mlsanityData to 7 Oct 2026

OpenQlaw: An Agentic AI Assistant for Analysis of 2D Quantum Materials

arXiv 2603.17043 ↗First posted 17 Mar 2026cs.CVcited by 1

On the map: LLM reasoning → Clinical and biomedical applications

also in 1 more
Abstract (arXiv)

Physics-aware multimodal large language models (MLLMs) can localize and characterize two-dimensional (2D) material flakes from optical microscopy images, producing rich candidate observations and scientific reasoning. However, downstream workflows also require reliable operations over these outputs, including counting, selection, measurement, and rendering. We present OpenQlaw, a tool-using agentic artificial intelligence (AI) system that connects a general vision-language orchestrator with Physics-Aware Instruction Tuning (QuPAINT), a physics-aware domain expert. Through evaluation on fully reviewed optical microscopy images, we show that summary counts derived from longer free-form candidate enumerations can become inconsistent with the underlying returned observations. Controlled replay experiments further show that structuring the same observations alone does not resolve this behavior, while deterministic delegation returns the exact requested record count in all cohort trials. To address this, we introduce State-Grounded OpenQlaw, which converts expert outputs into image-scoped observation records and performs deterministic scientific operations over explicitly identified records with refusal conditions when required information is unavailable. This preserves the expert's original analysis while making downstream operations exact over the selected record and independently evaluable from candidate-list discrepancies.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Placed in Clinical and biomedical applications, one of 17 directions in LLM reasoning. Builds on 29 of its 42 references that are in the map. First posted on arXiv 17 Mar 2026.

Builds on

29 of 42 references.

References · 29

  1. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  2. 2025Qwen3 Technical Reportcited by 8,195
  3. 2023Segment Anythingcited by 8,158
  4. 2020End-to-End Object Detection with Transformerscited by 7,384
  5. 2015You Only Look Once: Unified, Real-Time Object Detectioncited by 4,829
  6. 2020Deformable DETR: Deformable Transformers for End-to-End Object Detectioncited by 3,410
  7. 2024SAM 2: Segment Anything in Images and Videoscited by 2,784
  8. 2021BiMaL: Bijective Maximum Likelihood Approach to Domain Adaptation in Semantic Scene Segmentationcited by 31
  9. 2023FREDOM: Fairness Domain Adaptation Approach to Semantic Scene Understandingcited by 27
  10. 2019Deep-Learning-Based Image Segmentation Integrated with Optical Microscopy for Automatically Searching for Two-Dimensional Materialscited by 17
  11. 2023Fairness Continual Learning Approach to Semantic Scene Understanding in Open-World Environmentscited by 16
  12. 2022Two-Dimensional Quantum Material Identification via Self-Attention and Soft-labeling in Deep Learningcited by 15
17 more
  1. 2023Quantum Vision Clusteringcited by 13
  2. 2023FALCON: Fairness Learning via Contrastive Attention Approach to Continual Semantic Scene Understandingcited by 13
  3. 2022OTAdapt: Optimal Transport-based Approach For Unsupervised Domain Adaptationcited by 12
  4. 2022Self-supervised Domain Adaptation in Crowd Countingcited by 11
  5. 2022CONDA: Continual Unsupervised Domain Adaptation Learning in Visual Perception for Self-Driving Carscited by 11
  6. 2024Quantum Visual Feature Encoding Revisitedcited by 10
  7. 2024Diffusion-Inspired Quantum Noise Mitigation in Parameterized Quantum Circuitscited by 10
  8. 2019Defining Quantum Neural Networks via Quantum Time Evolutioncited by 8
  9. 2024Hierarchical Quantum Control Gates for Functional MRI Understandingcited by 8
  10. 2024Quantum-Brain: Quantum-Inspired Neural Network Approach to Vision-Brain Understandingcited by 7
  11. 2025QMoE: A Quantum Mixture of Experts Framework for Scalable Quantum Neural Networkscited by 7
  12. 2024EAGLE: Efficient Adaptive Geometry-based Learning in Cross-view Understandingcited by 6
  13. 2024MaskTerial: A Foundation Model for Automated 2D Material Flake Detectioncited by 4
  14. 2025varphi-Adapt: A Physics-Informed Adaptation Learning Approach to 2D Quantum Material Discoverycited by 3
  15. 2026QuPAINT: Physics-Aware Instruction Tuning Approach to Quantum Material Discoverycited by 3
  16. 2025CLIFF: Continual Learning for Incremental Flake Features in 2D Material Identificationcited by 2
  17. 2026φ-DPO: Fairness Direct Preference Optimization Approach to Continual Learning in Large Multimodal Modelscited by 2

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 1.

1 paper.

  1. 2026QLAM: A Quantum Long-Attention Memory Approach to Long-Sequence Token Modelingcited by 0

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  1. 2026QuPAINT: Physics-Aware Multimodal Reasoning for Quantum Material Characterization
  2. 2026EAA: Automating materials characterization with vision language model agents
  3. 2024Autonomous Microscopy Experiments through Large Language Model Agents
  4. 2026An LLM System for Autonomous Variational Quantum Circuit Design
  5. 2026Agentic AI for Scientific Reasoning in Autonomous Quantum Sensing Experiments
  6. 2025xChemAgents: Agentic AI for Explainable Quantum Chemistry
  7. 2026Qumus: Realization of An Embodied AI Quantum Material Experimentalist
  8. 2025Toward Greater Autonomy in Materials Discovery Agents: Unifying Planning, Physics, and Scientists