Tag: Efficiency
All the articles with the tag "Efficiency".
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Intra-Layer Recurrence in Transformers for Language Modeling
本文提出Intra-Layer Recurrence (ILR)方法,通过在Transformer单次前向传播中选择性循环特定层(尤其是早期层),在不增加参数量的情况下改善语言建模困惑度,但计算成本增加和大规模模型验证不足限制了其实用性。
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RWKVQuant: Quantizing the RWKV Family with Proxy Guided Hybrid of Scalar and Vector Quantization
RWKVQuant introduces a tailored Post Training Quantization framework for RWKV models, using a coarse-to-fine proxy to hybridize scalar and vector quantization and optimizing codebooks for element-wise operations, achieving ~3-bit quantization with minimal accuracy loss and significant memory and speed improvements.
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Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing
本文提出Mixture of Sparse Attention (MoSA)方法,通过专家选择路由实现基于内容的稀疏注意力,显著提高了Transformer模型在相同计算预算下的语言建模性能,并优化了资源使用。
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Training Plug-n-Play Knowledge Modules with Deep Context Distillation
本文提出使用深度上下文蒸馏训练可插拔知识模块的方法,能够在低数据场景下高效整合文档知识,并通过实验证明其在问答任务中优于传统方法且与 RAG 具有协同效应。
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SIMPLEMIX: Frustratingly Simple Mixing of Off- and On-policy Data in Language Model Preference Learning
This paper introduces SIMPLEMIX, a simple method to mix on- and off-policy data in language model preference optimization, demonstrating that their complementary strengths—on-policy for reasoning tasks and off-policy for open-ended tasks—lead to a 6.03% average improvement over single-source methods on Alpaca Eval 2.0.