5 accepted papers
Psychology research has shown that humans are poor at estimating their performance on tasks, tending towards underconfidence on easy tasks and overconfidence on difficult tasks. We examine three LLMs, Llama-3-70B-instruct, Claude-3-Sonnet, and GPT-4o, on a range of QA tasks of varying difficulty, an…
Spurious correlations occur when models rely on non-essential features that coincidentally co-vary with target labels, leading to incorrect reasoning under distribution shift. We consider spurious correlations in multi-modal Large Vision Language Models (LVLMs) pretrained on extensive and diverse da…
The correct model response in the face of uncertainty is to abstain from answering a question so as not to mislead the user. In this work, we study the ability of LLMs to abstain from answering context-dependent science questions when provided insufficient or incorrect context. We probe model sensit…
Our paper aims to generate diverse and realistic animal motion sequences from textual descriptions without a large-scale animal text-motion dataset. While the task of text-driven human motion synthesis is already extensively studied and benchmarked it remains challenging to transfer this success to…
Learning multi-organ segmentation from multiple partially-labeled datasets attracts increasing attention. It can be a promising solution for the scarcity of large-scale, fully labeled 3D medical image segmentation datasets. However, existing algorithms of multi-organ segmentation on partially-labele…