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Ningbo Institute of Digital Twin, Eastern Institute of Technology
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LLMs can achieve 93% precision in single-turn tool use, surpassing GPT, Gemini, and Claude, when trained on a unified dataset that standardizes tool interaction patterns and enforces cross-turn dependencies.
Instead of blindly imputing missing data, ProMMA first evaluates the importance of each modality, leading to state-of-the-art multimodal sentiment analysis even when data is incomplete.
Untangling the mess of "streaming LLMs," this paper delivers a clear taxonomy that distinguishes between streaming generation, streaming inputs, and interactive architectures.
