Vision-language models (VLMs) can reason about visual planning tasks, but querying them for every instance incurs repeated inference cost and latency. Generating reusable planning programs offers an alternative, but constructing reliable planning systems for new problem domains without extensive supervision remains cha...
Rui-Xiao Yang, Yi-Lun Hao, Ming-Xin Yu et al.· 0 citations
Large language models are increasingly applied to tasks grounded in long, heterogeneous information sources. Conventional Retrieval-Augmented Generation (RAG) relies on fixed similarity-based retrieval, while agentic variants adapt queries and tool use but remain largely retrieval-centric. However, in many tasks, the e...
Yi-Lun Hao, Krishna Sayana, Isabella Ye et al.· 0 citations
Artificial superintelligence (ASI) requires AI to move beyond mastering existing knowledge toward exploring the unknown, creating new knowledge, and turning new ideas into verifiable results. However, the capabilities of today's AI systems are still largely built on learning, compressing, and applying existing human kn...
Jun-Wei Zhou, Zhen Sun, Binyu Li et al.· 2 citations
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