Tag: Long Context
All the articles with the tag "Long Context".
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LongReD: Mitigating Short-Text Degradation of Long-Context Large Language Models via Restoration Distillation
本文提出LongReD方法,通过长文本训练、短文本蒸馏和短到长蒸馏的多目标训练策略,有效缓解了长上下文大语言模型在短文本任务上的性能下降,同时保持或提升长文本处理能力。
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Why do LLMs attend to the first token?
This paper argues that attention sinks in LLMs, particularly at the first token, are a useful mechanism to prevent over-mixing of information in deep Transformers, supported by theoretical insights and empirical evidence from Gemma 7B, LLaMa 3.1 models, and pre-training experiments showing stronger sinks with larger models and longer contexts.
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M+: Extending MemoryLLM with Scalable Long-Term Memory
M+通过引入长期记忆机制和协同训练的检索器,显著扩展了MemoryLLM的知识保留能力至超过160k token,并在长上下文任务中优于基线,同时保持较低GPU内存消耗。
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LIFEBench: Evaluating Length Instruction Following in Large Language Models
本文通过引入LIFEBENCH基准,系统评估了26个大型语言模型在长度指令遵循上的能力,发现其在长长度约束下普遍表现不佳,且远未达到厂商宣称的最大输出长度,揭示了模型在长度感知和长文本生成上的根本局限性。
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Skywork Open Reasoner 1 Technical Report
Skywork-OR1通过提出MAGIC框架,利用多阶段训练和自适应熵控制的强化学习方法,显著提升了长链式推理模型在数学和编码任务上的性能,并在AIME24和AIME25基准上超越了DeepSeek-R1和Qwen3-32B。