26 citations · 67 across the 45 of their papers we have counts for
5 papers · 1 filter
Auto-ICL: In-Context Learning without Human Supervision
Jinghan Yang, Shuming Ma, Furu Wei
With in-context learning ability, the performance of large language models can be significantly boosted when provided with appropriate context. However, existing in-context learnin…
Tuna: Instruction Tuning using Feedback from Large Language Models
Haoran Li, Yiran Liu, Xingxing Zhang +2
Instruction tuning of open-source large language models (LLMs) like LLaMA, using direct outputs from more powerful LLMs such as Instruct-GPT and GPT-4, has proven to be a cost-effe…
Democratizing Reasoning Ability: Tailored Learning from Large Language Model
Zhaoyang Wang, Shaohan Huang, Yuxuan Liu +8
Large language models (LLMs) exhibit impressive emergent abilities in natural language processing, but their democratization is hindered due to huge computation requirements and cl…
BitNet: Scaling 1-bit Transformers for Large Language Models
Hongyu Wang, Shuming Ma, Li Dong +7
The increasing size of large language models has posed challenges for deployment and raised concerns about environmental impact due to high energy consumption. In this work, we int…
Kosmos-G: Generating Images in Context with Multimodal Large Language Models
Xichen Pan, Li Dong, Shaohan Huang +3
Recent advancements in subject-driven image generation have made significant strides. However, current methods still fall short in diverse application scenarios, as they require te…