--- title: "Yang Liu — papers and cards" description: "Yang Liu: 5 paper cards in the Research library (2006–2020), with what each paper is about, the ideas Mova took from it, and the co-authors." canonical: "https://research.elamur.ai/free/en/authors/yang-liu/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/yang-liu/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Yang Liu # Yang Liu 5 paper cards in the Research library · 2006–2020 Yang Liu wrote 5 of the papers Mova reads, in 2006–2020, most of them on [Discourse analysis](https://md.research.elamur.ai/free/en/topics/discourse-analysis/), [Part-of-speech tagging](https://md.research.elamur.ai/free/en/topics/part-of-speech-tagging/), [Machine translation](https://md.research.elamur.ai/free/en/topics/machine-translation/); often with [Amir Zeldes](https://md.research.elamur.ai/free/en/authors/amir-zeldes/), [Luke Gessler](https://md.research.elamur.ai/free/en/authors/luke-gessler/), [Siyao Peng](https://md.research.elamur.ai/free/en/authors/siyao-peng/). [OpenAlex](https://openalex.org/A5086000078) · [ORCID](https://orcid.org/0000-0002-3087-242X) · [**h-index 34**](https://openalex.org/authors/A5086000078) · [4778 citations](https://openalex.org/authors/A5086000078) · [128 works](https://openalex.org/works?filter=author.id:A5086000078) — openalex-snapshot, 2026-10-14 The profile is the library's match of the name; two people with one name are not always told apart. Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Yang+Liu) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Yang+Liu) · [dblp](https://dblp.org/search?q=Yang+Liu) · [ACL Anthology](https://aclanthology.org/search/?q=Yang+Liu) · [ORCID](https://orcid.org/orcid-search/search?searchQuery=Yang+Liu) Topics: [Discourse analysis](https://md.research.elamur.ai/free/en/topics/discourse-analysis/) 3 · [Part-of-speech tagging](https://md.research.elamur.ai/free/en/topics/part-of-speech-tagging/) 1 · [Machine translation](https://md.research.elamur.ai/free/en/topics/machine-translation/) 1 ## Papers 1. **[AMALGUM – A Free, Balanced, Multilayer English Web Corpus](https://md.research.elamur.ai/free/en/papers/lingbulk-2020-gessler-amalgum-free-balanced-multilayer-english/)** *(2020)* AMALGUM is an English web corpus of about 4 million tokens, built from openly licensed online sources in eight genres (news, interviews, travel guides, how-to guides, academic papers, fiction, biographies and forum posts), with about 500k tokens per genre. 2. **[GumDrop at the DISRPT2019 Shared Task: A Model Stacking Approach to Discourse Unit Segmentation and Connective Detection](https://md.research.elamur.ai/free/en/papers/yu-2019-gumdrop-disrpt2019-shared-task-model/)** *(2019)* GumDrop is a shared-task system for sentence splitting, elementary discourse unit segmentation and connective detection across 15 corpora in 10 languages (RST, SDRT and PDTB styles). 3. **[A Discourse Signal Annotation System for RST Trees](https://md.research.elamur.ai/free/en/papers/gessler-2019-discourse-signal-annotation-system-rst/)** *(2019)* The paper extends rstWeb, a browser tool for building Rhetorical Structure Theory trees, so that each relation in the tree can carry the signals that let a reader recognise it. 4. **[Beyond The Wall Street Journal: Anchoring and Comparing Discourse Signals across Genres](https://md.research.elamur.ai/free/en/papers/liu-2019-beyond-wall-street-journal-anchoring/)** *(2019)* The RST Signalling Corpus records which signals mark each RST relation in news, but not where they are. This pilot anchors signals to tokens in 12 GUM documents (11K tokens) from four genres — academic, how-to, interview, news — with the RST-SC taxonomy extended by visual (image) and textual (title, date… 5. **[Tree-to-String Alignment Template for Statistical Machine Translation](https://md.research.elamur.ai/free/en/papers/liu-2006-tree-string-alignment-template-statistical/)** *(2006)* A tree-to-string alignment template (TAT) pairs a source parse subtree, with variables at some of its leaves, with a target string that uses the same variables. ## Co-authors (10) - [Amir Zeldes](https://md.research.elamur.ai/free/en/authors/amir-zeldes/) ×3 - [Luke Gessler](https://md.research.elamur.ai/free/en/authors/luke-gessler/) ×2 - [Siyao Peng](https://md.research.elamur.ai/free/en/authors/siyao-peng/) ×2 - [Yilun Zhu](https://md.research.elamur.ai/free/en/authors/yilun-zhu/) ×2 - Mackenzie Gong - [Qun Liu](https://md.research.elamur.ai/free/en/authors/qun-liu/) - [Shabnam Behzad](https://md.research.elamur.ai/free/en/authors/shabnam-behzad/) - [Shouxun Lin](https://md.research.elamur.ai/free/en/authors/shouxun-lin/) - Yan Liu - Yue Yu ## More papers in the library (18) Pages of the Research library: our summary, the ideas, references and who cites each. - [Skywork-Reward: Bag of Tricks for Reward Modeling in LLMs](https://md.research.elamur.ai/free/en/papers/liu-2024-skywork-reward-bag-tricks/) — Chris Yuhao Liu, Liang Zeng, Jiacai Liu, et al. · 2024 - [Jailbreaking ChatGPT via Prompt Engineering: An Empirical Study](https://md.research.elamur.ai/free/en/papers/liu-2023-jailbreaking-chatgpt-prompt-engineering-empirical/) — Yi Liu, Gelei Deng, Zhengzi Xu, et al. · 2023 - [Large Language Model Unlearning](https://md.research.elamur.ai/free/en/papers/yao-2023-large-language-model-unlearning/) — Yuanshun Yao, Xiaojun Xu, Yang Liu · 2023 - [OpenChat: Advancing Open-source Language Models with Mixed-Quality Data](https://md.research.elamur.ai/free/en/papers/wang-2023-openchat-advancing-open-source-language/) — Guan Wang, Sijie Cheng, Xianyuan Zhan, et al. · 2023 - [Prompt Injection attack against LLM-integrated Applications](https://md.research.elamur.ai/free/en/papers/liu-2023-prompt-injection-attack-against-llm/) — Yi Liu; Gelei Deng; Yuekang Li; Kailong Wang; Zihao Wang; Xiaofeng Wang; Tianwei Zhang; Yepang Liu; Haoyu Wang; Yan Zheng; Leo Yu Zhang;, Yang Liu · 2023 - [Towards a Unified Multi-Dimensional Evaluator for Text Generation](https://md.research.elamur.ai/free/en/papers/zhong-2022-unified-multi-dimensional-evaluator-text/) — Ming Zhong, Yang Liu, Da Yin, et al. · 2022 - [DialogSum: A Real-Life Scenario Dialogue Summarization Dataset](https://md.research.elamur.ai/free/en/papers/chen-2021-dialogsum-real-life-scenario-dialogue/) — Yulong Chen, Yang Liu, Liang Chen, et al. · 2021 - [MediaSum: A Large-scale Media Interview Dataset for Dialogue Summarization](https://md.research.elamur.ai/free/en/papers/zhu-2021-mediasum-large-scale-media-interview/) — Chenguang Zhu, Yang Liu, Jie Mei, et al. · 2021 - [QMSum: A New Benchmark for Query-based Multi-domain Meeting Summarization](https://md.research.elamur.ai/free/en/papers/zhong-2021-qmsum-new-benchmark-query-based/) — Ming Zhong, Da Yin, Tao Yu, et al. · 2021 - [Want To Reduce Labeling Cost? GPT-3 Can Help](https://md.research.elamur.ai/free/en/papers/wang-2021-want-reduce-labeling-cost-gpt/) — Shuohang Wang, Yang Liu, Yichong Xu, et al. · 2021 - [Hierarchical Transformers for Multi-Document Summarization](https://md.research.elamur.ai/free/en/papers/liu-2019-hierarchical-transformers-multi-document-summarization/) — Yang Liu, Mirella Lapata · 2019 - [Improving the Transformer Translation Model with Document-Level Context](https://md.research.elamur.ai/free/en/papers/zhang-2018-improving-transformer-translation-model-document/) — Jiacheng Zhang, Huanbo Luan, Maosong Sun, et al. · 2018 - [Adversarial Training for Unsupervised Bilingual Lexicon Induction](https://md.research.elamur.ai/free/en/papers/zhang-2017-adversarial-training-unsupervised-bilingual-lexicon/) — Meng Zhang, Yang Liu, Huanbo Luan, et al. · 2017 - [Learning Contextually Informed Representations for Linear-Time Discourse Parsing](https://md.research.elamur.ai/free/en/papers/liu-2017-learning-contextually-informed-representations-linear/) — Yang Liu, Mirella Lapata · 2017 - [Using Context Information for Dialog Act Classification in DNN Framework](https://md.research.elamur.ai/free/en/papers/liu-2017-context-information-dialog-act-classification/) — Yang Liu, Kun Han, Zhao Tan, et al. · 2017 - [Modeling Coverage for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/tu-2016-modeling-coverage-neural-machine-translation/) — Zhaopeng Tu, Zhengdong Lu, Yang Liu, et al. · 2016 - [Recognizing Implicit Discourse Relations via Repeated Reading: Neural Networks with Multi-Level Attention](https://md.research.elamur.ai/free/en/papers/liu-2016-recognizing-implicit-discourse-relations-repeated/) — Yang Liu, Sujian Li · 2016 - [Minimum Risk Training for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/shen-2015-minimum-risk-training-neural-machine/) — Shiqi Shen, Yong Cheng, Zhongjun He, et al. · 2015