research-papers
Original Paper: https://arxiv.org/abs/2307.09909 By: Urszula Jessen, Michal Sroka, Dirk Fahland Abstract: This research investigates the application of Large Language Models (LLMs) to augment conversational agents in process mining, aiming to tackle its inherent complexity and diverse skill requirements. While LLM advancements present novel opportunities for
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Original Paper: https://arxiv.org/abs/2307.01142 By: Stephen MacNeil, Andrew Tran, Joanne Kim, Ziheng Huang, Seth Bernstein, Dan Mogil Abstract: To help users do complex work, researchers have developed techniques to integrate AI and human intelligence into user interfaces (UIs). With the recent introduction of large language models
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Original Paper: https://arxiv.org/abs/2306.06211 By: Chaoning Zhang, Fachrina Dewi Puspitasari, Sheng Zheng, Chenghao Li, Yu Qiao, Taegoo Kang, Xinru Shan, Chenshuang Zhang, Caiyan Qin, Francois Rameau, Lik-Hang Lee, Sung-Ho Bae, Choong Seon Hong Abstract: Segment anything model (SAM) developed by Meta AI Research has recently attracted
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Original Paper: https://arxiv.org/abs/2306.13653 By: Jiaqi Ma, Tianheng Cheng, Guoli Wang, Qian Zhang, Xinggang Wang, Lefei Zhang Abstract: Image restoration aims to reconstruct degraded images, e.g., denoising or deblurring. Existing works focus on designing task-specific methods and there are inadequate attempts at universal methods. However,
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Original Paper: https://arxiv.org/abs/2302.05698 By: Jiacheng Ye, Zhiyong Wu, Jiangtao Feng, Tao Yu, Lingpeng Kong Abstract: Large pretrained language models (LMs) have shown impressive In-Context Learning (ICL) ability, where the model learns to do an unseen task via a prompt consisting of input-output examples as the
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Original Paper: https://arxiv.org/abs/2307.05493 By: David James Woo, Kai Guo, Hengky Susanto Abstract: ChatGPT is a state-of-the-art (SOTA) chatbot. Although it has potential to support English as a foreign language (EFL) students' writing, to effectively collaborate with it, a student must learn to engineer prompts,
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Original Paper: https://arxiv.org/abs/2306.11025 By: Xinli Yu, Zheng Chen, Yuan Ling, Shujing Dong, Zongyi Liu, Yanbin Lu Abstract: This paper presents a novel study on harnessing Large Language Models' (LLMs) outstanding knowledge and reasoning abilities for explainable financial time series forecasting. The application of machine
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Original Paper: https://arxiv.org/abs/2306.08833 By: Chaofan Wang, Samuel Kernan Freire, Mo Zhang, Jing Wei, Jorge Goncalves, Vassilis Kostakos, Zhanna Sarsenbayeva, Christina Schneegass, Alessandro Bozzon, Evangelos Niforatos Abstract: ChatGPT and other large language models (LLMs) have proven useful in crowdsourcing tasks, where they can effectively annotate machine