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The paper evaluates the performance of Google's Gemini, a Multimodal Large Language Model (MLLM), in complex reasoning tasks that require the integration of commonsense knowledge across modalities. The study finds that Gemini demonstrates competitive commonsense reasoning capabilities compared to other models.
https://arxiv.org/abs//2312.17661
YouTube: https://www.youtube.com/@ArxivPapers
TikTok: https://www.tiktok.com/@arxiv_papers
Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016
Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers
By Igor Melnyk5
33 ratings
The paper evaluates the performance of Google's Gemini, a Multimodal Large Language Model (MLLM), in complex reasoning tasks that require the integration of commonsense knowledge across modalities. The study finds that Gemini demonstrates competitive commonsense reasoning capabilities compared to other models.
https://arxiv.org/abs//2312.17661
YouTube: https://www.youtube.com/@ArxivPapers
TikTok: https://www.tiktok.com/@arxiv_papers
Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016
Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers

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