Tag: Large Language Model
All the articles with the tag "Large Language Model".
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AI in Money Matters
This paper investigates the cautious adoption of Large Language Models like ChatGPT in the Fintech industry through qualitative interviews, highlighting professionals' optimism for routine task automation, concerns over regulatory inadequacies, and interest in bespoke models to ensure compliance and data control.
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Unlocking Efficient Long-to-Short LLM Reasoning with Model Merging
本文通过模型融合方法整合快速思维和慢速推理能力,实现长到短推理,在7B模型上将响应长度压缩高达55%且保持性能,提出了一种高效解决大语言模型过度思考问题的方案。
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Why Distillation can Outperform Zero-RL: The Role of Flexible Reasoning
本文通过仅使用920个蒸馏样本对Qwen2.5-32B基础模型进行监督微调,显著超越了资源密集的Zero-RL方法,并揭示了蒸馏模型通过拟人化语言和高级认知行为实现更灵活推理的机制。
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Towards Safer Pretraining: Analyzing and Filtering Harmful Content in Webscale datasets for Responsible LLMs
This paper proposes a three-dimensional taxonomy and develops TTP and HarmFormer tools to filter harmful content from web-scale LLM pretraining datasets, revealing significant toxicity prevalence and persistent safety gaps through benchmarks like HAVOC.
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A Large-Scale Empirical Analysis of Custom GPTs' Vulnerabilities in the OpenAI Ecosystem
This paper conducts a large-scale empirical analysis of 14,904 custom GPTs in the OpenAI store, revealing over 95% lack adequate security against attacks like roleplay (96.51%) and phishing (91.22%), introduces a multi-metric popularity ranking system, and highlights the need for enhanced security in both custom and base models.