Summary of Improving Visual Commonsense in Language Models Via Multiple Image Generation, by Guy Yariv et al.
Improving Visual Commonsense in Language Models via Multiple Image Generation
by Guy Yariv, Idan Schwartz, Yossi Adi, Sagie Benaim
First submitted to arxiv on: 19 Jun 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Computer Vision and Pattern Recognition (cs.CV); Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper introduces a method to enhance large language models’ (LLMs) visual commonsense reasoning by integrating robust visual understanding with foundational text-based language reasoning. The approach generates multiple images based on input text prompts and combines their prediction probabilities with the output of a pre-trained LLM conditioned on text only. This late-fusion layer enables predictions based on comprehensive image-text knowledge as well as text only when required. The method is evaluated using several visual commonsense reasoning tasks, traditional NLP tasks including common sense reasoning and reading comprehension, showing significant superiority over existing baselines. When applied to recent state-of-the-art LLMs like Llama3, improvements are observed in both visual common sense and traditional NLP benchmarks. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper helps computers better understand the world by combining what they see with what they read. Currently, language models only learn from text, which limits their ability to understand images. On the other hand, visual models excel at image-based tasks but struggle with non-visual tasks like common sense reasoning. This paper introduces a new method that combines both worlds by generating multiple images based on text prompts and using them to make decisions. The result is a better understanding of both text and images, leading to improved performance in various tasks. |
Keywords
* Artificial intelligence * Nlp
