3 papers
cs.AI2025
Solomonoff-Inspired Hypothesis Ranking with LLMs for Prediction Under Uncertainty
Josh Barber, Rourke Young, Cameron Coombe +1
Reasoning under uncertainty is a key challenge in AI, especially for real-world tasks, where problems with sparse data demands systematic generalisation. Existing approaches strugg…
cs.CV2025
Intra-Class Probabilistic Embeddings for Uncertainty Estimation in Vision-Language Models
Zhenxiang Lin, Maryam Haghighat, Will Browne +1
Vision-language models (VLMs), such as CLIP, have gained popularity for their strong open vocabulary classification performance, but they are prone to assigning high confidence sco…
cs.RO2025
Open-Vocabulary Part-Based Grasping
Tjeard van Oort, Dimity Miller, Will N. Browne +3
Many robotic tasks require grasping objects at specific object parts instead of arbitrarily, a crucial capability for interactions beyond simple pick-and-place, such as human-robot…