Ping Nie
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The paper proposes a vision-first formulation to improve cache reuse efficiency and reranking performance in multimodal large language models.
This paper proposes CompRank, a token-efficient reranking framework for large language models that reduces redundant computation and achieves strong reranking performance.
The paper constructs datasets and benchmarks to evaluate the performance of visual generators in handling open-ended requests, and proposes a teach-then-search co-training framework to improve their world-knowledge.
Papers
Search Beyond What Can Be Taught: Evolving the Knowledge Boundary in Agentic Visual Generation
Haozhe Wang, Weijia Feng, Jinpeng Yu, Che Liu +7 more
The paper constructs datasets and benchmarks to evaluate the performance of visual generators in handling open-ended requests, and proposes a teach-then-search co-training framework to improve their w…