Search Results for author: Viet Dac Lai

Found 25 papers, 6 papers with code

Event Detection: Gate Diversity and Syntactic Importance Scores for Graph Convolution Neural Networks

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.

Diversity Event Detection

LUSIFER: Language Universal Space Integration for Enhanced Multilingual Embeddings with Large Language Models

1 code implementation1 Jan 2025 Hieu Man, Nghia Trung Ngo, Viet Dac Lai, Ryan A. Rossi, Franck Dernoncourt, Thien Huu Nguyen

Extensive experimental results demonstrate that LUSIFER significantly enhances the multilingual performance across various embedding tasks, particularly for medium and low-resource languages, without requiring explicit multilingual training data.

SlimLM: An Efficient Small Language Model for On-Device Document Assistance

no code implementations15 Nov 2024 Thang M. Pham, Phat T. Nguyen, Seunghyun Yoon, Viet Dac Lai, Franck Dernoncourt, Trung Bui

While small language models (SLMs) show promises for mobile deployment, their real-world performance and applications on smartphones remains underexplored.

Language Modeling Language Modelling +2

Are Language Model Logits Calibrated?

no code implementations21 Oct 2024 Charles Lovering, Michael Krumdick, Viet Dac Lai, Nilesh Kumar, Varshini Reddy, Rik Koncel-Kedziorski, Chris Tanner

For example, if the context concerns two equally likely options (e. g., heads or tails for a fair coin), the output probabilities should reflect this.

Language Modeling Language Modelling +1

An Analysis of Multilingual FActScore

no code implementations20 Jun 2024 Kim Trong Vu, Michael Krumdick, Varshini Reddy, Franck Dernoncourt, Viet Dac Lai

We also find that the knowledge source plays an important role in the quality of the estimated FActScore.

DocFinQA: A Long-Context Financial Reasoning Dataset

no code implementations12 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.

Retrieval Specificity

Okapi: Instruction-tuned Large Language Models in Multiple Languages with Reinforcement Learning from Human Feedback

2 code implementations29 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.

Boosting Punctuation Restoration with Data Generation and Reinforcement Learning

no code implementations24 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) +4

ChatGPT Beyond English: Towards a Comprehensive Evaluation of Large Language Models in Multilingual Learning

no code implementations12 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.

Multilingual NLP Text Generation +1

Event Extraction: A Survey

no code implementations7 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.

Event Detection Event Extraction +2

Symlink: A New Dataset for Scientific Symbol-Description Linking

no code implementations26 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.

SemEval 2022 Task 12: Symlink- Linking Mathematical Symbols to their Descriptions

no code implementations19 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

Cross-Task Instance Representation Interactions and Label Dependencies for Joint Information Extraction with Graph Convolutional Networks

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.

Relation Extraction Representation Learning +1

Event Detection: Gate Diversity and Syntactic Importance Scoresfor Graph Convolution Neural Networks

no code implementations27 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.

Diversity Event Detection

Extensively Matching for Few-shot Learning Event Detection

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.

Event Detection Few-Shot Learning

Exploiting the Matching Information in the Support Set for Few Shot Event Classification

no code implementations13 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.

Classification Few-Shot Learning +2

Extending Event Detection to New Types with Learning from Keywords

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.

Event Detection Sentence

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