cs.LG(2023-11-14)
📊 共 12 篇论文 | 🔗 2 篇有代码
🎯 兴趣领域导航
支柱二:RL算法与架构 (RL & Architecture) (5 🔗1)
支柱九:具身大模型 (Embodied Foundation Models) (5 🔗1)
支柱八:物理动画 (Physics-based Animation) (2)
🔬 支柱二:RL算法与架构 (RL & Architecture) (5 篇)
| # | 题目 | 一句话要点 | 标签 | 🔗 | ⭐ |
|---|---|---|---|---|---|
| 1 | Leveraging Foundation Models to Improve Lightweight Clients in Federated Learning | 提出基础模型蒸馏以提升联邦学习中的轻量客户端性能 | distillation foundation model | ||
| 2 | Adversarial Imitation Learning On Aggregated Data | 提出对抗模仿学习方法以解决逆强化学习的局限性 | reinforcement learning imitation learning inverse reinforcement learning | ||
| 3 | On-Policy Policy Gradient Reinforcement Learning Without On-Policy Sampling | 提出PROPS以解决采样误差导致的低效强化学习问题 | reinforcement learning policy learning | ||
| 4 | Purpose in the Machine: Do Traffic Simulators Produce Distributionally Equivalent Outcomes for Reinforcement Learning Applications? | 揭示交通模拟器在强化学习中的局限性 | reinforcement learning | ||
| 5 | Offline Data Enhanced On-Policy Policy Gradient with Provable Guarantees | 提出一种新型混合强化学习算法以提升样本效率 | policy learning offline RL | ✅ |
🔬 支柱九:具身大模型 (Embodied Foundation Models) (5 篇)
| # | 题目 | 一句话要点 | 标签 | 🔗 | ⭐ |
|---|---|---|---|---|---|
| 6 | Finding Inductive Loop Invariants using Large Language Models | 利用大型语言模型寻找归纳循环不变式以解决程序验证问题 | large language model | ||
| 7 | Plum: Prompt Learning using Metaheuristic | 提出基于元启发式的提示学习方法以优化大语言模型 | large language model chain-of-thought | ✅ | |
| 8 | Towards Evaluating AI Systems for Moral Status Using Self-Reports | 提出自我报告方法以评估AI系统的道德状态 | large language model | ||
| 9 | DiLoCo: Distributed Low-Communication Training of Language Models | 提出DiLoCo以解决低通信环境下语言模型训练问题 | large language model | ||
| 10 | Language Models are Better Bug Detector Through Code-Pair Classification | 提出代码对分类任务以提升bug检测能力 | large language model |
🔬 支柱八:物理动画 (Physics-based Animation) (2 篇)
| # | 题目 | 一句话要点 | 标签 | 🔗 | ⭐ |
|---|---|---|---|---|---|
| 11 | Bayesian Conditional Diffusion Models for Versatile Spatiotemporal Turbulence Generation | 提出基于贝叶斯条件扩散模型的多功能时空湍流生成方法 | spatiotemporal | ||
| 12 | Mean-field variational inference with the TAP free energy: Geometric and statistical properties in linear models | 提出基于TAP自由能的均场变分推断以解决高维贝叶斯线性模型问题 | AMP |