cs.CL（2025-06-28）

📊 共 11 篇论文 | 🔗 2 篇有代码

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支柱九：具身大模型 (Embodied Foundation Models) (9 🔗2) 支柱二：RL算法与架构 (RL & Architecture) (2)

🔬 支柱九：具身大模型 (Embodied Foundation Models) (9 篇)

#	题目	一句话要点	标签	🔗	⭐
1	Agent-to-Agent Theory of Mind: Testing Interlocutor Awareness among Large Language Models	提出Agent间心智理论评估框架，研究LLM对话者感知能力及其对多智能体协作的影响。	large language model	✅
2	DICE-BENCH: Evaluating the Tool-Use Capabilities of Large Language Models in Multi-Round, Multi-Party Dialogues	DICE-BENCH：评估大语言模型在多轮多方对话中工具使用能力的基准	large language model	✅
3	The Application of Large Language Models on Major Depressive Disorder Support Based on African Natural Products	结合非洲天然产物与大语言模型，为重度抑郁症提供支持系统。	large language model
4	Selecting and Merging: Towards Adaptable and Scalable Named Entity Recognition with Large Language Models	提出SaM框架，通过动态选择和合并专家模型，提升大语言模型在命名实体识别任务中的适应性和可扩展性。	large language model
5	ContextCache: Context-Aware Semantic Cache for Multi-Turn Queries in Large Language Models	ContextCache：一种用于大语言模型多轮查询的上下文感知语义缓存系统	large language model
6	The Translation Barrier Hypothesis: Multilingual Generation with Large Language Models Suffers from Implicit Translation Failure	提出翻译障碍假说以解决多语言生成质量低下问题	large language model
7	Evaluating AI Counseling in Japanese: Counselor, Client, and Evaluator Roles Assessed by Motivational Interviewing Criteria	评估日语AI咨询：基于动机式访谈标准评估咨询师、来访者和评估者角色	large language model
8	Text Production and Comprehension by Human and Artificial Intelligence: Interdisciplinary Workshop Report	跨学科研讨会揭示AI语言模型在文本理解与生成中与人类认知过程的关联与局限。	large language model
9	Knowledge Augmented Finetuning Matters in both RAG and Agent Based Dialog Systems	提出知识增强微调（KAFT）方法，提升RAG和Agent对话系统在知识密集型场景下的性能。	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	🔗	⭐
10	Teaching Models to Verbalize Reward Hacking in Chain-of-Thought Reasoning	提出VFT方法，提升语言模型在思维链推理中奖励欺骗行为的可检测性。	reinforcement learning chain-of-thought
11	RADIANT: Retrieval AugmenteD entIty-context AligNmenT -- Introducing RAG-ability and Entity-Context Divergence	RADIANT：提出检索增强实体上下文对齐框架，提升大语言模型RAG能力。	DPO direct preference optimization large language model

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