cs.LG（2025-09-07）
📊 共 14 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) (7 🔗1)
支柱二：RL算法与架构 (RL & Architecture) (6)
支柱八：物理动画 (Physics-based Animation) (1)
🔬 支柱九：具身大模型 (Embodied Foundation Models) (7 篇)
| # | 题目 | 一句话要点 | 标签 | 🔗 | ⭐ |
|---|---|---|---|---|---|
| 1 | MCIGLE: Multimodal Exemplar-Free Class-Incremental Graph Learning | 提出MCIGLE框架，解决多模态图结构数据上的无样本类增量学习难题。 | multimodal | ||
| 2 | Profiling LoRA/QLoRA Fine-Tuning Efficiency on Consumer GPUs: An RTX 4060 Case Study | 研究RTX 4060上LoRA/QLoRA微调LLM效率，提供资源受限场景下的实用指南。 | large language model foundation model | ||
| 3 | Exploring Urban Factors with Autoencoders: Relationship Between Static and Dynamic Features | 利用自编码器探索城市因素：静态与动态特征的关系分析 | multimodal | ||
| 4 | Unified Interaction Foundational Model (UIFM) for Predicting Complex User and System Behavior | 提出统一交互基础模型UIFM，用于预测复杂用户和系统行为 | foundation model | ||
| 5 | Code2MCP: Transforming Code Repositories into MCP Services | Code2MCP：将代码仓库转化为模型上下文协议(MCP)服务，促进工具集成。 | large language model | ✅ | |
| 6 | ALPHA: LLM-Enabled Active Learning for Human-Free Network Anomaly Detection | ALPHA：基于LLM的无人值守主动学习网络异常检测方法 | large language model | ||
| 7 | X-SQL: Expert Schema Linking and Understanding of Text-to-SQL with Multi-LLMs | 提出X-SQL框架，通过增强模式链接和理解，显著提升Text-to-SQL任务的性能。 | large language model |
🔬 支柱二：RL算法与架构 (RL & Architecture) (6 篇)
| # | 题目 | 一句话要点 | 标签 | 🔗 | ⭐ |
|---|---|---|---|---|---|
| 8 | An efficient deep reinforcement learning environment for flexible job-shop scheduling | 针对柔性作业车间调度，提出一种高效的深度强化学习环境。 | reinforcement learning deep reinforcement learning DRL | ||
| 9 | Reasoning Language Model for Personalized Lung Cancer Screening | 提出推理语言模型，融合影像与病历，实现个性化肺癌筛查风险评估 | reinforcement learning distillation chain-of-thought | ||
| 10 | Learning to Construct Knowledge through Sparse Reference Selection with Reinforcement Learning | 提出基于强化学习的稀疏引用选择方法，用于知识构建 | reinforcement learning deep reinforcement learning | ||
| 11 | Toward a Metrology for Artificial Intelligence: Hidden-Rule Environments and Reinforcement Learning | 提出基于Transformer的A2C算法，解决隐藏规则环境下的强化学习问题 | reinforcement learning | ||
| 12 | Using Reinforcement Learning to Optimize the Global and Local Crossing Number | 提出基于强化学习的图绘制方法，优化全局和局部交叉数 | reinforcement learning | ||
| 13 | PolicyEvolve: Evolving Programmatic Policies by LLMs for multi-player games via Population-Based Training | PolicyEvolve：利用LLM进化程序化策略，通过群体训练解决多人游戏问题 | reinforcement learning large language model |
🔬 支柱八：物理动画 (Physics-based Animation) (1 篇)
| # | 题目 | 一句话要点 | 标签 | 🔗 | ⭐ |
|---|---|---|---|---|---|
| 14 | Repeating vs. Non-Repeating FRBs: A Deep Learning Approach To Morphological Characterization | 利用深度学习对快速射电暴形态进行分类，区分重复和非重复FRB | PULSE |