Mu Li
6 papers in the PaperMetrix corpus
Papers by this author
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Earthformer: Exploring Space-Time Transformers for Earth System Forecasting
2022 · arXiv (Cornell University)
Conventionally, Earth system (e.g., weather and climate) forecasting relies on numerical simulation with complex physical models and are hence both expensive in computation and demanding on domain expertise. With the explosive growth of the spatiotemporal …
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Design of Digital Agricultural Product Traceability and Quality Traceability System Supported By Big Data Analysis
2024
With the increasing attention of the society to the quality and safety of agricultural products, the digital agricultural product traceability and quality traceability system has become an important means to solve the hidden dangers of …
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EmergentTTS-Eval: Evaluating TTS Models on Complex Prosodic, Expressiveness, and Linguistic Challenges Using Model-as-a-Judge
2025
Text-to-Speech (TTS) benchmarks often fail to capture how well models handle nuanced and semantically complex text. Building on $\textit{EmergentTTS}$, we introduce $\textit{EmergentTTS-Eval}$, a comprehensive benchmark covering six challenging TTS scenarios: emotions, paralinguistics, foreign words, syntactic …
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Achieving Human Parity on Automatic Chinese to English News Translation
2018 · arXiv (Cornell University)
Machine translation has made rapid advances in recent years. Millions of people are using it today in online translation systems and mobile applications in order to communicate across language barriers. The question naturally arises whether …
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Style Transfer as Unsupervised Machine Translation
2018 · arXiv (Cornell University)
Language style transferring rephrases text with specific stylistic attributes while preserving the original attribute-independent content. One main challenge in learning a style transfer system is a lack of parallel data where the source sentence is …
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Automatic Chain of Thought Prompting in Large Language Models
2022 · arXiv (Cornell University)
Large language models (LLMs) can perform complex reasoning by generating intermediate reasoning steps. Providing these steps for prompting demonstrations is called chain-of-thought (CoT) prompting. CoT prompting has two major paradigms. One leverages a simple prompt …