10 citations · 22 across the 7 of their papers we have counts for
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cs.CL2023★ 5 cited
Tuning LayerNorm in Attention: Towards Efficient Multi-Modal LLM Finetuning
Bingchen Zhao, Haoqin Tu, Chen Wei +2
This paper introduces an efficient strategy to transform Large Language Models (LLMs) into Multi-Modal Large Language Models (MLLMs). By conceptualizing this transformation as a do…
cs.CL2023
ZeroGen: Zero-shot Multimodal Controllable Text Generation with Multiple Oracles
Haoqin Tu, Bowen Yang, Xianfeng Zhao
Automatically generating textual content with desired attributes is an ambitious task that people have pursued long. Existing works have made a series of progress in incorporating…
cs.CL2023
ReSee: Responding through Seeing Fine-grained Visual Knowledge in Open-domain Dialogue
Haoqin Tu, Yitong Li, Fei Mi +1
Incorporating visual knowledge into text-only dialogue systems has become a potential direction to imitate the way humans think, imagine, and communicate. However, existing multimo…