Posts
All the articles I've posted.
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Zebra-Llama: Towards Extremely Efficient Hybrid Models
Zebra-Llama通过结合状态空间模型和多头潜在注意力层,从预训练Transformer构建高效混合模型,显著降低KV缓存大小并提升推理吞吐量,同时保持或超越基线性能。
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The Mosaic Memory of Large Language Models
This paper introduces the concept of 'mosaic memory' in Large Language Models, demonstrating through experiments on canaries and real-world datasets like SlimPajama that LLMs memorize training data via fuzzy duplicates with partial overlaps, predominantly syntactically, challenging existing deduplication practices and raising concerns for privacy, model utility, and benchmark fairness.
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REFINE-AF: A Task-Agnostic Framework to Align Language Models via Self-Generated Instructions using Reinforcement Learning from Automated Feedback
本文提出REFINE-AF框架,利用小型开源语言模型和基于自动化反馈的强化学习生成任务无关指令数据集,相较基线在SUPER-NI数据集上显著提升了63-66%的任务表现,同时降低了成本和人工干预。
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Deep Learning for On-Street Parking Violation Prediction
This paper develops a Deep Learning model with a novel data smoothing technique to predict fine-grained on-street parking violation rates in Thessaloniki, Greece, using indirect features like weather and time, achieving improved accuracy (MAE of 0.146) over baseline methods.
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Knowledge Grafting of Large Language Models
GraftLLM提出了一种通过模块感知压缩生成SkillPack的方法,实现大型语言模型间高效跨能力转移、知识融合和无遗忘持续学习,并在多个基准测试中显著优于现有方法。