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A focused stream of recent stories from the sources curated for this community. Latest: Google Research Introduces GlucoFM: A 0.72M-Parameter Dual-Stream Foundation Model for Continuous Glucose Monitoring, Can You Trust Frozen Hematology Foundation Models under Acquisition Shift?, and SHIFT-LLM: Distribution Shift Correction in Depth-Pruned LLMs. Page 47.
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Google releases GlucoFM, a 0.72M-parameter dual-stream CGM foundation model that beats larger baselines on metabolic phenotyping tasks.
Entities: Google
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Abstract page for arXiv paper 2608.25148: Can You Trust Frozen Hematology Foundation Models under Acquisition Shift?
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Abstract page for arXiv paper 2608.25068: SHIFT-LLM: Distribution Shift Correction in Depth-Pruned LLMs
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Abstract page for arXiv paper 2608.24956: Synergising Local Geo-Environmental Characteristics with Spatial Context for Enhancing Landslide Susceptibility Mapping
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Abstract page for arXiv paper 2608.24935: A Lightweight Multimodal Vision-Language Framework for Early-Stage Anatomical Green Fruit Classification in Commercial Orchards
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Abstract page for arXiv paper 2608.24934: Fusing Perceptual Vision Experts with Multimodal Large Language Models for Explainable Plant Disease Diagnosis: From Benchmark Imagery to Real-World Robotic Field Validation
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Abstract page for arXiv paper 2608.25061: DataKernelBench: Can LLMs Optimize Database Queries on GPUs?
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Abstract page for arXiv paper 2608.25028: Behind the [MASK]: Disentangling Representation and Faithfulness in DAPF-Based Dementia Detection
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Abstract page for arXiv paper 2608.25005: The Imperfective Paradox Is Not Necessarily in Large Language Models: A Benchmark Failure Before a Model Failure
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Abstract page for arXiv paper 2608.24988: Does Fine-Tuning Undo Activation Steering? Behavioural Recovery Without Weight-Edit Reversal
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Abstract page for arXiv paper 2608.24982: Unsupervised Post-Training of Foundation Models: A Survey
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Abstract page for arXiv paper 2608.24920: Semantic Variability of Replies Across LLMs: Implications for Designing Conversation-Based Assessment
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