170 citations · 267 across the 16 of their papers we have counts for
16 papers
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…
Pretrained Language Model based Web Search Ranking: From Relevance to Satisfaction
Canjia Li, Xiaoyang Wang, Dongdong Li +6
Search engine plays a crucial role in satisfying users' diverse information needs. Recently, Pretrained Language Models (PLMs) based text ranking models have achieved huge success…
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…
Streamlining Multimodal Data Fusion in Wireless Communication and Sensor Networks
Mohammud J. Bocus, Xiaoyang Wang, Robert. J. Piechocki
This paper presents a novel approach for multimodal data fusion based on the Vector-Quantized Variational Autoencoder (VQVAE) architecture. The proposed method is simple yet effect…
OASum: Large-Scale Open Domain Aspect-based Summarization
Xianjun Yang, Kaiqiang Song, Sangwoo Cho +4
Aspect or query-based summarization has recently caught more attention, as it can generate differentiated summaries based on users' interests. However, the current dataset for aspe…
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…
Variational Autoencoder Assisted Neural Network Likelihood RSRP Prediction Model
Peizheng Li, Xiaoyang Wang, Robert Piechocki +3
Measuring customer experience on mobile data is of utmost importance for global mobile operators. The reference signal received power (RSRP) is one of the important indicators for…
Towards Abstractive Grounded Summarization of Podcast Transcripts
Kaiqiang Song, Chen Li, Xiaoyang Wang +2
Podcasts have recently shown a rapid rise in popularity. Summarization of podcast transcripts is of practical benefit to both content providers and consumers. It helps consumers to…
NaturalConv: A Chinese Dialogue Dataset Towards Multi-turn Topic-driven Conversation
Xiaoyang Wang, Chen Li, Jianqiao Zhao +1
In this paper, we propose a Chinese multi-turn topic-driven conversation dataset, NaturalConv, which allows the participants to chat anything they want as long as any element from…
Automatic Summarization of Open-Domain Podcast Episodes
Kaiqiang Song, Chen Li, Xiaoyang Wang +2
We present implementation details of our abstractive summarizers that achieve competitive results on the Podcast Summarization task of TREC 2020. A concise textual summary that cap…
Towards Faithful Neural Table-to-Text Generation with Content-Matching Constraints
Zhenyi Wang, Xiaoyang Wang, Bang An +2
Text generation from a knowledge base aims to translate knowledge triples to natural language descriptions. Most existing methods ignore the faithfulness between a generated text d…
STA: Spatial-Temporal Attention for Large-Scale Video-based Person Re-Identification
Yang Fu, Xiaoyang Wang, Yunchao Wei +1
In this work, we propose a novel Spatial-Temporal Attention (STA) approach to tackle the large-scale person re-identification task in videos. Different from the most existing metho…
Request-and-Reverify: Hierarchical Hypothesis Testing for Concept Drift Detection with Expensive Labels
Shujian Yu, Xiaoyang Wang, Jose C. Principe
One important assumption underlying common classification models is the stationarity of the data. However, in real-world streaming applications, the data concept indicated by the j…