Instruction-tuning can be substantially optimized through enhanced diversity, resulting in models capable of handling a broader spectrum of tasks. However, existing data employed for such tuning often exhibit an inade...
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ISBN:
(纸本)9798891760608
Instruction-tuning can be substantially optimized through enhanced diversity, resulting in models capable of handling a broader spectrum of tasks. However, existing data employed for such tuning often exhibit an inadequate coverage of individual domains, limiting the scope for nuanced comprehension and interactions within these areas. To address this deficiency, we propose EXPLORE-INSTRUCT, a novel approach to enhance the data coverage to be used in domain-specific instruction-tuning through active explorationvia Large Language Models (LLMs). Built upon representative domain use cases, EXPLORE-INSTRUCT explores a multitude of variations or possibilities by implementing a search algorithm to obtain diversified and domain-focused instruction-tuning data. Our data-centric analysisvalidates the effectiveness of this proposed approach in improving domain-specific instruction coverage. Moreover, our model's performance demonstrates considerable advancements over multiple baselines, including those utilizing domain-specific data enhancement. Our findings offer a promising opportunity to improve instruction coverage, especially in domain-specific contexts, thereby advancing the development of adaptable language models. Our code, model weights, and data are public at https://***/fanqiwan/Explore-Instruct.
Satellite image denoising is of utmost importance in various applications weather monitoring, flood control and crop monitoring focusing on enhancing the visual quality of affected images. Denoising is a contemporary ...
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The proceedings contain 193 papers. The topics discussed include: visualanalysis of artificial intelligence in short video research based on CiteSpace;optimization design of financial shared services based on improve...
ISBN:
(纸本)9798331519032
The proceedings contain 193 papers. The topics discussed include: visualanalysis of artificial intelligence in short video research based on CiteSpace;optimization design of financial shared services based on improved algorithms and artificial intelligence;research on the application of artificial intelligence technology in microelectronics testing and fault diagnosis;artificial intelligence method for v2g oriented power distribution network control strategy and capacity analysis;research on indoor lighting optimization control system based on artificial intelligence algorithm;a model for evaluating the effectiveness of news dissemination under the combination of big data and artificial intelligence;and mechanical and electronic engineering design and control technology under artificial intelligence.
An important LAM professional competency is the ability to create metadata that effectively facilitates discovery of information resources in various settings. While some metadata courses for information professionals...
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Accurate prediction of cardiovascular disease risk is essential for improving healthcare outcomes and resource management. This study uses a cardiovascular disease dataset and applies deep learning models to forecast ...
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Mamba, a state-space model with selective mechanisms and hardware-aware architecture, has demonstrated outstanding performance in long sequence modeling tasks, particularly garnering widespread exploration and applica...
To date, investigations of strain-induced crystallization are out of reach for most mechanical laboratories due to costly X-ray diffraction facilities. Making use of the exothermic nature of such phase transition, inf...
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To date, investigations of strain-induced crystallization are out of reach for most mechanical laboratories due to costly X-ray diffraction facilities. Making use of the exothermic nature of such phase transition, infrared thermography based quantitative surface calorimetry has provided an alternative approach to investigate strain-induced crystallinity in conventional mechanical laboratories. Moreover, this calorimetric approach provides continuum quantities of interest for enriching and validating constitutive models. Nevertheless, its application has been confined to the evaluation of crystallinity under only the loading case. In this contribution, strain-induced crystallization is investigated in various types of natural rubbers by coupling dataanalysis with domain knowledge of thermodynamics. It pushes the boundaries of the current quantitative surface calorimetry methodology to explore not only the crystallinity during loading-unloading cycles but also different compositions of the internal energy.
visual Speech Recognition (vSR) aims to predict spoken content by analyzing lip movements in videos. Recently reported state-of-the-art results in vSR often rely on increasingly large amounts of video data, while the ...
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We present a generic Reinforcement Learning (RL) framework optimized for crafting adversarial attacks on different model types spanning from ECG signal analysis (1D), image classification (2D), and video classificatio...
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ISBN:
(纸本)1577358872
We present a generic Reinforcement Learning (RL) framework optimized for crafting adversarial attacks on different model types spanning from ECG signal analysis (1D), image classification (2D), and video classification (3D). The framework focuses on identifying sensitive regions and inducing misclassifications with minimal distortions and various distortion types. The novel RL method outperforms state-of-the-art methods for all three applications, proving its efficiency. Our RL approach produces superior localization masks, enhancing interpretability for image classification and ECG analysis models. For applications such as ECG analysis, our platform highlights critical ECG segments for clinicians while ensuring resilience against prevalent distortions. This comprehensive tool aims to bolster both resilience with adversarial training and transparency across varied applications and data types.
Low-light image enhancement is for the sake of improving the quality of visual perception of captured data on the conditions under low-light to obtain more information, and has gradually become a research hotspot in t...
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