Summary of Align Anything: Training All-modality Models to Follow Instructions with Language Feedback, by Jiaming Ji et al.
Align Anything: Training All-Modality Models to Follow Instructions with Language Feedback
by Jiaming Ji, Jiayi Zhou, Hantao Lou, Boyuan Chen, Donghai Hong, Xuyao Wang, Wenqi Chen, Kaile Wang, Rui Pan, Jiahao Li, Mohan Wang, Josef Dai, Tianyi Qiu, Hua Xu, Dong Li, Weipeng Chen, Jun Song, Bo Zheng, Yaodong Yang
First submitted to arxiv on: 20 Dec 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computation and Language (cs.CL)
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Summary difficulty | Written by | Summary |
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High | Paper authors | High Difficulty Summary Read the original abstract here |
Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper proposes a novel approach to fine-tune large language models for instruction-following capabilities across multiple modalities, including text, image, audio, and video. The authors address the challenges of aligning all-modality models with human intentions by introducing the align-anything framework, which includes 200k meticulously annotated human preference data. They also develop an alignment method that learns from unified language feedback to capture complex modality-specific human preferences. To evaluate performance improvements, they construct a challenging all-modality capability evaluation framework called eval-anything. The authors make their data, models, and code frameworks open-source for the community. |
Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper helps us better understand how to teach computers to follow instructions correctly, no matter what type of information we give them. Imagine being able to ask your phone’s virtual assistant to do things like show you a picture or play a song, and it knows exactly what you mean! The researchers came up with a new way to make this happen by teaching computers how to understand different types of instructions, like text, images, audio, or videos. They even created special tools to help them test their idea and share it with others. |
Keywords
» Artificial intelligence » Alignment