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Found 6 papers, 6 papers with code
Linear Alignment of Vision-language Models for Image Captioning
We propose a more efficient training protocol that fits a linear mapping between image and text embeddings of CLIP via a closed-form solution.
Learning to Modulate pre-trained Models in RL
That is, the performance on the pre-training tasks deteriorates when fine-tuning on new tasks.
Semantic HELM: A Human-Readable Memory for Reinforcement Learning
Then we feed these tokens to a pretrained language model that serves the agent as memory and provides it with a coherent and human-readable representation of the past.
Reactive Exploration to Cope with Non-Stationarity in Lifelong Reinforcement Learning
Therefore, exploration strategies and learning methods are required that are capable of tracking the steady domain shifts, and adapting to them.
History Compression via Language Models in Reinforcement Learning
We propose to utilize a frozen Pretrained Language Transformer (PLT) for history representation and compression to improve sample efficiency.
WECHSEL: Effective initialization of subword embeddings for cross-lingual transfer of monolingual language models
Our method makes training large language models for new languages more accessible and less damaging to the environment.
