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Published on Aug 21 · Submitted by Leon on Aug 25 · TaoLive AIGC Abstract TLive-Omni is an omni-modal model for live-commerce that unifies image, video, audio, and text via timestamped token grouping, staged supervised training, and reinforcement fine-tuning with verifiable feedback to enable accurate real-time understanding.
E-commerce live streaming requires omni-modal understanding of noisy, temporally extended streams, where product facts are distributed across speech, video frames, product images, overlaid text, and user queries. We present TLive-Omni, an omni-modal understanding model tailored to live-commerce scenarios. It maps image, video, audio, and text inputs into a unified representation space.
Abstract While the impact of non-antibiotic drugs on gut bacteria is well-known, their mechanisms of action remain poorly characterized, and effective mitigation strategies for drug-induced dysbiosis are still limited. Here, we screened bacteria-derived drug-target protein homologs (BDTPHs) mapped to 63 target proteins and 107 associated drugs to quantify “drug–BDTPH–bacterium” interactions.
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