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Megh Thakkar
megh1211
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Language Models' Factuality Depends on the Language of Inquiry
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GitChameleon: Unmasking the Version-Switching Capabilities of Code Generation Models
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π’ Exciting News! Our latest paper "ChartGemma" is out! π π§΅1/3: ChartGemma overcomes existing chart models key limitations that rely too much on data tables. Instead, it is trained on data generated directly from chart images, capturing crucial visual trendsπΈπ π§΅2/3: ChartGemma builds upon PaliGemma from Google Research and is fine-tuned on a high-quality visual instruction tuning dataset generated from Gemini Flash 1.5. ππ π§΅3/3: Achieves state-of-the-art results in chart summarization, question answering, and fact-checking tasks. π π It can also generate more accurate and realistic chart summaries. ππ Our model and data are publicly available. We also have a cool web demo. Check it out! π Demo: https://huggingface.co/spaces/ahmed-masry/ChartGemma Code: https://github.com/vis-nlp/ChartGemma Paper: https://huggingface.co/papers/2407.04172
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ChartGemma
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Generate insights from charts using text prompts