4 citations · 8 across the 6 of their papers we have counts for
9 papers · 1 filter
Unsupervised Multi-document Summarization with Holistic Inference
Haopeng Zhang, Sangwoo Cho, Kaiqiang Song +4
Multi-document summarization aims to obtain core information from a collection of documents written on the same topic. This paper proposes a new holistic framework for unsupervised…
Skills-in-Context Prompting: Unlocking Compositionality in Large Language Models
Jiaao Chen, Xiaoman Pan, Dian Yu +4
We investigate how to elicit compositional generalization capabilities in large language models (LLMs). Compositional generalization empowers LLMs to solve complex problems by comb…
DecipherPref: Analyzing Influential Factors in Human Preference Judgments via GPT-4
Yebowen Hu, Kaiqiang Song, Sangwoo Cho +3
Human preference judgments are pivotal in guiding large language models (LLMs) to produce outputs that align with human values. Human evaluations are also used in summarization tas…
Toward Unifying Text Segmentation and Long Document Summarization
Sangwoo Cho, Kaiqiang Song, Xiaoyang Wang +2
Text segmentation is important for signaling a document's structure. Without segmenting a long document into topically coherent sections, it is difficult for readers to comprehend…
Salience Allocation as Guidance for Abstractive Summarization
Fei Wang, Kaiqiang Song, Hongming Zhang +6
Abstractive summarization models typically learn to capture the salient information from scratch implicitly. Recent literature adds extractive summaries as guidance for abstractive…
Z-LaVI: Zero-Shot Language Solver Fueled by Visual Imagination
Yue Yang, Wenlin Yao, Hongming Zhang +3
Large-scale pretrained language models have made significant advances in solving downstream language understanding tasks. However, they generally suffer from reporting bias, the ph…