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 • EMNLP 2020 • Viet Dac Lai, Tuan Ngo Nguyen, Thien Huu Nguyen
Recent studies on event detection (ED) have shown that the syntactic dependency graph can be employed in graph convolution neural networks (GCN) to achieve state-of-the-art performance.
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 • 12 Jan 2024 • Varshini Reddy, Rik Koncel-Kedziorski, Viet Dac Lai, Michael Krumdick, Charles Lovering, Chris Tanner
For large language models (LLMs) to be effective in the financial domain -- where each decision can have a significant impact -- it is necessary to investigate realistic tasks and data.
no code implementations • 17 Sep 2023 • Thuat Nguyen, Chien Van Nguyen, Viet Dac Lai, Hieu Man, Nghia Trung Ngo, Franck Dernoncourt, Ryan A. Rossi, Thien Huu Nguyen
However, when it comes to training datasets for these LLMs, especially the recent state-of-the-art models, they are often not fully disclosed.
2 code implementations • 29 Jul 2023 • Viet Dac Lai, Chien Van Nguyen, Nghia Trung Ngo, Thuat Nguyen, Franck Dernoncourt, Ryan A. Rossi, Thien Huu Nguyen
Okapi introduces instruction and response-ranked data in 26 diverse languages to facilitate the experiments and development of future multilingual LLM research.
no code implementations • 24 Jul 2023 • Viet Dac Lai, Abel Salinas, Hao Tan, Trung Bui, Quan Tran, Seunghyun Yoon, Hanieh Deilamsalehy, Franck Dernoncourt, Thien Huu Nguyen
Punctuation restoration is an important task in automatic speech recognition (ASR) which aim to restore the syntactic structure of generated ASR texts to improve readability.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +3
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 • 7 Oct 2022 • Viet Dac Lai
In this report, we provide the task definition, the evaluation method, as well as the benchmark datasets and a taxonomy of methodologies for event extraction.
no code implementations • 26 Apr 2022 • Viet Dac Lai, Amir Pouran Ben Veyseh, Franck Dernoncourt, Thien Huu Nguyen
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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 • NAACL 2021 • Minh Van Nguyen, Viet Dac Lai, Thien Huu Nguyen
Existing works on information extraction (IE) have mainly solved the four main tasks separately (entity mention recognition, relation extraction, event trigger detection, and argument extraction), thus failing to benefit from inter-dependencies between tasks.
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 • 27 Oct 2020 • Viet Dac Lai, Tuan Ngo Nguyen, Thien Huu Nguyen
Recent studies on event detection (ED) haveshown that the syntactic dependency graph canbe employed in graph convolution neural net-works (GCN) to achieve state-of-the-art per-formance.
1 code implementation • WS 2020 • Viet Dac Lai, Franck Dernoncourt, Thien Huu Nguyen
In this work, weformulate event detection as a few-shot learn-ing problem to enable to extend event detec-tion to new event types.
no code implementations • 13 Feb 2020 • Viet Dac Lai, Franck Dernoncourt, Thien Huu Nguyen
The existing event classification (EC) work primarily focuseson the traditional supervised learning setting in which models are unableto extract event mentions of new/unseen event types.
no code implementations • WS 2019 • Viet Dac Lai, Thien Huu Nguyen
We introduce a novel feature-based attention mechanism for convolutional neural networks for event detection in the new formulation.