5 accepted papers
Recent advances have enabled Large Language Models (LLMs) to tackle reasoning tasks by generating chain-of-thought (CoT) rationales, yet these gains have largely applied to high-resource languages, leaving low-resource languages underperformed. In this work, we first investigate CoT techniques in ex
Artificial intelligence offers powerful methods for audio processing and analysis. Still, complex workflows and the required programming skills often limit access for students and domain experts, such as marine bioacousticians and soundscape ecologists. We present "AI EcoSound Tutor", a code-free an
As Large Language Model (LLM) agents scale toward real-world deployment, they generate large volumes of fragmented, non-standardized execution traces. Many existing observability platforms treat these traces primarily as passive logging artifacts, lacking the unified infrastructure to operationalize
Cross-lingual chain-of-thought prompting techniques have proven effective for investigating diverse reasoning paths in Large Language Models (LLMs), especially for low-resource languages. Despite these empirical gains, the mechanisms underlying cross-lingual improvements remain perplexing. This stud
With the recent advances in graph neural networks, there is a rising number of studies on graph-based multi-label classification with the consideration of object dependencies within visual data. Nevertheless, graph representations can become indistinguishable due to the complex nature of label relat…