cs.CL(2025-07-13)

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支柱九:具身大模型 (Embodied Foundation Models) (4 🔗1) 支柱二:RL算法与架构 (RL & Architecture) (2 🔗1)

🔬 支柱九:具身大模型 (Embodied Foundation Models) (4 篇)

#题目一句话要点标签🔗
1 Large Language Models Encode Semantics in Low-Dimensional Linear Subspaces 发现大语言模型在低维线性子空间中编码语义信息,并提出基于此的防御机制。 large language model
2 Towards Agentic RAG with Deep Reasoning: A Survey of RAG-Reasoning Systems in LLMs 综述Agentic RAG:深度推理增强LLM的检索增强生成系统 large language model multimodal
3 How Important is `Perfect' English for Machine Translation Prompts? 研究用户提示中的错误对LLM机器翻译性能的影响 large language model instruction following
4 MCEval: A Dynamic Framework for Fair Multilingual Cultural Evaluation of LLMs MCEval:用于评估LLM多语言文化公平性的动态框架 large language model

🔬 支柱二:RL算法与架构 (RL & Architecture) (2 篇)

#题目一句话要点标签🔗
5 ViSP: A PPO-Driven Framework for Sarcasm Generation with Contrastive Learning 提出ViSP框架,结合PPO和对比学习,用于生成高质量多模态讽刺文本。 PPO contrastive learning large language model
6 Your Pretrained Model Tells the Difficulty Itself: A Self-Adaptive Curriculum Learning Paradigm for Natural Language Understanding 提出基于预训练模型自适应难度评估的课程学习方法,提升NLU任务性能。 curriculum learning

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