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Creators/Authors contains: "Kim, D"

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  1. ; ; ; ; ; (, USENIX NSDI)
    Free, publicly-accessible full text available April 28, 2026
  2. ; ; ; ; ; (, IEEE)
    Free, publicly-accessible full text available December 20, 2025
  3. ; ; ; ; ; ; (, arXiv preprints)
    Finetuned large language models (LLMs) have shown remarkable performance in financial tasks, such as sentiment analysis and information retrieval. Due to privacy concerns, finetuning and deploying financial LLMs (FinLLMs) locally are crucial for institutions and individuals. In this paper, we employ quantized low-rank adaptation (QLoRA) to finetune FinLLMs, which leverage low-rank structure and quantization technique to significantly reduce computational requirements while maintaining model performance. We also employ data and pipeline parallelism to enable local finetuning on commodity GPUs. Experiments on financial datasets validate the efficacy of our approach in yielding notable improvements over the base models. 
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    Free, publicly-accessible full text available December 16, 2025
  4. ; ; ; ; ; ; ; ; ; ; et al (, arXiv preprints)
    Financial large language models (FinLLMs) have been applied to various tasks in business, finance, accounting, and auditing. Complex financial regulations and standards are critical to financial services, which LLMs must comply with. However, FinLLMs’ performance in understanding and interpreting financial regulations has rarely been studied. Therefore, we organize the Regulations Challenge, a shared task at COLING FinNLP-FNP-LLMFinLegal2025. It encourages the academic community to explore the strengths and limitations of popular LLMs. We create 9 novel tasks and corresponding question sets. In this paper, we provide an overview of these tasks and summarize participants’ approaches and results. We aim to raise awareness of FinLLMs’ professional capability in financial regulations. 
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    Free, publicly-accessible full text available December 15, 2025
  5. ; (, ASEE)
    Accepted Manuscript Full Text Available
  6. ; (, ASEE)
    Accepted Manuscript Full Text Available
  7. ; ; (, ASEE)
    Accepted Manuscript Full Text Available
  8. ; ; ; ; (, ASEE)
    Accepted Manuscript Full Text Available
  9. ; ; ; ; ; ; ; ; ; ; et al (, Physical Review Letters)
    We report the first detection of coherent elastic neutrino-nucleus scattering (CEvNS) on natural germanium, measured at the Spallation Neutron Source at Oak Ridge National Laboratory. The Ge-Mini detector of the COHERENT collaboration employs large-mass, low-noise, high-purity germanium spectrometers, enabling excellent energy resolution, and an analysis threshold of 1.5 keV electron-equivalent ionization energy. We observe an on-beam excess of 20.6 − 6.3 + 7.1 counts with a total exposure of 10.22 GWhkg, and we reject the no-CEvNS hypothesis with 3.9 σ significance. The result agrees with the predicted standard model of particle physics signal rate within 2 σ . Published by the American Physical Society2025 
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    Free, publicly-accessible full text available June 1, 2026
  10. (, The Proceedings of 2023 ASEE Annual Conference and Exhibitions)
    Accepted Manuscript Full Text Available