3 accepted papers
Mental health is increasingly critical in contemporary healthcare, with psychotherapy demanding dynamic, context-sensitive interactions that traditional NLP methods struggle to capture. Large Language Models (LLMs) offer significant potential for addressing this gap due to their ability to handle ex…
Real-world graph data environments intrinsically exist noise (e.g., link and structure errors) that inevitably disturb the effectiveness of graph representation and downstream learning tasks. For homogeneous graphs, the latest works use original node features to synthesize a similarity graph that ca…
Reliable multi-image geological reasoning is essential for automating expert tasks in remote-sensing mineral exploration, yet remains challenging for multimodal large language models (MLLMs) due to the need for locating target areas, accurate cross-image referencing, and consistency over long reason