Unverified50% confidenceFactExact time
The OmniGround team built a 580K-sample training dataset by reconstructing temporal question answering from dense audio-visual annotations and organizing general omni-modal instruction data.
1
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50%
Confidence
Medium-term (~90 days)
Relevance
10/20/2026
First Seen
Valid until: 1/18/2027
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UnverifiedOmniGround is a general omni-modal model trained on TACG and the 580K dataset, with stronger temporal grounding capability.72% similarUnverifiedThe training incorporated behavioral metrics such as merge rate, code review time, and repository size, ultimately generating more than 1 million step-to-step state transition data entries.72% similarUnverifiedThe training dataset contains 4096 numerical Richards equation trajectories, split into training, validation, and evaluation sets in a 2867/614/615 ratio.69% similarUnverified智谱GLM-5.3基于743B（7430亿参数）基座进行后训练，主打编程与智能体两大核心场景69% similarUnverifiedThe original Whisper research described training on 680,000 hours of multilingual and multitask supervised data and reported strong zero-shot transfer across benchmarks.69% similar
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