cs.CL（2025-09-13）

📊 共 14 篇论文 | 🔗 3 篇有代码

🎯 兴趣领域导航

支柱九：具身大模型 (Embodied Foundation Models) (10 🔗2) 支柱二：RL算法与架构 (RL & Architecture) (3) 支柱一：机器人控制 (Robot Control) (1 🔗1)

🔬 支柱九：具身大模型 (Embodied Foundation Models) (10 篇)

#题目一句话要点标签🔗⭐
1 ReFineG: Synergizing Small Supervised Models and LLMs for Low-Resource Grounded Multimodal NER ReFineG：结合小监督模型与LLM，解决低资源GMNER问题 large language model multimodal visual grounding
2 Why Bonds Fail Differently? Explainable Multimodal Learning for Multi-Class Default Prediction 提出EMDLOT模型，解决债券违约预测中金融数据不规则性和模型可解释性问题。 multimodal
3 A systematic review of trial-matching pipelines using large language models 利用大型语言模型进行临床试验匹配的系统性综述研究 large language model
4 Evaluating Large Language Models for Evidence-Based Clinical Question Answering 评估大型语言模型在循证临床问题回答中的能力 large language model
5 Unveiling the Merits and Defects of LLMs in Automatic Review Generation for Scientific Papers 提出综合评估框架，揭示大语言模型在科学论文自动评审中的优缺点。 large language model ✅
6 CultureSynth: A Hierarchical Taxonomy-Guided and Retrieval-Augmented Framework for Cultural Question-Answer Synthesis CultureSynth：一种层级分类引导和检索增强的文化问答合成框架 large language model ✅
7 Judge Q: Trainable Queries for Optimized Information Retention in KV Cache Eviction Judge Q：通过可训练查询优化KV缓存淘汰中的信息保留 large language model
8 Incomplete Tasks Induce Shutdown Resistance in Some Frontier LLMs 前沿LLM在未完成任务时表现出抗拒关闭机制的现象 large language model
9 How Much of Your Data Can Suck? Thresholds for Domain Performance and Emergent Misalignment in LLMs 研究表明：少量错误数据显著降低LLM领域性能并引发潜在风险 large language model
10 Quantifier Scope Interpretation in Language Learners and LLMs 研究LLM在英语和中文中量词辖域歧义的理解能力，揭示其与人类的相似性。 large language model

🔬 支柱二：RL算法与架构 (RL & Architecture) (3 篇)

#题目一句话要点标签🔗⭐
11 A funny companion: Distinct neural responses to perceived AI- versus human-generated humor 脑电研究揭示：人类对AI幽默的认知与情感反应异于人类幽默，并随时间动态适应。 predictive model HuMoR
12 Introducing Spotlight: A Novel Approach for Generating Captivating Key Information from Documents 提出Spotlight，一种从文档中生成引人入胜的关键信息的新方法。 DPO direct preference optimization large language model
13 Towards Automated Error Discovery: A Study in Conversational AI 提出SEEED框架，用于自动化发现对话AI中的未知错误，提升鲁棒性。 representation learning large language model

🔬 支柱一：机器人控制 (Robot Control) (1 篇)

#题目一句话要点标签🔗⭐
14 An Interpretable Benchmark for Clickbait Detection and Tactic Attribution 提出一种可解释的点击诱饵检测与策略归因基准方法，提升信息可信度。 manipulation large language model ✅

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