Unverified50% confidenceSolutionExact time
An offline pretraining + online fine-tuning paradigm can be adopted where the policy network is first pretrained with behavioral cloning and then fine-tuned with SAC, provided that the BC data must be clean.
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50%
Confidence
Long-term
Relevance
8/17/2026
First Seen
Sources
机械手抓取任务失败？强化学习新手常见陷阱与解决方案
Related Claims
Partially VerifiedA pre-trained model refers to a model that has been trained in advance on large-scale datasets, which users can directly fine-tune or call to complete specific tasks.73% similarUnverifiedSelf-supervised learning is the core paradigm of the pre-training phase, where the model constructs training signals from the data itself through a next-token prediction task.71% similarUnverifiedOff-policy algorithms (such as SAC and DQN) can be trained on data collected by any policy, are capable of maintaining a replay buffer of millions of experiences for repeated learning, and have higher sample efficiency than on-policy methods.70% similarUnverifiedThe training recipes published by SWE-bench cover key aspects including data preparation, model selection, fine-tuning strategies, and inference frameworks.70% similar
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