3 accepted papers
Vision–Language Models (VLMs) are increasingly deployed with web search tools, yet we still lack benchmarks that isolate a critical capability for real-world use: deciding when to search and how to steer search from ambiguous visual evidence, especially when multiple images provide overlapping or co…
The rapid advancement of Multimodal Large Language Models (MLLMs) has revealed the limitations of existing benchmarks in evaluating complex reasoning over multiple images. To address this gap, we introduce MIRACLE, a novel benchmark for Multi-Image complex Reasoning And Comprehension Logic Evaluatio
Hence, developing a corpus for speech emotion recognition (SER) in the target domain is significant; however, this is time-consuming and cost-intensive. In this study, we aim to fully use a partially-labeled corpus in the target domain (target corpus) with the help of an existing fully-labeled corpu…