The next train = 下一班车 by Lou, Mei Jun

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Investigating Fine-Tuning of Language Models for Multiple-Choice Questions by Wang, Ivy A.

“…We specifically investigate training data properties related to positional bias in fine-tuned language model performance on correctly answering MCQs. …”
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Investigating fine-tuning of large language models for text summarisation by Khaliq, Usama, Patel, Preeti

“…In contrast, bigger models, like GPT-4, with its 1.7 trillion parameters, generated near-perfect summaries without having been trained on a specific dataset. The limited performance increase from the fine-tuned models was likely due to small datasets and medium-sized LLMs. …”
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HMM speech recognition with reduced training by Foo, Say Wei, Yap, Timothy

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Effects of auditory training in older adults by Lai, Yvonne C. Y., Ng, P. S., Chan, Alice Hiu Dan, Wong, Francis C. K.

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OSPC: Multimodal Harmful Content Detection using Fine-tuned Language Models by Cai, Bill

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Robustness to training disturbances in SpikeProp Learning by Shrestha, Sumit Bam, Song, Qing

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RITA: Group Attention is All You Need for Timeseries Analytics by Liang, Jiaming, Cao, Lei, Madden, Samuel, Ives, Zack, Li, Guoliang

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Design of a linear motor-based magnetic levitation train prototype by Mohd Zaidi, Muhammad Syafiq, Mohd Hassan, Siti Lailatul, Abdul Halim, Ili Shairah, Sulaiman, Nasri

“…This study explores the modelling of a magnetic levitation train and its implementation using a microcontroller. …”
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Bystanders by Rowe, Mary, Giraldo-Kerr, Anna

“…If they take helpful action, they may be called “active” or “positive” bystanders, or “up-standers.” …”
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Who learns when workers are trained? a case of safety training of maintenance contractors’ workers for a major petrochemical plant shutdown by A., Fakhru'l-Razi, S.E., Iyuke, M.B., Hassan, M.S., Aini

“…Subsequently, detailed correlation using the model was performed on all Ei=f(A, X, L, P, Rp, RR, T), which were plots of training effectiveness vs Ei as percentages, gave good quantitative parameters for further simulations in the future. …”
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Internet based training for engineers in the aspect of six sigma by Chatta Kannappa Srinivas.

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EyeTrAES: Fine-grained, Low-Latency Eye Tracking via Adaptive Event Slicing by Sen, Argha, Bandara, Nuwan, Gokarn, Ila, Kandappu, Thivya, Misra, Archan

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Battery plug-in electric vehicle concept design : (motor-drive train and batterypack) by Liong, Farandy Angesti.

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Evaluating Adaptive Layer Freezing through Hyperparameter Optimization for Enhanced Fine-Tuning Performance of Language Models by Figueroa, Reinaldo

“…Additionally, we explore which layers inside the models usually hold more contextual information from pre-training that might be valuable to keep ‘frozen’ when fine-tuning on small datasets. …”
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An Effective Med-VQA Method Using a Transformer with Weights Fusion of Multiple Fine-Tuned Models by Al-Hadhrami, Suheer, Menai, Mohamed El Bachir, Al-Ahmadi, Saad, Alnafessah, Ahmad

“…The second model, the greedy-soup-based model, uses a greedy soup technique based on the fusion of multiple fine-tuned models to set the model parameters. The greedy soup selects the model parameters by fusing the model parameters that have significant performance on the validation accuracy in training. …”
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An Unusual Harassment Training That Was Warmly Received and Also Inspired Bystanders by Rowe, Mary P.

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Dictionary training for sparse representation as generalization of K-means clustering by Sahoo, Sujit Kumar, Makur, Anamitra

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The training intensity distribution of marathon runners across performance levels by Muniz-Pumares, Daniel, Hunter, Ben, Meyler, Samuel, Maunder, Ed, Smyth, Barry

“…Results: Training volume across all runners was 45.1±26.4 km·wk-1, but the fastest runners within the dataset (marathon time 120-150 min) accumulated >3 times more volume than slower runners. …”
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Effective image synthesis for effective deep neural network training by Cui, Kaiwen

“…To address this issue, a solution called data-limited image generation has been proposed. …”
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