cs.CL（2025-02-28）
📊 共 7 篇论文 | 🔗 1 篇有代码
🎯 兴趣领域导航
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)
支柱一：机器人控制 (Robot Control) (1)
🔬 支柱九：具身大模型 (Embodied Foundation Models) (4 篇)
| # | 题目 | 一句话要点 | 标签 | 🔗 | ⭐ |
|---|---|---|---|---|---|
| 1 | AgroLLM: Connecting Farmers and Agricultural Practices through Large Language Models for Enhanced Knowledge Transfer and Practical Application | AgroLLM：利用大型语言模型连接农民与农业实践，增强知识转移和应用 | large language model | ||
| 2 | Leveraging Large Language Models for Building Interpretable Rule-Based Data-to-Text Systems | 利用大型语言模型构建可解释的规则型数据到文本系统 | large language model | ||
| 3 | LexRAG: Benchmarking Retrieval-Augmented Generation in Multi-Turn Legal Consultation Conversation | 提出LexRAG：用于多轮法律咨询对话中检索增强生成的新基准。 | large language model | ✅ | |
| 4 | Rectifying Belief Space via Unlearning to Harness LLMs' Reasoning | 提出基于遗忘学习的信念空间修正方法，提升LLM推理可靠性 | 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 | Continuous Adversarial Text Representation Learning for Affective Recognition | 提出连续对抗文本表示学习框架，提升情感识别任务性能 | representation learning contrastive learning | ||
| 6 | Towards Anthropomorphic Conversational AI Part I: A Practical Framework | 提出多模块框架，增强大型语言模型在对话AI中的拟人化表现 | reinforcement 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 | 🔗 | ⭐ |
|---|---|---|---|---|---|
| 7 | JAM: Controllable and Responsible Text Generation via Causal Reasoning and Latent Vector Manipulation | 提出JAM框架，通过因果推理和隐向量操控实现可控且负责任的文本生成。 | manipulation large language model |