22 citations · 33 across the 8 of their papers we have counts for
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cs.CL2024
Do RAG Systems Cover What Matters? Evaluating and Optimizing Responses with Sub-Question Coverage
Kaige Xie, Philippe Laban, Prafulla Kumar Choubey +2
Evaluating retrieval-augmented generation (RAG) systems remains challenging, particularly for open-ended questions that lack definitive answers and require coverage of multiple sub…
cs.CL2024
Making Large Language Models into World Models with Precondition and Effect Knowledge
Kaige Xie, Ian Yang, John Gunerli +1
World models, which encapsulate the dynamics of how actions affect environments, are foundational to the functioning of intelligent agents. In this work, we explore the potential o…
cs.CL2024★ 4 cited
Creating Suspenseful Stories: Iterative Planning with Large Language Models
Kaige Xie, Mark Riedl
Automated story generation has been one of the long-standing challenges in NLP. Among all dimensions of stories, suspense is very common in human-written stories but relatively und…