Causal inference enables us to move beyond merely observing correlations in understanding the actual causal relationships between variables, but how to connect it withmachinelearning model still needs careful and sc...
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Using naturallanguageprocessing technology and Python software, word frequency statistics were performed on the relevant policy texts of the collaborative innovation of science and technology in Beijing-Tianjin-Hebe...
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Organizations are increasingly adopting chatbots to deliver enterprise-specific search services, providing conversational and contextually appropriate naturallanguage responses to user queries. To meet complex demand...
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Time series forecasting, as an important field of data mining, is of great significance in revealing future trends. Traditional statistical models have limitations in handling nonlinear and non-stationary time series....
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As datasets continue to expand, the significance of feature selection in identifying influential features for classification becomes increasingly apparent. Meanwhile, the performance of a classifier has a great impact...
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To offer the military personnel a good service of assisting them to get information about enemy's equipment outside Internet, we build a system named MilChat which includes a large language model that has the abil...
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the proceedings contain 69 papers. the topics discussed include: dynamic region fusion neural radiance fields for audio-driven talking head generation;food named entity recognition with BERT and adversarial training;a...
ISBN:
(纸本)9798350354973
the proceedings contain 69 papers. the topics discussed include: dynamic region fusion neural radiance fields for audio-driven talking head generation;food named entity recognition with BERT and adversarial training;a multimodal named entity recognition approach based on multi-perspective contrastive learning;a selective ensemble learning method for time series forecasting;MilChat: a large language model and application for military equipment;five years of COVID-19 discourse on Instagram: a labeled Instagram dataset of over half a million posts for multilingual sentiment analysis;VTN-EG: CLIP-based visual and textual fusion network for entity grounding;fact-aware abstractive summarization based on prompt information and re-ranking;and poisoning attacks against non-IID federated learning with mixed-data calibration.
Large language models (LLMs) have rapidly advanced and are increasingly utilized in Finance. these technologies offer innovative decision-making tools for financial investors, particularly as traditional methods often...
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Previous research on stance detection usually focuses on incorporating sentiment analysis to help stance detection, whereas texts with ironic maneuvers may reverse the entire semantics. In this paper, we propose the E...
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As air combat technologies evolve, beyond-visual-range (BVR) operations have become the dominant mode of engagement. this paper addresses the autonomous decision-making challenges in BVR air combat by proposing an imp...
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