3 accepted papers
In-context learning (ICL) advances Large Language Models (LLMs) exhibiting emergent ability on downstream tasks without updating billions of parameters. However, in the area of multimodal Large Language Models (MLLMs), two problems hinder the application of multimodal ICL: (1) Most primary MLLMs are…
In-context learning (ICL) enhances the reasoning abilities of Large Language Models (LLMs) by prepending a few demonstrations. It motivates researchers to introduce more examples to provide additional contextual information for the generation. However, existing methods show a significant limitation…
Many text generation tasks are copy-oriented. For instance, nearly 30% content of news summaries is copied. The copy rate is even higher in Grammatical Error Correction (GEC). However, existing generative models generate texts through word-by-word decoding, which may lead to factual inconsistencies…