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Struct-Searcher achieves a remarkable 17.2% accuracy boost in multimodal information seeking by effectively managing conflicting evidence through a dynamic structural graph.
Forget monolithic models: a lightweight RL policy can dynamically orchestrate ensembles of frozen experts to outperform GPT-5 and Gemini-2.5-Pro on multimodal tasks, even generalizing to unseen models and skills.
Forget static emotion labels – EmoTransCap lets you generate speech captions that actually track how emotions evolve in a conversation.
Emotion-LLaMAv2 leaps beyond its predecessor by ditching face detectors and embracing a unified architecture that actually understands emotion, thanks to a novel pre-fusion module and curriculum tuning.
