Fei Liu

State Fusion of Decentralized Optimal Unbiased FIR Filters

2018 · Journal of Electrical and Computer Engineering

The paper presents a decentralized fusion strategy based on the optimal unbiased finite impulse response (OUFIR) filter for discrete systems with correlated process and measurement noise. We extend OUFIR filter to apply in the model …

Guiding Extractive Summarization with Question-Answering Rewards

2019

Kristjan Arumae, Fei Liu. Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers). 2019.

Improving the Similarity Measure of Determinantal Point Processes for Extractive Multi-Document Summarization

2019 · arXiv (Cornell University)

The most important obstacles facing multi-document summarization include excessive redundancy in source descriptions and the looming shortage of training data. These obstacles prevent encoder-decoder models from being used directly, but optimization-based methods such as determinantal …

Understanding Points of Correspondence between Sentences for Abstractive Summarization

2020 · arXiv (Cornell University)

Logan Lebanoff, John Muchovej, Franck Dernoncourt, Doo Soon Kim, Lidan Wang, Walter Chang, Fei Liu. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop. 2020.

CATE: Computation-aware Neural Architecture Encoding with Transformers

2021 · arXiv (Cornell University)

Recent works (White et al., 2020a; Yan et al., 2020) demonstrate the importance of architecture encodings in Neural Architecture Search (NAS). These encodings encode either structure or computation information of the neural architectures. Compared to …

Large-Scale Scientific Research Instrument Resource Information Sharing Platform through O2O Mode

2021 · Journal of Physics Conference Series

Abstract Through the collection and integration of scientific instrument resources and scientific research services across the province, a scientific instrument public service system based on the O2O model will be constructed. The system takes the …

Generating User-Engaging News Headlines

2023

Pengshan Cai, Kaiqiang Song, Sangwoo Cho, Hongwei Wang, Xiaoyang Wang, Hong Yu, Fei Liu, Dong Yu. Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2023.

Algorithm Evolution Using Large Language Model

2023 · arXiv (Cornell University)

Optimization can be found in many real-life applications. Designing an effective algorithm for a specific optimization problem typically requires a tedious amount of effort from human experts with domain knowledge and algorithm design skills. In …

Multi-Task Learning for Routing Problem with Cross-Problem Zero-Shot Generalization

2024 · arXiv (Cornell University)

Vehicle routing problems (VRPs), which can be found in numerous real-world applications, have been an important research topic for several decades. Recently, the neural combinatorial optimization (NCO) approach that leverages a learning-based model to solve …

Stage-Wise and Prior-Aware Neural Speech Phase Prediction

2024 · arXiv (Cornell University)

This paper proposes a novel Stage-wise and Prior-aware Neural Speech Phase Prediction (SP-NSPP) model, which predicts the phase spectrum from input amplitude spectrum by two-stage neural networks. In the initial prior-construction stage, we preliminarily predict …

OmniStyle: Filtering High Quality Style Transfer Data at Scale

2025

In this paper, we introduce OmniStyle-1M, a large-scale paired style transfer dataset comprising over one million content-style-stylized image triplets across 1,000 diverse style categories, each enhanced with textual descriptions and instruction prompts. We show that …

Extractive Summarization by Maximizing Semantic Volume

2015

The most successful approaches to extractive text summarization seek to maximize bigram coverage subject to a budget constraint. In this work, we propose instead to maximize semantic volume. We embed each sentence in a semantic …

Abstract Meaning Representation for Multi-Document Summarization

2018 · arXiv (Cornell University)

Generating an abstract from a collection of documents is a desirable capability for many real-world applications. However, abstractive approaches to multi-document summarization have not been thoroughly investigated. This paper studies the feasibility of using Abstract …

Structure-Infused Copy Mechanisms for Abstractive Summarization

2018 · arXiv (Cornell University)

Seq2seq learning has produced promising results on summarization. However, in many cases, system summaries still struggle to keep the meaning of the original intact. They may miss out important words or relations that play critical …

Scoring Sentence Singletons and Pairs for Abstractive Summarization

2019

When writing a summary, humans tend to choose content from one or two sentences and merge them into a single summary sentence. However, the mechanisms behind the selection of one or multiple source sentences remain …

Dialog state tracking, a machine reading approach using Memory Network

2017

In an end-to-end dialog system, the aim of dialog state tracking is to accurately estimate a compact representation of the current dialog status from a sequence of noisy observations produced by the speech recognition and …

Adapting the Neural Encoder-Decoder Framework from Single to Multi-Document Summarization

2018

Generating a text abstract from a set of documents remains a challenging task. The neural encoder-decoder framework has recently been exploited to summarize single documents, but its success can in part be attributed to the …

MoverScore: Text Generation Evaluating with Contextualized Embeddings and Earth Mover Distance

2019

Wei Zhao, Maxime Peyrard, Fei Liu, Yang Gao, Christian M. Meyer, Steffen Eger. Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing …