mDPO: Conditional Preference Optimization for Multimodal Large Language Models
Paper
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2406.11839
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Published
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36
Papers to Read
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Pandora: Towards General World Model with Natural Language Actions and Video States
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WPO: Enhancing RLHF with Weighted Preference Optimization
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Self-Improving Robust Preference Optimization
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MotionLLM: Understanding Human Behaviors from Human Motions and Videos
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Offline Regularised Reinforcement Learning for Large Language Models Alignment
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Value-Incentivized Preference Optimization: A Unified Approach to Online and Offline RLHF
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An Introduction to Vision-Language Modeling
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OpenRLHF: An Easy-to-use, Scalable and High-performance RLHF Framework
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Octo: An Open-Source Generalist Robot Policy
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TRANSIC: Sim-to-Real Policy Transfer by Learning from Online Correction
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RLHF Workflow: From Reward Modeling to Online RLHF
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Self-Play Preference Optimization for Language Model Alignment
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Iterative Reasoning Preference Optimization
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KAN: Kolmogorov-Arnold Networks
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A Multimodal Automated Interpretability Agent
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Learning H-Infinity Locomotion Control
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Reuse Your Rewards: Reward Model Transfer for Zero-Shot Cross-Lingual Alignment
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Scaling Instructable Agents Across Many Simulated Worlds
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Learn Your Reference Model for Real Good Alignment
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Direct Nash Optimization: Teaching Language Models to Self-Improve with General Preferences
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Robust Gaussian Splatting
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RL for Consistency Models: Faster Reward Guided Text-to-Image Generation
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