Progress in Multimodal Large Language Models: Background, Architecture, Evolution, Team Work, and Future Outlook

This article reviews recent advances in multimodal large language models, covering their background, architectural components, training strategies, application scenarios, evaluation benchmarks, team research on hallucination mitigation and long‑video understanding, and outlines promising future research directions.

Model architectureMultimodal LLMevaluation benchmarks

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Progress in Multimodal Large Language Models: Background, Architecture, Evolution, Team Work, and Future Outlook

DataFunTalk

May 15, 2022 · Artificial Intelligence

Search Term Recommendation: Scenarios, Algorithm Design, Challenges and Future Directions

This article presents an in‑depth overview of search term recommendation in QQ Browser, covering the various recommendation scenarios, the composition of recommendation items, the multi‑stage algorithm architecture, key technical challenges, evaluation metrics, and future research directions such as multi‑task and session‑aware modeling.

future researchmachine learningmulti-task learning

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