10 Oct 2025
Researchers systematically analyzed visual layer selection in Multimodal Large Language Models (MLLMs), demonstrating that integrating features from shallow, middle, and deep Vision Transformer layers via a simple concatenation fusion outperforms conventional deep-layer reliance and more complex fusion strategies.
04 Sep 2025
The MULTICONIR benchmark was developed to systematically evaluate information retrieval and reranking models on multi-condition natural language queries, revealing that current state-of-the-art models suffer significant performance degradation and lack robust relevance monotonicity and format invariance. Advanced general-purpose LLMs, such as GPT-4o, demonstrated superior capabilities in these complex retrieval scenarios.
10 Apr 2025
A data-efficient framework for Thai text-to-speech synthesis combines phoneme-tone adaptive modeling with specialized preprocessing pipelines to handle complex linguistic features, achieving high-fidelity speech synthesis and zero-shot voice cloning while requiring significantly less training data than traditional approaches.
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