no code implementations • NAACL (MIA) 2022 • Sumit Agarwal, Suraj Tripathi, Teruko Mitamura, Carolyn Penstein Rose
People speaking different kinds of languages search for information in a cross-lingual manner.
no code implementations • dialdoc (ACL) 2022 • Srijan Bansal, Suraj Tripathi, Sumit Agarwal, Sireesh Gururaja, Aditya Srikanth Veerubhotla, Ritam Dutt, Teruko Mitamura, Eric Nyberg
In this paper, we present our submission to the DialDoc shared task based on the MultiDoc2Dial dataset.
1 code implementation • 1 Mar 2024 • Kimihiro Hasegawa, Nikhil Kandukuri, Susan Holm, Yukari Yamakawa, Teruko Mitamura
Considering that identifying temporal orders of events is a core subtask in timeline construction, we further benchmark open LLMs on existing event temporal ordering datasets to gain a robust understanding of their capabilities.
1 code implementation • ICCV 2023 • Zhi-Qi Cheng, Qi Dai, SiYao Li, Jingdong Sun, Teruko Mitamura, Alexander G. Hauptmann
We evaluate ChartReader on Chart-to-Table, ChartQA, and Chart-to-Text tasks, demonstrating its superiority over existing methods.
no code implementations • 8 Feb 2023 • Jiefu Ou, Adithya Pratapa, Rishubh Gupta, Teruko Mitamura
In this work, we present an extension to the event grounding task that requires tackling hierarchical event structures from the KB.
1 code implementation • 18 Aug 2022 • Zhi-Qi Cheng, Qi Dai, SiYao Li, Teruko Mitamura, Alexander G. Hauptmann
In the second stage, we exploit transformer layers to unearth the potential semantic relations within both verbs and semantic roles.
1 code implementation • NAACL (MIA) 2022 • Adithya Pratapa, Rishubh Gupta, Teruko Mitamura
On the two proposed tasks, we compare multiple event linking systems including BM25+ (Lv and Zhai, 2011) and multilingual adaptations of the biencoder and crossencoder architectures from BLINK (Wu et al., 2020).
1 code implementation • CoNLL (EMNLP) 2021 • Adithya Pratapa, Zhengzhong Liu, Kimihiro Hasegawa, Linwei Li, Yukari Yamakawa, Shikun Zhang, Teruko Mitamura
To this end, we design a new annotation workflow with careful quality control and an easy-to-use annotation interface.
1 code implementation • AKBC Workshop CSKB 2021 • Steven Y. Feng, Kevin Lu, Zhuofu Tao, Malihe Alikhani, Teruko Mitamura, Eduard Hovy, Varun Gangal
We investigate the use of multimodal information contained in images as an effective method for enhancing the commonsense of Transformer models for text generation.
1 code implementation • Findings (ACL) 2021 • Steven Y. Feng, Varun Gangal, Jason Wei, Sarath Chandar, Soroush Vosoughi, Teruko Mitamura, Eduard Hovy
In this paper, we present a comprehensive and unifying survey of data augmentation for NLP by summarizing the literature in a structured manner.
1 code implementation • 14 Apr 2021 • Varun Gangal, Steven Y. Feng, Malihe Alikhani, Teruko Mitamura, Eduard Hovy
In this paper, we propose and investigate the task of Narrative Reordering (NAREOR) which involves rewriting a given story in a different narrative order while preserving its plot.
1 code implementation • EMNLP 2020 • Zhengzhong Liu, Guanxiong Ding, Avinash Bukkittu, Mansi Gupta, Pengzhi Gao, Atif Ahmed, Shikun Zhang, Xin Gao, Swapnil Singhavi, Linwei Li, Wei Wei, Zecong Hu, Haoran Shi, Haoying Zhang, Xiaodan Liang, Teruko Mitamura, Eric P. Xing, Zhiting Hu
Empirical natural language processing (NLP) systems in application domains (e. g., healthcare, finance, education) involve interoperation among multiple components, ranging from data ingestion, human annotation, to text retrieval, analysis, generation, and visualization.
no code implementations • 14 Jan 2021 • Vinay Damodaran, Sharanya Chakravarthy, Akshay Kumar, Anjana Umapathy, Teruko Mitamura, Yuta Nakashima, Noa Garcia, Chenhui Chu
Visual Question Answering (VQA) is of tremendous interest to the research community with important applications such as aiding visually impaired users and image-based search.
2 code implementations • EMNLP (DeeLIO) 2020 • Steven Y. Feng, Varun Gangal, Dongyeop Kang, Teruko Mitamura, Eduard Hovy
We also examine the relationship between the amount of augmentation and the quality of the generated text.
1 code implementation • 28 Aug 2020 • Noa Garcia, Chentao Ye, Zihua Liu, Qingtao Hu, Mayu Otani, Chenhui Chu, Yuta Nakashima, Teruko Mitamura
Our dataset inherently consists of visual (painting-based) and knowledge (comment-based) questions.
no code implementations • LREC 2020 • Keiichi Takamaru, Yasutomo Kimura, Hideyuki Shibuki, Hokuto Ototake, Yuzu Uchida, Kotaro Sakamoto, Madoka Ishioroshi, Teruko Mitamura, K, Noriko o
We conducted a {``}segmentation task{''} to identify the scope of one question and answer in the minutes as a sub task of the shared task.
no code implementations • WS 2019 • Sai Abishek Bhaskar, Rashi Rungta, James Route, Eric Nyberg, Teruko Mitamura
This paper presents a multi-task learning approach to natural language inference (NLI) and question entailment (RQE) in the biomedical domain.
no code implementations • WS 2019 • Vinayshekhar Bannihatti Kumar, Ashwin Srinivasan, Aditi Chaudhary, James Route, Teruko Mitamura, Eric Nyberg
This paper presents the submissions by Team Dr. Quad to the ACL-BioNLP 2019 shared task on Textual Inference and Question Entailment in the Medical Domain.
no code implementations • WS 2019 • Hemant Pugaliya, Karan Saxena, Shefali Garg, Sheetal Shalini, Prashant Gupta, Eric Nyberg, Teruko Mitamura
Parallel deep learning architectures like fine-tuned BERT and MT-DNN, have quickly become the state of the art, bypassing previous deep and shallow learning methods by a large margin.
no code implementations • 24 Feb 2019 • Aditi Chaudhary, Siddharth Dalmia, Junjie Hu, Xinjian Li, Austin Matthews, Aldrian Obaja Muis, Naoki Otani, Shruti Rijhwani, Zaid Sheikh, Nidhi Vyas, Xinyi Wang, Jiateng Xie, Ruochen Xu, Chunting Zhou, Peter J. Jansen, Yiming Yang, Lori Levin, Florian Metze, Teruko Mitamura, David R. Mortensen, Graham Neubig, Eduard Hovy, Alan W. black, Jaime Carbonell, Graham V. Horwood, Shabnam Tafreshi, Mona Diab, Efsun S. Kayi, Noura Farra, Kathleen McKeown
This paper describes the ARIEL-CMU submissions to the Low Resource Human Language Technologies (LoReHLT) 2018 evaluations for the tasks Machine Translation (MT), Entity Discovery and Linking (EDL), and detection of Situation Frames in Text and Speech (SF Text and Speech).
no code implementations • WS 2018 • Ashwin Naresh Kumar, Harini Kesavamoorthy, Madhura Das, Pramati Kalwad, Ch, Khyathi u, Teruko Mitamura, Eric Nyberg
The ever-increasing magnitude of biomedical information sources makes it difficult and time-consuming for a human researcher to find the most relevant documents and pinpointed answers for a specific question or topic when using only a traditional search engine.
1 code implementation • EMNLP 2018 • Zhengzhong Liu, Chenyan Xiong, Teruko Mitamura, Eduard Hovy
Our analyses demonstrate that our neural model captures interesting connections between salience and discourse unit relations (e. g., scripts and frame structures).
1 code implementation • COLING 2018 • Jun Araki, Teruko Mitamura
This paper introduces open-domain event detection, a new event detection paradigm to address issues of prior work on restricted domains and event annotation.
no code implementations • COLING 2018 • Zhengzhong Liu, Teruko Mitamura, Eduard Hovy
In this paper, we study two types of relation: Event Coreference and Event Sequencing.
no code implementations • WS 2018 • Vasu Sharma, Nitish Kulkarni, Srividya Pranavi, Gabriel Bayomi, Eric Nyberg, Teruko Mitamura
In this paper, we present a novel Biomedical Question Answering system, BioAMA: {``}Biomedical Ask Me Anything{''} on task 5b of the annual BioASQ challenge.
no code implementations • 13 Jun 2018 • Zhengzhong Liu, Teruko Mitamura, Eduard Hovy
In this paper, we study two types of relation: Event Coreference and Event Sequencing.
no code implementations • WS 2017 • Evangelia Spiliopoulou, Eduard Hovy, Teruko Mitamura
Recent methods for Event Detection focus on Deep Learning for automatic feature generation and feature ranking.
no code implementations • COLING 2016 • Jun Araki, Dheeraj Rajagopal, Sreecharan Sankaranarayanan, Susan Holm, Yukari Yamakawa, Teruko Mitamura
We present a novel approach to automated question generation that improves upon prior work both from a technology perspective and from an assessment perspective.
no code implementations • LREC 2014 • Jun Araki, Zhengzhong Liu, Eduard Hovy, Teruko Mitamura
First, we introduce a multiclass logistic regression model that can detect subevent relations in addition to full coreference.
no code implementations • LREC 2014 • Zhengzhong Liu, Jun Araki, Eduard Hovy, Teruko Mitamura
Event coreference is an important task for full text analysis.
no code implementations • LREC 2014 • Lori Levin, Teruko Mitamura, Brian MacWhinney, Davida Fromm, Jaime Carbonell, Weston Feely, Robert Frederking, Anatole Gershman, Carlos Ramirez
The extraction rules operate on the output of a dependency parser and identify the grammatical configurations (such as a verb with a prepositional phrase complement) that are likely to contain conventional metaphors.
no code implementations • LREC 2012 • Hideki Shima, Teruko Mitamura
Recognizing similar or close meaning on different surface form is a common challenge in various Natural Language Processing and Information Access applications.