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RLHF: A comprehensive Survey for Cultural, Multimodal and Low Latency Alignment Methods
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Meta-Learning Objectives for Preference Optimization
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DeAL: Decoding-time Alignment for Large Language Models
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Reward Model Routing in Alignment
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Clean First, Align Later: Benchmarking Preference Data Cleaning for Reliable LLM Alignment
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Targeting Alignment: Extracting Safety Classifiers of Aligned LLMs
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Beyond Ordinal Preferences: Why Alignment Needs Cardinal Human Feedback
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PROPS: Progressively Private Self-alignment of Large Language Models
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2025-08-12T04:39:01.000000Z
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Alignment and Safety in Large Language Models: Safety Mechanisms, Training Paradigms, and Emerging Challenges
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Inverse Reinforcement Learning Meets Large Language Model Post-Training: Basics, Advances, and Opportunities
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Crome: Google DeepMind’s Causal Framework for Robust Reward Modeling in LLM Alignment
MarkTechPost@AI
2025-07-04T01:20:46.000000Z
I replicated the Anthropic alignment faking experiment on other models, and they didn't fake alignment
少点错误
2025-05-30T20:12:30.000000Z