cs.CL(2025-05-04)

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支柱九:具身大模型 (Embodied Foundation Models) (12 🔗1) 支柱二:RL算法与架构 (RL & Architecture) (1)

🔬 支柱九:具身大模型 (Embodied Foundation Models) (12 篇)

#题目一句话要点标签🔗
1 LecEval: An Automated Metric for Multimodal Knowledge Acquisition in Multimedia Learning LecEval:一种用于多媒体学习中多模态知识获取的自动化评估指标 large language model multimodal
2 Analyzing Cognitive Differences Among Large Language Models through the Lens of Social Worldview 提出社会世界观分类法以分析大型语言模型的认知差异 large language model
3 Personalisation or Prejudice? Addressing Geographic Bias in Hate Speech Detection using Debias Tuning in Large Language Models 利用Debias Tuning解决大语言模型中基于地理位置的仇恨言论检测偏差问题 large language model
4 Adaptive Thinking via Mode Policy Optimization for Social Language Agents 提出AML框架,通过自适应模式策略优化提升社交语言Agent的推理能力。 chain-of-thought
5 QiMeng-Xpiler: Transcompiling Tensor Programs for Deep Learning Systems with a Neural-Symbolic Approach QiMeng-Xpiler:利用神经-符号方法转译张量程序,实现深度学习系统跨平台部署 large language model
6 LLM-OptiRA: LLM-Driven Optimization of Resource Allocation for Non-Convex Problems in Wireless Communications LLM-OptiRA:利用LLM优化无线通信中非凸资源分配问题 large language model
7 A New HOPE: Domain-agnostic Automatic Evaluation of Text Chunking 提出HOPE,一种领域无关的文本分块自动评估指标,提升RAG性能。 large language model
8 Decoding Open-Ended Information Seeking Goals from Eye Movements in Reading 首次提出仅从阅读时的眼动追踪数据解码开放式信息搜寻目标 multimodal
9 Probing Audio-Generation Capabilities of Text-Based Language Models 探索文本语言模型音频生成能力:一种基于代码中间层的三层递进方法 large language model
10 Measuring Hong Kong Massive Multi-Task Language Understanding 提出香港多任务语言理解基准HKMMLU,评估LLM在香港语言文化环境下的能力。 large language model
11 Identifying Legal Holdings with LLMs: A Systematic Study of Performance, Scale, and Memorization 利用大型语言模型识别法律判决要点:性能、规模与记忆的系统性研究 large language model
12 Incorporating Legal Structure in Retrieval-Augmented Generation: A Case Study on Copyright Fair Use 提出结合法律知识图谱的RAG方法,提升版权合理使用场景下的检索质量与推理可靠性 chain-of-thought

🔬 支柱二:RL算法与架构 (RL & Architecture) (1 篇)

#题目一句话要点标签🔗
13 Exploring the Potential of Offline RL for Reasoning in LLMs: A Preliminary Study 探索离线强化学习在提升大语言模型推理能力上的潜力 reinforcement learning offline RL DPO

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