Tag: Large Language Model
All the articles with the tag "Large Language Model".
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R1-Code-Interpreter: Training LLMs to Reason with Code via Supervised and Reinforcement Learning
Published: at 11:42 AM
87.73 🤔本文提出 R1-Code-Interpreter 框架，通过监督微调和强化学习训练大型语言模型动态生成和执行代码，在 144 个推理和规划任务上显著提升准确率，R1-CI-14B 达到 64.1%，接近 GPT-4o+Code Interpreter 的性能。
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Rodimus*: Breaking the Accuracy-Efficiency Trade-Off with Efficient Attentions
Published: at 11:29 AM 87.72 🤔本文提出 Rodimus 和 Rodimus+ 模型，通过数据依赖温度选择（DDTS）和滑动窗口共享键注意力（SW-SKA）机制，在保持性能的同时显著降低大型语言模型的计算和内存复杂度，挑战了准确性与效率的权衡。
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MaskSearch: A Universal Pre-Training Framework to Enhance Agentic Search Capability
Published: at 11:19 AM 87.72 🤔本文提出 MASKSEARCH 框架，通过 Retrieval-Augmented Mask Prediction (RAMP) 预训练任务结合监督微调和强化学习，显著提升了大型语言模型在开放域多跳问答任务中的代理搜索能力。
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Communicating Activations Between Language Model Agents
Published: at 10:59 AM 87.71 🤔This paper introduces Activation Communication (AC), a novel method for inter-LLM communication using intermediate activations instead of natural language, achieving up to 27% performance improvement over traditional methods with significantly reduced compute across coordination games and reasoning benchmarks.
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Merge to Mix: Mixing Datasets via Model Merging
Published: at 11:24 AM 87.71 🤔本文提出*Merge to Mix*方法，通过模型合并技术作为代理，高效选择数据集混合用于大型模型微调，在图像分类和语言任务中显著优于传统方法，接近甚至部分超过Oracle性能。