Tag: Large Language Model
All the articles with the tag "Large Language Model".
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SEAL: Steerable Reasoning Calibration of Large Language Models for Free
Published: at 06:16 PM
87.52 🤔SEAL, a training-free method, calibrates the reasoning process of Large Language Models by steering latent representations to reduce redundant thoughts, achieving up to 14.1% accuracy improvement and 50.4% token reduction across diverse benchmarks.
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Think2SQL: Reinforce LLM Reasoning Capabilities for Text2SQL
Published: at 11:18 PM 87.33 🤔本文通过结合监督微调（SFT）、强化学习（RL）及细粒度奖励函数（如QATCH），显著提升了小型LLM在Text2SQL任务中的推理能力和性能，Think2SQL-7B模型在BIRD数据集上超越了400B+参数模型。
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AI agents may be worth the hype but not the resources (yet): An initial exploration of machine translation quality and costs in three language pairs in the legal and news domains
Published: at 12:22 AM 86.86 🤔本文通过实证评估五种机器翻译范式，发现推理增强的大型语言模型（如o1-preview）在人工评估中表现出色，超越传统NMT，而多智能体系统虽具潜力，但因高计算成本和语言对表现不一致而受限。
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Activated LoRA: Fine-tuned LLMs for Intrinsics
Published: at 12:17 AM 86.84 🤔本文提出 Activated LoRA (aLoRA)，一种改进的 LoRA 框架，通过仅对激活后 token 适配权重，复用基础模型 KV 缓存，实现高效动态适配，并在多个任务上保持与标准 LoRA 相当的性能，同时显著降低推理成本。
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LENSLLM: Unveiling Fine-Tuning Dynamics for LLM Selection
Published: at 06:16 PM 86.80 🤔LENSLLM introduces a Hessian-based PAC-Bayes framework and NTK-based scaling model for LLM selection, achieving up to 91.1% accuracy and 88.5% computational cost reduction by modeling fine-tuning dynamics across diverse tasks.