Yizheng Zhao

Retrieval-Augmented Generation (RAG) has become the backbone of knowledge-intensive multi-hop question answering, yet routing every sub-query through a frontier model turns every hop into a cost multiplier and makes real-world deployment prohibitively expensive. Existing remedies either fix the r...

Recent theory suggests Transformers are inherently succinct, capable of representing recursive algorithms like binary counting over exponential state spaces using constant-size circuits, unlike the exponential bottleneck of RNNs. However, it remains unclear under what conditions gradient-trained...

Current neural biomedical entity linking (BioEL) models treat ontologies as flat dictionaries, ignoring the rich terminological knowledge (TBox) that defines concept boundaries. Consequently, they struggle with contextual ambiguity, often retrieving logically inconsistent candidates based solely...