Catha edulis
PulseAugur coverage of Catha edulis — every cluster mentioning Catha edulis across labs, papers, and developer communities, ranked by signal.
6 day(s) with sentiment data
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New MMPM framework improves pedestrian trajectory prediction from video
Researchers have developed a new framework called MMPM to improve pedestrian trajectory prediction from ego-centric videos. This model addresses the challenge of multimodal pedestrian behavior by separately modeling dis…
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LLaMA user seeks advice on Gemma 4 31B quantizations and hardware optimization
A user on the r/LocalLLaMA subreddit is seeking advice on optimizing their setup for running large language models, specifically the Gemma 4 31B model. They are trying to determine if newer 'QAT' (Quantized Aware Traini…
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Google Gemma 4 12B performance boosted by quantization techniques
A blog post compares the performance of the Google Gemma 4 12B model with and without quantization techniques, specifically MTP (Mixed Precision Training) and QAT (Quantization-Aware Training). The author provides speed…
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Anthropic's Mythos AI to Transform Cybersecurity; Google Optimizes Gemma 4 for Local Use
Anthropic has reportedly developed a new AI model named "Mythos," which is expected to significantly impact cybersecurity defenses. Meanwhile, Google has introduced a memory-saving technique called QAT for its Gemma 4 m…
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llama.cpp integrates Gemma 4 MTP for faster local model performance
The llama.cpp project has merged support for Gemma 4 MTP, a feature that enhances the speed and efficiency of local large language models. This integration allows users to leverage Gemma 4 with Quantization Aware Traini…
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New MUSCLE-NET model improves pedestrian trajectory forecasting
Researchers have developed MUSCLE-NET, a novel network designed for predicting pedestrian trajectories in autonomous driving and transportation systems. This new model addresses limitations in existing methods by better…
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Swin Transformer shows resilience to FP4 quantization in anomaly segmentation
A new research paper explores how model architecture, scale, and specific quantization-aware training (QAT) recipes affect the quality of anomaly segmentation models when using FP4 precision. The study found that attent…
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Gemma 4 QAT models spark debate over performance and utility
Users are discussing the performance and utility of Gemma 4 QAT (Quantization Aware Training) models, particularly comparing them to standard quantizations. While some users report improved speed and quality for general…