SciPy
PulseAugur coverage of SciPy — every cluster mentioning SciPy across labs, papers, and developer communities, ranked by signal.
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New benchmark tests LLMs on real-world code optimization
Researchers have introduced SWE-fficiency, a new benchmark designed to evaluate the performance optimization capabilities of language models on real-world software repositories. The benchmark includes 498 tasks across n…
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LLM evaluation metrics need confidence intervals to distinguish signal from noise
Evaluating Large Language Models (LLMs) requires understanding the uncertainty inherent in performance metrics. A single score, such as 84.2% accuracy, can be misleading because it doesn't account for sampling error. By…
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NVIDIA Canary-1B-v2 Tutorial: ASR, Translation, and Subtitle Generation
This tutorial demonstrates how to utilize NVIDIA's Canary-1B-v2 model for advanced audio processing tasks, including automatic speech recognition (ASR), translation, and subtitle generation. The guide covers setting up …
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New research explores genetic programming for symbolic regression · 2 sources tracked
Two recent arXiv papers explore genetic programming (GP) for symbolic regression (SR). One study, "Evaluation of Population Initialization Methods for Genetic Programming-based Symbolic Regression," found that different…
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TimeCopilot tutorial shows end-to-end forecasting with foundation models
This tutorial demonstrates how to build an end-to-end forecasting pipeline using TimeCopilot, a tool that integrates various forecasting models. The process involves preparing a dataset with real airline passenger data …
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New framework distills foundation models for specialized time-series forecasting
Researchers have developed a novel framework called Guard to distill knowledge from large, general-purpose foundation models (FMs) into lightweight, specialized time-series forecasters. This approach addresses the chall…
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PyTorch gets differentiable sparse linear algebra library
Researchers have developed torch-sla, an open-source Python library designed to provide differentiable sparse linear algebra capabilities within PyTorch. This library addresses a gap in PyTorch's existing functionalitie…