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Chain of lora: Efficient fine-tuning of language models via residual learning
Fine-tuning is the primary methodology for tailoring pre-trained large language models to
specific tasks. As the model's scale and the diversity of tasks expand, parameter-efficient fine …
specific tasks. As the model's scale and the diversity of tasks expand, parameter-efficient fine …
How to configure good in-context sequence for visual question answering
Inspired by the success of Large Language Models in dealing with new tasks via In-Context
Learning (ICL) in NLP researchers have also developed Large Vision-Language Models …
Learning (ICL) in NLP researchers have also developed Large Vision-Language Models …
Lever LM: configuring in-context sequence to lever large vision language models
As Archimedes famously said,``Give me a lever long enough and a fulcrum on which to
place it, and I shall move the world'', in this study, we propose to use a tiny Language Model …
place it, and I shall move the world'', in this study, we propose to use a tiny Language Model …
Lifelong Event Detection with Embedding Space Separation and Compaction
To mitigate forgetting, existing lifelong event detection methods typically maintain a memory
module and replay the stored memory data during the learning of a new task. However, the …
module and replay the stored memory data during the learning of a new task. However, the …