具体来说,首先使用caption(或label)模型将VQA image翻译为captions(或labels list),如绿色框中VQA输入x是翻译后的captions(“Context: People are standing in a parking lot with some umbrellas as it snows.”)和问题字符串(“Q: What is the warmest temperature at which this weather can happen?”),A(...
Implementation of CVPR 2023 paper "Prompting Large Language Models with Answer Heuristics for Knowledge-based Visual Question Answering". - MILVLG/prophet
A: Michael started with 58 golf balls. After losing 23 on tuesday, he had 58 - 23 = 35. After losing 2 more, he had 35 - 2 = 33 golf balls. The answer is 33. Q: Olivia has $23. She bought five bagels for $3 each. How much money does she have left? A: Olivia had 23 ...
Chain-of-Thought (CoT) prompting can enhance the reasoning capabilities of large language models (LLMs), establishing itself as a primary approach to solving complex reasoning tasks. Existing CoT synthesis approaches usually focus on simpler reasoning tasks and thus result in low-quality and inconsist...
Recently, Large Language Models (LLMs) have demonstrated their applicability in the field of process mining [29]. In particular, LLMs can translate statements expressing information needs in natural language into queries on event logs and engage in question-answer conversations with analysts [3,11]...
25 of the best large language models in 2025 When people are confronted with a challenging problem, they often break it down into smaller, more manageable pieces. For example, solving a complex math equation typically involves several substeps, each of which is essential to arriving at the final...
By leveraging the chain of thought prompting, you can remarkably enhance the interpretability of the LLM output. Moreover, the large language model becomes transparent by mentioning the step-by-step reasoning behind every answer. This even allows the users to become familiar with how the conclusions...
In-context prompting in large language models (LLMs) has become a prevalent approach to improve zero-shot capabilities, but this idea is less explored in the vision domain. Existing visual prompting methods focus on referring segmentation to segment the most relevant object, falling short of addres...
Image created by author with Midjourney Introducing Chain-of-Thought Prompting Large Language Models (LLMs) have revolutionized the field of artificial intelligence, offering unprecedented capabilities in natural language understanding and generation. However, their ability to perform complex reasoning tasks ...
Large language models (LLMs) have transformed natural language processing (NLP) by demonstrating the effectiveness of increasing the number of parameters and training data for various reasoning tasks. One successful method, chain-of-thought (CoT) prom...