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#machinelearning

134 posts96 participants7 posts today
Public
Compsci Weekly

UCLA Researchers Released OpenVLThinker-7B: A Reinforcement Learning Driven Model for Enhancing Complex Visual Reasoning and Step-by-Step Problem Solving in Multimodal Systems

marktechpost.com/2025/03/28/uc

Discussions: discu.eu/q/https://www.marktec

MarkTechPost · UCLA Researchers Released OpenVLThinker-7B: A Reinforcement Learning Driven Model for Enhancing Complex Visual Reasoning and Step-by-Step Problem Solving in Multimodal SystemsLarge vision-language models (LVLMs) integrate large language models with image processing capabilities, enabling them to interpret images and generate coherent textual responses. While they excel at recognizing visual objects and responding to prompts, they often falter when presented with problems requiring multi-step reasoning. Vision-language tasks like understanding charts, solving visual math questions, or interpreting diagrams demand more than recognition; they need the ability to follow logical steps based on visual cues. Despite advancements in model architecture, current systems consistently struggle to produce accurate and interpretable answers in such complex scenarios. A major limitation in current vision-language models is their inability
#compsci#machinelearning
Public
Geospatial Technologies

🌾 Cutting-Edge Research in Land Cover Mapping! 🛰️

Thrilled to share a pivotal study by our Master of Geospatial Technologies alumni published in ISPRS Archives! Their work leverages Sentinel-2 time-series data to automate land cover and crop mapping in Portugal, achieving 76% accuracy with 31 distinct classes.

📄 Open-access paper: doi.org/10.5194/isprs-archives

➡️ Master applications close May 31!
#GeospatialTech #RemoteSensing #PrecisionAgriculture #Sentinel2 #MachineLearning

Public
Geospatial Technologies

🌐 Research Alert from Our Alumni! 📊

Excited to highlight a groundbreaking publication by Carles Milà (Master of Geospatial Technologies alum) in Methods in Ecology and Evolution! The paper introduces Nearest Neighbour Distance Matching Leave-One-Out Cross-Validation (NNDM LOO CV), a novel method for robust map validation in spatial prediction tasks.

📄 Open-access paper: doi.org/10.1111/2041-210X.13851
#GeospatialTech #SpatialAnalysis #MachineLearning #Ecology #RemoteSensing

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