4 papers
Clarify or Answer: Reinforcement Learning for Agentic VQA with Context Under-specification
Zongwan Cao, Bingbing Wen, Lucy Lu Wang
Real-world visual question answering (VQA) is often context-dependent: an image-question pair may be under-specified, such that the correct answer depends on external information t…
Do Language Models Mirror Human Confidence? Exploring Psychological Insights to Address Overconfidence in LLMs
Chenjun Xu, Bingbing Wen, Bin Han +3
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…
Escaping the SpuriVerse: Can Large Vision-Language Models Generalize Beyond Seen Spurious Correlations?
Yiwei Yang, Chung Peng Lee, Shangbin Feng +5
Finetuning can cause spurious correlations to arise between non-essential features and the target labels, but benchmarks to study these effects involve contrived settings and narro…
MMMG: a Comprehensive and Reliable Evaluation Suite for Multitask Multimodal Generation
Jihan Yao, Yushi Hu, Yujie Yi +9
Automatically evaluating multimodal generation presents a significant challenge, as automated metrics often struggle to align reliably with human evaluation, especially for complex…