1 citations · 1 across the 4 of their papers we have counts for
4 papers
Broaden your SCOPE! Efficient Multi-turn Conversation Planning for LLMs with Semantic Space
Zhiliang Chen, Xinyuan Niu, Chuan-Sheng Foo +1
Large language models (LLMs) are used in chatbots or AI assistants to hold conversations with a human user. In such applications, the quality (e.g., user engagement, safety) of a c…
Waterfall: Framework for Robust and Scalable Text Watermarking and Provenance for LLMs
Gregory Kang Ruey Lau, Xinyuan Niu, Hieu Dao +3
Protecting intellectual property (IP) of text such as articles and code is increasingly important, especially as sophisticated attacks become possible, such as paraphrasing by larg…
Data-Centric AI in the Age of Large Language Models
Xinyi Xu, Zhaoxuan Wu, Rui Qiao +16
This position paper proposes a data-centric viewpoint of AI research, focusing on large language models (LLMs). We start by making the key observation that data is instrumental in…
A Remote Sim2real Aerial Competition: Fostering Reproducibility and Solutions' Diversity in Robotics Challenges
Spencer Teetaert, Wenda Zhao, Niu Xinyuan +21
Shared benchmark problems have historically been a fundamental driver of progress for scientific communities. In the context of academic conferences, competitions offer the opportu…