object Recognition in Automated Sorting Systems
  2. 2026GarmentPile++: Affordance-Driven Cluttered Garments Retrieval with Vision-Language Reasoning
  3. 2025BiFold: Bimanual Cloth Folding with Language Guidance
  4. 2024SKT: Integrating State-Aware Keypoint Trajectories with Vision-Language Models for Robotic Garment Manipulation
  5. 2025An analysis of vision-language models for fabric retrieval
  6. 2019Deep Imitation Learning of Sequential Fabric Smoothing From an Algorithmic Supervisor
  7. 2023RoboLLM: Robotic Vision Tasks Grounded on Multimodal Large Language Models
  8. 2024ChatGarment: Garment Estimation, Generation and Editing via Large Language Models