Posts
All the articles I've posted.
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Beyond 'Aha!': Toward Systematic Meta-Abilities Alignment in Large Reasoning Models
Published: at 11:02 AM
86.87 🤔This paper introduces a systematic approach to enhance large reasoning models by aligning them with deduction, induction, and abduction meta-abilities through a three-stage pipeline of individual training, parameter merging, and domain-specific RL, achieving up to 4% performance gains over instruction-tuned baselines across math, coding, and science benchmarks.
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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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Boltzmann Classifier: A Thermodynamic-Inspired Approach to Supervised Learning
Published: at 11:08 AM 86.86 🤔The Boltzmann Classifier introduces a thermodynamically inspired supervised learning approach that uses an energy-based model derived from the Boltzmann distribution to estimate class probabilities, achieving competitive accuracy on benchmark datasets while offering interpretability and computational efficiency.
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How Well Can a Long Sequence Model Model Long Sequences? Comparing Architechtural Inductive Biases on Long-Context Abilities
Published: at 11:24 AM 86.84 🤔本文通过对比实验揭示，尽管长序列模型（如Mamba2）理论上支持无限长上下文，但在实际长上下文任务中与Transformer模型一样面临显著局限，尤其在信息位置和数据格式变化时表现不佳，亟需进一步研究其原因。
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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。