1 code implementation • LREC 2022 • Yuanhe Tian, Han Qin, Fei Xia, Yan Song
Chinese word segmentation (CWS) and named entity recognition (NER) are two important tasks in Chinese natural language processing.
1 code implementation • LREC 2022 • Yuanhe Tian, Han Qin, Fei Xia, Yan Song
To achieve a better performance in SRL, a model is always required to have a good understanding of the context information.
Ranked #2 on Semantic Role Labeling on CoNLL 2005
1 code implementation • LREC 2022 • Han Qin, Yuanhe Tian, Fei Xia, Yan Song
Aspect-based sentiment analysis (ABSA) aims to predict the sentiment polarity towards a given aspect term in a sentence on the fine-grained level, which usually requires a good understanding of contextual information, especially appropriately distinguishing of a given aspect and its contexts, to achieve good performance.
Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA) +1
1 code implementation • LREC 2022 • Han Qin, Yuanhe Tian, Yan Song
Relation extraction (RE) is a sub-field of information extraction, which aims to extract the relation between two given named entities (NEs) in a sentence and thus requires a good understanding of contextual information, especially the entities and their surrounding texts.
1 code implementation • NAACL (BioNLP) 2021 • Yang Liu, Yuanhe Tian, Tsung-Hui Chang, Song Wu, Xiang Wan, Yan Song
Chinese word segmentation (CWS) and medical concept recognition are two fundamental tasks to process Chinese electronic medical records (EMRs) and play important roles in downstream tasks for understanding Chinese EMRs.
1 code implementation • Findings (ACL) 2022 • Yuanhe Tian, Yan Song, Fei Xia
Relation extraction (RE) is an important natural language processing task that predicts the relation between two given entities, where a good understanding of the contextual information is essential to achieve an outstanding model performance.
Ranked #11 on Relation Extraction on SemEval-2010 Task-8
no code implementations • EMNLP 2021 • Han Qin, Guimin Chen, Yuanhe Tian, Yan Song
Aspect-based sentiment analysis (ABSA) predicts the sentiment polarity towards a particular aspect term in a sentence, which is an important task in real-world applications.
Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA) +2
no code implementations • EMNLP 2021 • Han Qin, Yuanhe Tian, Yan Song
Most recent studies for relation extraction (RE) leverage the dependency tree of the input sentence to incorporate syntax-driven contextual information to improve model performance, with little attention paid to the limitation where high-quality dependency parsers in most cases unavailable, especially for in-domain scenarios.
1 code implementation • Findings (ACL) 2022 • Han Qin, Yan Song
In detail, a shared memory is used to record the mappings between visual and textual information, and the proposed reinforced algorithm is performed to learn the signal from the reports to guide the cross-modal alignment even though such reports are not directly related to how images and texts are mapped.
no code implementations • COLING 2022 • Yan Song
Chinese couplet generation aims to generate a pair of clauses (usually generating a subsequent clause given an antecedent one) with certain rules (e. g., morphological and syntactical symmetry) adhered and has long been a challenging task with cultural background.
1 code implementation • COLING 2022 • Yuanhe Tian, Yan Song, Fei Xia
Dependency parsing is an important fundamental natural language processing task which analyzes the syntactic structure of an input sentence by illustrating the syntactic relations between words.
Ranked #2 on Dependency Parsing on Penn Treebank
1 code implementation • 12 Oct 2024 • Jun Wang, Meng Fang, Ziyu Wan, Muning Wen, Jiachen Zhu, Anjie Liu, Ziqin Gong, Yan Song, Lei Chen, Lionel M. Ni, Linyi Yang, Ying Wen, Weinan Zhang
Inspired by the success of OpenAI's o1 model, which demonstrated improved reasoning abilities through step-by-step reasoning and reinforcement learning, OpenR integrates test-time compute, reinforcement learning, and process supervision to improve reasoning in LLMs.
no code implementations • 10 Oct 2024 • Xue Yan, Yan Song, Xidong Feng, Mengyue Yang, Haifeng Zhang, Haitham Bou Ammar, Jun Wang
In sequential decision-making (SDM) tasks, methods like reinforcement learning (RL) and heuristic search have made notable advances in specific cases.
no code implementations • 8 Oct 2024 • Zhaohui Jiang, Xuening Feng, Paul Weng, Yifei Zhu, Yan Song, Tianze Zhou, Yujing Hu, Tangjie Lv, Changjie Fan
On the other hand, facing corrective actions with different types of imperfection, our method can overcome the non-optimality of this feedback thanks to the guidance from proxy reward.
1 code implementation • 26 Sep 2024 • Pengfei Cai, Yan Song, Nan Jiang, Qing Gu, Ian McLoughlin
A significant challenge in sound event detection (SED) is the effective utilization of unlabeled data, given the limited availability of labeled data due to high annotation costs.
no code implementations • 3 Sep 2024 • Yihao Chen, Haochen Wu, Nan Jiang, Xiang Xia, Qing Gu, Yunqi Hao, Pengfei Cai, Yu Guan, Jialong Wang, Weilin Xie, Lei Fang, Sian Fang, Yan Song, Wu Guo, Lin Liu, Minqiang Xu
In Track 2, we continued using the CM system from Track 1 and fused it with a CNN-based ASV system.
1 code implementation • 16 Aug 2024 • Pengfei Cai, Yan Song, Kang Li, Haoyu Song, Ian McLoughlin
Sound event detection (SED) methods that leverage a large pre-trained Transformer encoder network have shown promising performance in recent DCASE challenges.
Ranked #1 on Sound Event Detection on DESED (PSDS1 metric)
no code implementations • 22 Jul 2024 • Hanwei Liu, Rudong An, Zhimeng Zhang, Bowen Ma, Wei zhang, Yan Song, Yujing Hu, Wei Chen, Yu Ding
First, the carefully designed normalization network struggles to directly remove the above task-irrelevant noise, by maintaining facial expression consistency but normalizing all original images to a common identity with consistent pose, and background.
no code implementations • 20 Jun 2024 • Mingyi Jia, Junwen Duan, Yan Song, Jianxin Wang
Electronic Medical Records (EMRs), while integral to modern healthcare, present challenges for clinical reasoning and diagnosis due to their complexity and information redundancy.
no code implementations • 14 Mar 2024 • Qirui Mi, Zhiyu Zhao, Siyu Xia, Yan Song, Jun Wang, Haifeng Zhang
The Lucas critique emphasizes the importance of considering microfoundations, how micro-agents (i. e., households) respond to policy changes, in macroeconomic policymaking.
1 code implementation • 26 Jan 2024 • XiaoJun Wu, Dixiang Zhang, Ruyi Gan, Junyu Lu, Ziwei Wu, Renliang Sun, Jiaxing Zhang, Pingjian Zhang, Yan Song
Recent advancements in text-to-image models have significantly enhanced image generation capabilities, yet a notable gap of open-source models persists in bilingual or Chinese language support.
no code implementations • 7 Dec 2023 • Ruyi Gan, XiaoJun Wu, Junyu Lu, Yuanhe Tian, Dixiang Zhang, Ziwei Wu, Renliang Sun, Chang Liu, Jiaxing Zhang, Pingjian Zhang, Yan Song
However, there are few specialized models in certain domains, such as interior design, which is attributed to the complex textual descriptions and detailed visual elements inherent in design, alongside the necessity for adaptable resolution.
1 code implementation • 23 Nov 2023 • Chang Liu, Yuanhe Tian, Yan Song
Specifically, we firstly cover pivotal RRG approaches based on the task-specific features of radiographs, reports, and the cross-modal relations between them, and then illustrate the benchmark datasets conventionally used for this task with evaluation metrics, subsequently analyze the performance of different approaches and finally offer our summary on the challenges and the trends in future directions.
no code implementations • 14 Nov 2023 • Ting Wang, Weidong Chen, Yuanhe Tian, Yan Song, Zhendong Mao
Having the difficulty of solving the semantic gap between images and texts for the image captioning task, conventional studies in this area paid some attention to treating semantic concepts as a bridge between the two modalities and improved captioning performance accordingly.
1 code implementation • 10 Nov 2023 • Yuanhe Tian, Ruyi Gan, Yan Song, Jiaxing Zhang, Yongdong Zhang
Recently, the increasing demand for superior medical services has highlighted the discrepancies in the medical infrastructure.
no code implementations • 6 Nov 2023 • Ruyi Gan, Ziwei Wu, Renliang Sun, Junyu Lu, XiaoJun Wu, Dixiang Zhang, Kunhao Pan, Junqing He, Yuanhe Tian, Ping Yang, Qi Yang, Hao Wang, Jiaxing Zhang, Yan Song
Although many such issues are addressed along the line of research on LLMs, an important yet practical limitation is that many studies overly pursue enlarging model sizes without comprehensively analyzing and optimizing the use of pre-training data in their learning process, as well as appropriate organization and leveraging of such data in training LLMs under cost-effective settings.
no code implementations • 27 Oct 2023 • Xue Yan, Yan Song, Xinyu Cui, Filippos Christianos, Haifeng Zhang, David Henry Mguni, Jun Wang
To that purpose, we offer a new leader-follower bilevel framework that is capable of learning to ask relevant questions (prompts) and subsequently undertaking reasoning to guide the learning of actions.
no code implementations • 12 Oct 2023 • Junyu Lu, Dixiang Zhang, XiaoJun Wu, Xinyu Gao, Ruyi Gan, Jiaxing Zhang, Yan Song, Pingjian Zhang
Recent advancements enlarge the capabilities of large language models (LLMs) in zero-shot image-to-text generation and understanding by integrating multi-modal inputs.
no code implementations • 11 Sep 2023 • Haotian Wang, Yuxuan Xi, Hang Chen, Jun Du, Yan Song, Qing Wang, Hengshun Zhou, Chenxi Wang, Jiefeng Ma, Pengfei Hu, Ya Jiang, Shi Cheng, Jie Zhang, Yuzhe Weng
Three different structures based on attention-guided feature gathering (AFG) are designed for deep feature fusion.
no code implementations • 20 May 2023 • Xiao-Min Zeng, Yan Song, Zhu Zhuo, Yu Zhou, Yu-Hong Li, Hui Xue, Li-Rong Dai, Ian McLoughlin
In this paper, we propose a joint generative and contrastive representation learning method (GeCo) for anomalous sound detection (ASD).
1 code implementation • 16 May 2023 • Yan Song, He Jiang, Zheng Tian, Haifeng Zhang, Yingping Zhang, Jiangcheng Zhu, Zonghong Dai, Weinan Zhang, Jun Wang
Few multi-agent reinforcement learning (MARL) research on Google Research Football (GRF) focus on the 11v11 multi-agent full-game scenario and to the best of our knowledge, no open benchmark on this scenario has been released to the public.
no code implementations • 23 Mar 2023 • Stephanie Milani, Anssi Kanervisto, Karolis Ramanauskas, Sander Schulhoff, Brandon Houghton, Sharada Mohanty, Byron Galbraith, Ke Chen, Yan Song, Tianze Zhou, Bingquan Yu, He Liu, Kai Guan, Yujing Hu, Tangjie Lv, Federico Malato, Florian Leopold, Amogh Raut, Ville Hautamäki, Andrew Melnik, Shu Ishida, João F. Henriques, Robert Klassert, Walter Laurito, Ellen Novoseller, Vinicius G. Goecks, Nicholas Waytowich, David Watkins, Josh Miller, Rohin Shah
To facilitate research in the direction of fine-tuning foundation models from human feedback, we held the MineRL BASALT Competition on Fine-Tuning from Human Feedback at NeurIPS 2022.
no code implementations • 7 Mar 2023 • Kang Li, Yan Song, Li-Rong Dai, Ian McLoughlin, Xin Fang, Lin Liu
In this paper, we propose an effective sound event detection (SED) method based on the audio spectrogram transformer (AST) model, pretrained on the large-scale AudioSet for audio tagging (AT) task, termed AST-SED.
1 code implementation • 20 Feb 2023 • Shizhe Diao, Sedrick Scott Keh, Liangming Pan, Zhiliang Tian, Yan Song, Tong Zhang
Social media classification tasks (e. g., tweet sentiment analysis, tweet stance detection) are challenging because social media posts are typically short, informal, and ambiguous.
no code implementations • 27 Jan 2023 • Zhuo Li, Derui Zhu, Yujing Hu, Xiaofei Xie, Lei Ma, Yan Zheng, Yan Song, Yingfeng Chen, Jianjun Zhao
Generally, episodic control-based approaches are solutions that leverage highly-rewarded past experiences to improve sample efficiency of DRL algorithms.
1 code implementation • CVPR 2023 • Zheren Fu, Zhendong Mao, Yan Song, Yongdong Zhang
Image-text matching, a bridge connecting image and language, is an important task, which generally learns a holistic cross-modal embedding to achieve a high-quality semantic alignment between the two modalities.
1 code implementation • 13 Dec 2022 • Bin Wang, Yan Song, Fanming Wang, Yang Zhao, Xiangbo Shu, Yan Rui
To balance the annotation labor and the granularity of supervision, single-frame annotation has been introduced in temporal action localization.
no code implementations • 2 Jul 2022 • Yang Zhao, Yan Song
To obtain more information to optimize the model, the existing method generated pseudo frame-wise labels iteratively based on the output of a segmentation model and the timestamp annotations.
1 code implementation • ACL 2021 • Zhihong Chen, Yaling Shen, Yan Song, Xiang Wan
Medical imaging plays a significant role in clinical practice of medical diagnosis, where the text reports of the images are essential in understanding them and facilitating later treatments.
no code implementations • 21 Dec 2021 • Xiangbo Shu, Jiawen Yang, Rui Yan, Yan Song
This work focuses on the task of elderly activity recognition, which is a challenging task due to the existence of individual actions and human-object interactions in elderly activities.
1 code implementation • Findings (ACL) 2021 • Jinpeng Hu, Jianling Li, Zhihong Chen, Yaling Shen, Yan Song, Xiang Wan, Tsung-Hui Chang
In this paper, we propose a novel method for automatic impression generation, where a word graph is constructed from the findings to record the critical words and their relations, then a Word Graph guided Summarization model (WGSum) is designed to generate impressions with the help of the word graph.
no code implementations • 17 Aug 2021 • Yi Li, Yan Song, Qin Zhang
We study the problem of learning to cluster data points using an oracle which can answer same-cluster queries.
1 code implementation • ACL 2021 • Yuanhe Tian, Guimin Chen, Yan Song, Xiang Wan
Syntactic information, especially dependency trees, has been widely used by existing studies to improve relation extraction with better semantic guidance for analyzing the context information associated with the given entities.
Ranked #12 on Relation Extraction on SemEval-2010 Task-8
1 code implementation • ACL 2021 • Han Qin, Guimin Chen, Yuanhe Tian, Yan Song
Arabic diacritization is a fundamental task for Arabic language processing.
1 code implementation • ACL 2021 • Shizhe Diao, Ruijia Xu, Hongjin Su, Yilei Jiang, Yan Song, Tong Zhang
In this paper, we aim to adapt a generic pretrained model with a relatively small amount of domain-specific data.
Ranked #38 on Time Series Forecasting on ETTh1 (336) Multivariate
no code implementations • 24 Jun 2021 • Shuang Li, Lu Wang, Xinyun Chen, Yixiang Fang, Yan Song
In this paper, we model the propagation of the COVID-19 as spatio-temporal point processes and propose a generative and intensity-free model to track the spread of the disease.
1 code implementation • Findings (ACL) 2021 • Yu Lu, Junwei Bao, Yan Song, Zichen Ma, Shuguang Cui, Youzheng Wu, Xiaodong He
Existing conversational recommendation (CR) systems usually suffer from insufficient item information when conducted on short dialogue history and unfamiliar items.
2 code implementations • NAACL 2021 • Yuanhe Tian, Guimin Chen, Yan Song
It is popular that neural graph-based models are applied in existing aspect-based sentiment analysis (ABSA) studies for utilizing word relations through dependency parses to facilitate the task with better semantic guidance for analyzing context and aspect words.
Ranked #3 on Aspect-Based Sentiment Analysis (ABSA) on MAMS
Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA)
1 code implementation • 4 May 2021 • Yan Song, Tong Zhang, Yonggang Wang, Kai-Fu Lee
Pre-trained text encoders have drawn sustaining attention in natural language processing (NLP) and shown their capability in obtaining promising results in different tasks.
no code implementations • 20 Apr 2021 • Tiancheng Li, Yan Song, Hongqi Fan
This paper addresses the problem of real-time detection and tracking of a non-cooperative target in the challenging scenario with almost no a-priori information about target birth, death, dynamics and detection probability.
1 code implementation • EACL 2021 • Yuanhe Tian, Guimin Chen, Yan Song
Aspect-level sentiment analysis (ASA) has received much attention in recent years.
no code implementations • 15 Mar 2021 • Zi-Qiang Zhang, Yan Song, Ming-Hui Wu, Xin Fang, Li-Rong Dai
In this paper, we propose a weakly supervised multilingual representation learning framework, called cross-lingual self-training (XLST).
1 code implementation • COLING 2020 • Yuanhe Tian, Yan Song, Fei Xia
However, their work on modeling such contextual features is limited to concatenating the features or their embeddings directly with the input embeddings without distinguishing whether the contextual features are important for the joint task in the specific context.
1 code implementation • COLING 2020 • Guimin Chen, Yuanhe Tian, Yan Song
End-to-end aspect-based sentiment analysis (EASA) consists of two sub-tasks: the first extracts the aspect terms in a sentence and the second predicts the sentiment polarities for such terms.
1 code implementation • COLING 2020 • Yan Song, Yuanhe Tian, Nan Wang, Fei Xia
For the particular dataset used in this study, we show that high-quality summaries can be generated by extracting two types of utterances, namely, problem statements and treatment recommendations.
no code implementations • COLING 2020 • Jianfeng Liu, Ling Luo, Xiang Ao, Yan Song, Haoran Xu, Jian Ye
Multi-source neural machine translation aims to translate from parallel sources of information (e. g. languages, images, etc.)
1 code implementation • BMC Bioinformatics 2020 • Yuanhe Tian, Wang Shen, Yan Song, Fei Xia, Min He, Kenli Li
The experimental results on six English benchmark datasets demonstrate that auto-processed syntactic information can be a useful resource for BioNER and our method with KVMN can appropriately leverage such information to improve model performance.
Ranked #1 on Named Entity Recognition (NER) on Species-800
2 code implementations • EMNLP 2020 • Zhihong Chen, Yan Song, Tsung-Hui Chang, Xiang Wan
Particularly, this is the first work reporting the generation results on MIMIC-CXR to the best of our knowledge.
1 code implementation • EMNLP 2020 • Yuyang Nie, Yuanhe Tian, Xiang Wan, Yan Song, Bo Dai
In particular, we obtain the augmented semantic information from a large-scale corpus, and propose an attentive semantic augmentation module and a gate module to encode and aggregate such information, respectively.
Ranked #4 on Named Entity Recognition (NER) on WNUT 2016
Chinese Named Entity Recognition named-entity-recognition +3
1 code implementation • Findings of the Association for Computational Linguistics 2020 • Yuyang Nie, Yuanhe Tian, Yan Song, Xiang Ao, Xiang Wan
Named entity recognition (NER) is highly sensitive to sentential syntactic and semantic properties where entities may be extracted according to how they are used and placed in the running text.
Ranked #3 on Named Entity Recognition (NER) on WNUT 2016
Chinese Named Entity Recognition named-entity-recognition +2
1 code implementation • Findings of the Association for Computational Linguistics 2020 • Yuanhe Tian, Yan Song, Fei Xia, Tong Zhang
Constituency parsing is a fundamental and important task for natural language understanding, where a good representation of contextual information can help this task.
Ranked #1 on Constituency Parsing on ATB
1 code implementation • EMNLP 2020 • Yuanhe Tian, Yan Song, Fei Xia
Specifically, we build the graph from chunks (n-grams) extracted from a lexicon and apply attention over the graph, so that different word pairs from the contexts within and across chunks are weighted in the model and facilitate the supertagging accordingly.
Ranked #2 on CCG Supertagging on CCGbank
1 code implementation • ACL 2020 • Yuanhe Tian, Yan Song, Fei Xia, Tong Zhang, Yonggang Wang
Contextual features always play an important role in Chinese word segmentation (CWS).
Ranked #1 on Chinese Word Segmentation on CITYU
no code implementations • WS 2020 • Nan Wang, Yan Song, Fei Xia
Medical conversation is a central part of medical care.
1 code implementation • ACL 2020 • Yuanhe Tian, Yan Song, Xiang Ao, Fei Xia, Xiaojun Quan, Tong Zhang, Yonggang Wang
Chinese word segmentation (CWS) and part-of-speech (POS) tagging are important fundamental tasks for Chinese language processing, where joint learning of them is an effective one-step solution for both tasks.
no code implementations • ACL 2020 • Kun Li, Chengbo Chen, Xiaojun Quan, Qing Ling, Yan Song
In this paper, we formulate the data augmentation as a conditional generation task: generating a new sentence while preserving the original opinion targets and labels.
1 code implementation • 21 Apr 2020 • Shizhe Diao, Yan Song, Tong Zhang
Keyphrase generation aims to produce a set of phrases summarizing the essentials of a given document.
2 code implementations • 10 Mar 2020 • Yan Song, Yingfeng Chen, Yujing Hu, Changjie Fan
In this paper, we focus on improving the effectiveness of finding unknown states and propose action balance exploration, which balances the frequency of selecting each action at a given state and can be treated as an extension of upper confidence bound (UCB) to deep reinforcement learning.
no code implementations • 23 Jan 2020 • Kun Xu, Linfeng Song, Yansong Feng, Yan Song, Dong Yu
Existing entity alignment methods mainly vary on the choices of encoding the knowledge graph, but they typically use the same decoding method, which independently chooses the local optimal match for each source entity.
1 code implementation • IJCNLP 2019 • Hongming Zhang, Jiaxin Bai, Yan Song, Kun Xu, Changlong Yu, Yangqiu Song, Wilfred Ng, Dong Yu
Therefore, in this paper, we propose a multiplex word embedding model, which can be easily extended according to various relations among words.
7 code implementations • Findings of the Association for Computational Linguistics 2020 • Shizhe Diao, Jiaxin Bai, Yan Song, Tong Zhang, Yonggang Wang
Moreover, it is shown that reasonable performance can be obtained when ZEN is trained on a small corpus, which is important for applying pre-training techniques to scenarios with limited data.
Ranked #1 on Chinese Part-of-Speech Tagging on CTB5 Dev
Chinese Named Entity Recognition Chinese Word Segmentation +5
1 code implementation • IJCNLP 2019 • Ling Luo, Xiang Ao, Yan Song, Feiyang Pan, Min Yang, Qing He
In this work, we re-examine the problem of extractive text summarization for long documents.
Ranked #8 on Extractive Text Summarization on CNN / Daily Mail
1 code implementation • IJCNLP 2019 • Xintong Yu, Hongming Zhang, Yangqiu Song, Yan Song, Chang-Shui Zhang
To tackle this challenge, in this paper, we formally define the task of visual-aware pronoun coreference resolution (PCR) and introduce VisPro, a large-scale dialogue PCR dataset, to investigate whether and how the visual information can help resolve pronouns in dialogues.
1 code implementation • WS 2019 • Zhaofeng Wu, Yan Song, Sicong Huang, Yuanhe Tian, Fei Xia
Natural language inference (NLI) is challenging, especially when it is applied to technical domains such as biomedical settings.
1 code implementation • WS 2019 • Yuanhe Tian, Weicheng Ma, Fei Xia, Yan Song
Question answering (QA) is a challenging task in natural language processing (NLP), especially when it is applied to specific domains.
no code implementations • IJCAI 2019 • Ling Luo, Xiang Ao, Yan Song, Jinyao Li, Xiaopeng Yang, Qing He, Dong Yu
Aspect extraction relies on identifying aspects by discovering coherence among words, which is challenging when word meanings are diversified and processing on short texts.
Aspect Extraction Aspect Term Extraction and Sentiment Classification +1
1 code implementation • ACL 2019 • Hongming Zhang, Yan Song, Yangqiu Song, Dong Yu
Resolving pronoun coreference requires knowledge support, especially for particular domains (e. g., medicine).
1 code implementation • ACL 2019 • Miaofeng Liu, Yan Song, Hongbin Zou, Tong Zhang
Supervised models suffer from the problem of domain shifting where distribution mismatch in the data across domains greatly affect model performance.
1 code implementation • 7 Jun 2019 • Guoyin Wang, Yan Song, Yue Zhang, Dong Yu
Word embeddings are traditionally trained on a large corpus in an unsupervised setting, with no specific design for incorporating domain knowledge.
1 code implementation • ACL 2019 • Kun Xu, Li-Wei Wang, Mo Yu, Yansong Feng, Yan Song, Zhiguo Wang, Dong Yu
Previous cross-lingual knowledge graph (KG) alignment studies rely on entity embeddings derived only from monolingual KG structural information, which may fail at matching entities that have different facts in two KGs.
1 code implementation • NAACL 2019 • Hongming Zhang, Yan Song, Yangqiu Song
Linking pronominal expressions to the correct references requires, in many cases, better analysis of the contextual information and external knowledge.
no code implementations • CL 2018 • Jing Li, Yan Song, Zhongyu Wei, Kam-Fai Wong
To address this issue, we organize microblog messages as conversation trees based on their reposting and replying relations, and propose an unsupervised model that jointly learns word distributions to represent: (1) different roles of conversational discourse, and (2) various latent topics in reflecting content information.
no code implementations • EMNLP 2018 • Juntao Li, Yan Song, Haisong Zhang, Dongmin Chen, Shuming Shi, Dongyan Zhao, Rui Yan
It is a challenging task to automatically compose poems with not only fluent expressions but also aesthetic wording.
1 code implementation • EMNLP 2018 • Dingmin Wang, Yan Song, Jing Li, Jialong Han, Haisong Zhang
Chinese spelling check (CSC) is a challenging yet meaningful task, which not only serves as a preprocessing in many natural language processing(NLP) applications, but also facilitates reading and understanding of running texts in peoples{'} daily lives.
1 code implementation • EMNLP 2018 • Xiuying Chen, Shen Gao, Chongyang Tao, Yan Song, Dongyan Zhao, Rui Yan
In this paper, we introduce Iterative Text Summarization (ITS), an iteration-based model for supervised extractive text summarization, inspired by the observation that it is often necessary for a human to read an article multiple times in order to fully understand and summarize its contents.
Ranked #14 on Extractive Text Summarization on CNN / Daily Mail
no code implementations • 27 Sep 2018 • Miaofeng Liu, Yan Song, Hongbin Zou, Tong Zhang
Following the TDS methodology, in this paper, we propose a general data selection framework with representation learning and distribution matching simultaneously for domain adaptation on neural models.
no code implementations • 11 Sep 2018 • Jing Li, Yan Song, Zhongyu Wei, Kam-Fai Wong
To address this issue, we organize microblog messages as conversation trees based on their reposting and replying relations, and propose an unsupervised model that jointly learns word distributions to represent: 1) different roles of conversational discourse, 2) various latent topics in reflecting content information.
no code implementations • EMNLP 2018 • Jichuan Zeng, Jing Li, Yan Song, Cuiyun Gao, Michael R. Lyu, Irwin King
Many classification models work poorly on short texts due to data sparsity.
no code implementations • WS 2018 • Miaofeng Liu, Jialong Han, Haisong Zhang, Yan Song
With the development of medical information management, numerous medical data are being classified, indexed, and searched in various systems.
no code implementations • WS 2018 • Nan Wang, Yan Song, Fei Xia
This paper describes the COSTA scheme for coding structures and actions in conversation.
no code implementations • NAACL 2018 • Yan Song, Shuming Shi, Jing Li, Haisong Zhang
In this paper, we present directional skip-gram (DSG), a simple but effective enhancement of the skip-gram model by explicitly distinguishing left and right context in word prediction.
no code implementations • NAACL 2018 • Yingyi Zhang, Jing Li, Yan Song, Chengzhi Zhang
Existing keyphrase extraction methods suffer from data sparsity problem when they are conducted on short and informal texts, especially microblog messages.
no code implementations • 15 May 2018 • Jing Li, Yan Song, Haisong Zhang, Shuming Shi
This paper presents a large-scale corpus for non-task-oriented dialogue response selection, which contains over 27K distinct prompts more than 82K responses collected from social media.
1 code implementation • ACL 2018 • Jialong Han, Yan Song, Wayne Xin Zhao, Shuming Shi, Haisong Zhang
Hypertext documents, such as web pages and academic papers, are of great importance in delivering information in our daily life.
no code implementations • CONLL 2017 • Yan Song, Chia-Jung Lee, Fei Xia
This paper presents a unified framework that leverages pre-learned or external priors, in the form of a regularizer, for enhancing conventional language model-based embedding learning.
no code implementations • 3 Jun 2017 • Xiangbo Shu, Jinhui Tang, Guo-Jun Qi, Yan Song, Zechao Li, Liyan Zhang
To this end, we propose a novel Concurrence-Aware Long Short-Term Sub-Memories (Co-LSTSM) to model the long-term inter-related dynamics between two interacting people on the bounding boxes covering people.
Ranked #2 on Human Interaction Recognition on BIT
no code implementations • EACL 2017 • Yan Song, Chia-Jung Lee
Many important email-related tasks, such as email classification or search, highly rely on building quality document representations (e. g., bag-of-words or key phrases) to assist matching and understanding.
no code implementations • LREC 2014 • Yan Song, Fei Xia
Languages change over time and ancient languages have been studied in linguistics and other related fields.
no code implementations • LREC 2012 • Yan Song, Fei Xia
Domain adaptation is an important topic for natural language processing.