Making AI smarter without more training data | UCR News
A study by UC Riverside researchers offers a practical solution to one of artificial intelligence’s toughest challenges by enabling AI systems to reason more like humans, without requiring new training data beyond testing questions. In a preprint paper entitled “Test-Time Matching: Unlocking Compositional Reasoning in Multimodal Models”, assistant professor Yinglun Zhu and students introduce a…