EPO: Entropy-regularized Policy Optimization for LLM Agents Reinforcement Learning
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2509.22576
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135
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AgentBench: Evaluating LLMs as Agents
Paper • 2308.03688 • Published • 25 -
DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter
Paper • 1910.01108 • Published • 21 -
Direct Preference Optimization: Your Language Model is Secretly a Reward Model
Paper • 2305.18290 • Published • 64 -
AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration
Paper • 2306.00978 • Published • 11 -
GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers
Paper • 2210.17323 • Published • 10 -
TPO: Aligning Large Language Models with Multi-branch & Multi-step Preference Trees
Paper • 2410.12854 • Published • 1 -
KTO: Model Alignment as Prospect Theoretic Optimization
Paper • 2402.01306 • Published • 21 -
Training language models to follow instructions with human feedback
Paper • 2203.02155 • Published • 24