cs.LG(2023-11-13)
📊 共 11 篇论文 | 🔗 1 篇有代码
🎯 兴趣领域导航
支柱二:RL算法与架构 (RL & Architecture) (6)
支柱九:具身大模型 (Embodied Foundation Models) (4 🔗1)
支柱三:空间感知与语义 (Perception & Semantics) (1)
🔬 支柱二:RL算法与架构 (RL & Architecture) (6 篇)
| # | 题目 | 一句话要点 | 标签 | 🔗 | ⭐ |
|---|---|---|---|---|---|
| 1 | Data-Efficient Task Generalization via Probabilistic Model-based Meta Reinforcement Learning | 提出PACOH-RL以解决数据稀缺下的任务泛化问题 | reinforcement learning model-based RL | ||
| 2 | An introduction to reinforcement learning for neuroscience | 介绍强化学习在神经科学中的应用与挑战 | reinforcement learning deep reinforcement learning | ||
| 3 | Explainable History Distillation by Marked Temporal Point Process | 提出可解释历史蒸馏方法以解决事件预测问题 | distillation | ||
| 4 | On Elastic Language Models | 提出弹性语言模型以解决请求流变化问题 | distillation large language model | ||
| 5 | Embarassingly Simple Dataset Distillation | 提出RaT-BPTT方法以优化数据集蒸馏过程 | distillation | ||
| 6 | Estimating optical vegetation indices and biophysical variables for temperate forests with Sentinel-1 SAR data using machine learning techniques: A case study for Czechia | 利用SAR数据和机器学习估算森林光学植被指数以解决光学数据局限性问题 | MAE penetration |
🔬 支柱九:具身大模型 (Embodied Foundation Models) (4 篇)
| # | 题目 | 一句话要点 | 标签 | 🔗 | ⭐ |
|---|---|---|---|---|---|
| 7 | On The Truthfulness of 'Surprisingly Likely' Responses of Large Language Models | 提出'惊人可能'响应以提升大语言模型的真实信息获取能力 | large language model | ||
| 8 | Explicit Foundation Model Optimization with Self-Attentive Feed-Forward Neural Units | 提出显式基础模型优化方法以降低神经网络计算成本 | foundation model | ||
| 9 | To Transformers and Beyond: Large Language Models for the Genome | 探讨大型语言模型在基因组学中的应用与挑战 | large language model | ||
| 10 | Can LLMs Patch Security Issues? | 提出反馈驱动安全修补方法以解决LLMs代码安全问题 | large language model | ✅ |
🔬 支柱三:空间感知与语义 (Perception & Semantics) (1 篇)
| # | 题目 | 一句话要点 | 标签 | 🔗 | ⭐ |
|---|---|---|---|---|---|
| 11 | Non-Contact Breathing Rate Detection Using Optical Flow | 提出非接触式呼吸频率检测方法以解决健康监测问题 | optical flow |