1 code implementation • LREC 2022 • Amir Pouran Ben Veyseh, Viet Lai, Franck Dernoncourt, Thien Nguyen
Question-Answer (QA) is one of the effective methods for storing knowledge which can be used for future retrieval.
no code implementations • EMNLP 2021 • Amir Pouran Ben Veyseh, Minh Van Nguyen, Nghia Ngo Trung, Bonan Min, Thien Huu Nguyen
To address this issue, we propose a novel method to model document-level context for ED that dynamically selects relevant sentences in the document for the event prediction of the target sentence.
no code implementations • *SEM (NAACL) 2022 • Amir Pouran Ben Veyseh, Thien Nguyen
Event Detection (ED) aims to identify mentions/triggers of real world events in text.
no code implementations • LREC 2022 • Viet Lai, Amir Pouran Ben Veyseh, Franck Dernoncourt, Thien Nguyen
Livestreaming videos have become an effective broadcasting method for both video sharing and educational purposes.
no code implementations • Findings (ACL) 2022 • Amir Pouran Ben Veyseh, Minh Van Nguyen, Franck Dernoncourt, Bonan Min, Thien Nguyen
Event Argument Extraction (EAE) is one of the sub-tasks of event extraction, aiming to recognize the role of each entity mention toward a specific event trigger.
1 code implementation • COLING 2022 • Viet Dac Lai, Amir Pouran Ben Veyseh, Minh Van Nguyen, Franck Dernoncourt, Thien Huu Nguyen
Our dataset thus enable a new research direction on cross-lingual transfer learning for ECI.
no code implementations • Findings (NAACL) 2022 • Luis Guzman-Nateras, Viet Lai, Amir Pouran Ben Veyseh, Franck Dernoncourt, Thien Nguyen
In particular, we introduce SuicideED: a new dataset for the ED task that features seven suicidal event types to comprehensively capture suicide actions and ideation, and general risk and protective factors.
no code implementations • EMNLP 2020 • Hieu Man Duc Trong, Duc Trong Le, Amir Pouran Ben Veyseh, Thuat Nguyen, Thien Huu Nguyen
Detecting cybersecurity events is necessary to keep us informed about the fast growing number of such events reported in text.
1 code implementation • Findings (NAACL) 2022 • Viet Lai, Amir Pouran Ben Veyseh, Franck Dernoncourt, Thien Nguyen
This work presents a new human-annotated corpus, called BehancePR, for punctuation restoration in livestreaming video transcripts.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +4
no code implementations • SemEval (NAACL) 2022 • Viet Lai, Amir Pouran Ben Veyseh, Franck Dernoncourt, Thien Nguyen
We describe Symlink, a SemEval shared task of extracting mathematical symbols and their descriptions from LaTeX source of scientific documents.
no code implementations • Findings (ACL) 2022 • Amir Pouran Ben Veyseh, Ning Xu, Quan Tran, Varun Manjunatha, Franck Dernoncourt, Thien Nguyen
Toxic span detection is the task of recognizing offensive spans in a text snippet.
no code implementations • COLING 2022 • Amir Pouran Ben Veyseh, Viet Dac Lai, Franck Dernoncourt, Thien Huu Nguyen
As such, the challenges of EE in informal and noisy texts are not adequately studied.
no code implementations • COLING 2022 • Amir Pouran Ben Veyseh, Quan Hung Tran, Seunghyun Yoon, Varun Manjunatha, Hanieh Deilamsalehy, Rajiv Jain, Trung Bui, Walter W. Chang, Franck Dernoncourt, Thien Huu Nguyen
To this end, this work studies new challenges of KP in transcripts of videos, an understudied domain for KP that involves informal texts and non-cohesive presentation styles.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1
no code implementations • 12 Apr 2023 • Viet Dac Lai, Nghia Trung Ngo, Amir Pouran Ben Veyseh, Hieu Man, Franck Dernoncourt, Trung Bui, Thien Huu Nguyen
The answer to this question requires a thorough evaluation of ChatGPT over multiple tasks with diverse languages and large datasets (i. e., beyond reported anecdotes), which is still missing or limited in current research.
no code implementations • 11 Nov 2022 • Amir Pouran Ben Veyseh, Javid Ebrahimi, Franck Dernoncourt, Thien Huu Nguyen
Event Extraction (EE) is one of the fundamental tasks in Information Extraction (IE) that aims to recognize event mentions and their arguments (i. e., participants) from text.
no code implementations • NAACL 2022 • Amir Pouran Ben Veyseh, Minh Van Nguyen, Franck Dernoncourt, Thien Huu Nguyen
Event Detection (ED) is the task of identifying and classifying trigger words of event mentions in text.
no code implementations • 11 Sep 2022 • Amir Pouran Ben Veyseh, Nicole Meister, Franck Dernoncourt, Thien Huu Nguyen
Keyphrase extraction is one of the essential tasks for document understanding in NLP.
no code implementations • 11 Sep 2022 • Amir Pouran Ben Veyseh, Franck Dernoncourt, Thien Huu Nguyen
In order to alleviate this issue, one solution is to link the streaming videos with the relevant tutorial available for the tools used in the streaming video.
no code implementations • 26 Apr 2022 • Viet Dac Lai, Amir Pouran Ben Veyseh, Franck Dernoncourt, Thien Huu Nguyen
Mathematical symbols and descriptions appear in various forms across document section boundaries without explicit markup.
no code implementations • 19 Feb 2022 • Viet Dac Lai, Amir Pouran Ben Veyseh, Franck Dernoncourt, Thien Huu Nguyen
Given the increasing number of livestreaming videos, automatic speech recognition and post-processing for livestreaming video transcripts are crucial for efficient data management as well as knowledge mining.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +4
no code implementations • COLING 2022 • Amir Pouran Ben Veyseh, Nicole Meister, Seunghyun Yoon, Rajiv Jain, Franck Dernoncourt, Thien Huu Nguyen
Acronym extraction is the task of identifying acronyms and their expanded forms in texts that is necessary for various NLP applications.
no code implementations • 1 Nov 2021 • Bonan Min, Hayley Ross, Elior Sulem, Amir Pouran Ben Veyseh, Thien Huu Nguyen, Oscar Sainz, Eneko Agirre, Ilana Heinz, Dan Roth
Large, pre-trained transformer-based language models such as BERT have drastically changed the Natural Language Processing (NLP) field.
no code implementations • ACL 2021 • Amir Pouran Ben Veyseh, Viet Lai, Franck Dernoncourt, Thien Huu Nguyen
To prevent the noises inevitable in automatically generated data from hampering training process, we propose to exploit a teacher-student architecture in which the teacher is supposed to learn anchor knowledge from the original data.
no code implementations • SEMEVAL 2021 • Amir Pouran Ben Veyseh, Franck Dernoncourt, Thien Huu Nguyen
To this end, in this paper, we propose a novel model for the task of measurement relation extraction (MRE) whose goal is to recognize the relation between measured entities, quantities, and conditions mentioned in a document.
1 code implementation • EACL 2021 • Amir Pouran Ben Veyseh, Franck Dernoncourt, Walter Chang, Thien Huu Nguyen
However, none of the existing works provide a unified solution capable of processing acronyms in various domains and to be publicly available.
1 code implementation • EACL 2021 • Minh Van Nguyen, Viet Dac Lai, Amir Pouran Ben Veyseh, Thien Huu Nguyen
Finally, we create a demo video for Trankit at: https://youtu. be/q0KGP3zGjGc.
Ranked #1 on Sentence segmentation on UD2.5 test
no code implementations • 22 Dec 2020 • Amir Pouran Ben Veyseh, Franck Dernoncourt, Thien Huu Nguyen, Walter Chang, Leo Anthony Celi
To push forward research in this direction, we have organized two shared task for acronym identification and acronym disambiguation in scientific documents, named AI@SDU and AD@SDU, respectively.
2 code implementations • COLING 2020 • Amir Pouran Ben Veyseh, Franck Dernoncourt, Quan Hung Tran, Thien Huu Nguyen
The proposed model outperforms the state-of-the-art models on the new AD dataset, providing a strong baseline for future research on this dataset.
no code implementations • EMNLP 2020 • Amir Pouran Ben Veyseh, Nasim Nouri, Franck Dernoncourt, Dejing Dou, Thien Huu Nguyen
In this work, we propose to incorporate the syntactic structures of the sentences into the deep learning models for TOWE, leveraging the syntax-based opinion possibility scores and the syntactic connections between the words.
Aspect-Based Sentiment Analysis Aspect-oriented Opinion Extraction +1
no code implementations • Findings of the Association for Computational Linguistics 2020 • Amir Pouran Ben Veyseh, Nasim Nour, Franck Dernoncourt, Quan Hung Tran, Dejing Dou, Thien Huu Nguyen
In addition, we propose a mechanism to obtain the importance scores for each word in the sentences based on the dependency trees that are then injected into the model to improve the representation vectors for ABSA.
Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA) +1
no code implementations • Findings of the Association for Computational Linguistics 2020 • Amir Pouran Ben Veyseh, Tuan Ngo Nguyen, Thien Huu Nguyen
The goal of Event Argument Extraction (EAE) is to find the role of each entity mention for a given event trigger word.
no code implementations • ACL 2020 • Amir Pouran Ben Veyseh, Franck Dernoncourt, Dejing Dou, Thien Huu Nguyen
In order to overcome these issues, we propose a novel deep learning model for RE that uses the dependency trees to extract the syntax-based importance scores for the words, serving as a tree representation to introduce syntactic information into the models with greater generalization.
no code implementations • WS 2020 • Amir Pouran Ben Veyseh, Franck Dernoncourt, Thien Huu Nguyen
To address this issue, in this paper, we propose a novel method to incorporate the contextual information in two different levels, i. e., representation level and task-specific (i. e., label) level.
Ranked #5 on Intent Detection on SNIPS
1 code implementation • 5 Nov 2019 • Amir Pouran Ben Veyseh, Franck Dernoncourt, Dejing Dou, Thien Huu Nguyen
In this work, we propose a novel model for DE that simultaneously performs the two tasks in a single framework to benefit from their inter-dependencies.
no code implementations • 7 Jul 2019 • Amir Pouran Ben Veyseh, Thien Huu Nguyen, Dejing Dou
The current deep learning models for relation extraction has mainly exploited this dependency information by guiding their computation along the structures of the dependency trees.
1 code implementation • ACL 2019 • Amir Pouran Ben Veyseh, Thien Huu Nguyen, Dejing Dou
In this work, we introduce a novel graph-based neural network for EFP that can integrate the semantic and syntactic information more effectively.