cs.LG（2024-04-04）

📊 共 13 篇论文 | 🔗 1 篇有代码

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支柱二：RL算法与架构 (RL & Architecture) (9) 支柱九：具身大模型 (Embodied Foundation Models) (3 🔗1) 支柱一：机器人控制 (Robot Control) (1)

🔬 支柱二：RL算法与架构 (RL & Architecture) (9 篇)

#题目一句话要点标签🔗⭐
1 GP-MoLFormer: A Foundation Model For Molecular Generation 提出GP-MoLFormer以解决分子生成任务的挑战 linear attention foundation model
2 Direct Nash Optimization: Teaching Language Models to Self-Improve with General Preferences 提出直接纳什优化以解决语言模型自我改进问题 reinforcement learning RLHF contrastive learning
3 On the Surprising Efficacy of Distillation as an Alternative to Pre-Training Small Models 提出蒸馏方法以替代小模型的预训练过程 contrastive learning distillation
4 Investigating Regularization of Self-Play Language Models 提出KL正则化与虚拟博弈以解决自我博弈语言模型不稳定问题 reinforcement learning RLHF DPO
5 Exploration is Harder than Prediction: Cryptographically Separating Reinforcement Learning from Supervised Learning 提出区分强化学习与监督学习的加密方法 reinforcement learning
6 DIDA: Denoised Imitation Learning based on Domain Adaptation 提出DIDA以解决低质量演示数据中的模仿学习问题 imitation learning
7 REACT: Revealing Evolutionary Action Consequence Trajectories for Interpretable Reinforcement Learning 提出REACT以增强强化学习模型的可解释性 reinforcement learning
8 Knowledge Distillation-Based Model Extraction Attack using GAN-based Private Counterfactual Explanations 基于知识蒸馏的模型提取攻击方法解决隐私泄露问题 distillation
9 Laser Learning Environment: A new environment for coordination-critical multi-agent tasks 提出激光学习环境以解决多智能体协调任务中的瓶颈问题 reinforcement learning distillation

🔬 支柱九：具身大模型 (Embodied Foundation Models) (3 篇)

#题目一句话要点标签🔗⭐
10 Analyzing heterogeneity in Alzheimer Disease using multimodal normative modeling on imaging-based ATN biomarkers 提出多模态规范建模以分析阿尔茨海默病的异质性 multimodal
11 HiMAL: A Multimodal Hierarchical Multi-task Auxiliary Learning framework for predicting and explaining Alzheimer disease progression 提出HiMAL框架以预测和解释阿尔茨海默病进展 multimodal
12 Red Teaming GPT-4V: Are GPT-4V Safe Against Uni/Multi-Modal Jailbreak Attacks? 构建全面评估数据集以提升GPT-4V对多模态攻击的安全性 large language model multimodal ✅

🔬 支柱一：机器人控制 (Robot Control) (1 篇)

#题目一句话要点标签🔗⭐
13 Distributionally Robust Reinforcement Learning with Interactive Data Collection: Fundamental Hardness and Near-Optimal Algorithm 提出分布鲁棒强化学习以解决模拟与现实环境差距问题 sim-to-real reinforcement learning

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