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[1] AIDetection
帮助检测
来源:ARXIV_20250324
[2] Universal approximation property of neural stochastic differential equations
神经随机微分方程的普遍逼近性质
来源:ARXIV_20250324
[3] Forecasting U.S. equity market volatility with attention and sentiment to the economy
根据对经济的关注和情绪预测美国股市波动
来源:ARXIV_20250326
[4] Demand Estimation with Text and Image Data
基于文本和图像数据的需求估计
来源:ARXIV_20250327
[5] A Causal Perspective of Stock Prediction Models
股票预测模型的因果视角
来源:ARXIV_20250328
[1] AIDetection
标题:帮助检测
作者:Andy Buschmann
来源:ARXIV_20250324
Abstract : This paper introduces a simple JavaScript based web application designed to assist educators in detecting AI generated content in student essays and written assignments. Unlike existing AI detection tools that rely on obfuscated machine learning models, this http URL employs a heuristic based approach to identify common syntactic traces left by generative AI models, such as ChatGPT, Claude, Grok, DeepSeek, Gemini,......(摘要翻译及全文见知识星球)
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[2] Universal approximation property of neural stochastic differential equations
标题:神经随机微分方程的普遍逼近性质
作者:Anna P. Kwossek, David J. Prömel, Josef Teichmann
来源:ARXIV_20250324
Abstract : We identify various classes of neural networks that are able to approximate continuous functions locally uniformly subject to fixed global linear growth constraints. For such neural networks the associated neural stochastic differential equations can approximate general stochastic differential equations, both of It diffusion type, arbitrarily well. Moreover, quantitative error estimates are derived for stochastic differential equations with sufficiently regular coefficients.......(摘要翻译及全文见知识星球)
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[3] Forecasting U.S. equity market volatility with attention and sentiment to the economy
标题:根据对经济的关注和情绪预测美国股市波动
作者:Martina Halousková, Štefan Lyócsa
来源:ARXIV_20250326
Abstract : Macroeconomic variables are known to significantly impact equity markets, but their predictive power for price fluctuations has been underexplored due to challenges such as infrequency and variability in timing of announcements, changing market expectations, and the gradual pricing in of news. To address these concerns, we estimate the public s attention and sentiment towards ten scheduled macroeconomic variables using social media,......(摘要翻译及全文见知识星球)
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[4] Demand Estimation with Text and Image Data
标题:基于文本和图像数据的需求估计
作者:Giovanni Compiani, Ilya Morozov, Stephan Seiler
来源:ARXIV_20250327
Abstract : We propose a demand estimation method that leverages unstructured text and image data to infer substitution patterns. Using pre trained deep learning models, we extract embeddings from product images and textual descriptions and incorporate them into a random coefficients logit model. This approach enables researchers to estimate demand even when they lack data on product attributes or when consumers value hard......(摘要翻译及全文见知识星球)
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[5] A Causal Perspective of Stock Prediction Models
标题:股票预测模型的因果视角
作者:Songci Xu, Qiangqiang Cheng, Chi-Guhn Lee
来源:ARXIV_20250328
Abstract : In the realm of stock prediction, machine learning models encounter considerable obstacles due to the inherent low signal to noise ratio and the nonstationary nature of financial markets. These challenges often result in spurious correlations and unstable predictive relationships, leading to poor performance of models when applied to out of sample (OOS) domains. To address these issues, we investigate textit......(摘要翻译及全文见知识星球)
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