Papers by Tran Hoang

9 papers
CareerPathKG: Knowledge Graph Integrated Framework for Career Intelligence (2026.eacl-industry)

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Challenge: a new framework for career orientation is needed to address the challenges of the labor market . a recent study found that traditional ML and large language models are brittle when faced with heterogeneous job descriptions .
Approach: They propose a career-path knowledge graph-based recruitment framework to capture occupations, skill requirements and career transitions using standardized taxonomies enriched with job-posting data.
Outcome: The proposed framework captures occupations, skill requirements, and career transitions using standardized taxonomies enriched with job-posting data.
Diffusion Directed Acyclic Transformer for Non-Autoregressive Machine Translation (2025.acl-short)

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Challenge: Non-autoregressive transformers (NATs) often encounter performance challenges due to the multi-modality problem.
Approach: They propose a direct-acyclic transformer (DAT) that captures multiple translation modalities to paths in a Directed Acyclic Graph (DAG) this allows the model to integrate latent variables into the model, which is crucial for DAT to achieve state-of-the-art performance.
Outcome: The proposed model captures multiple translation modalities to paths in a Directed Acyclic Graph (DAG) but the collaboration with the latent variable introduced through the Glancing training is crucial for the model to attain state-of-the-art performance.
PhoMT: A High-Quality and Large-Scale Benchmark Dataset for Vietnamese-English Machine Translation (2021.emnlp-main)

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Challenge: We present a high-quality and large-scale Vietnamese-English parallel dataset . our dataset is 2.9M pairs larger than the benchmark Vietnamese- English corpus .
Approach: They present a large-scale Vietnamese-English parallel dataset with 3.02M sentence pairs . they compare strong neural baselines and well-known automatic translation engines .
Outcome: The proposed dataset is 2.9M pairs larger than the benchmark Vietnamese-English corpus IWSLT15.
Fantastic Questions and Where to Find Them: FairytaleQA – An Authentic Dataset for Narrative Comprehension (2022.acl-long)

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Challenge: Existing QA datasets rarely distinguish fine-grained reading skills, such as the understanding of varying narrative elements.
Approach: They propose to use FairytaleQA to generate 10,580 questions based on 278 children-friendly stories to assess model's fine-grained learning skills.
Outcome: The proposed dataset consists of 10,580 questions derived from 278 children-friendly stories, covering seven types of narrative elements or relations.
VLUE: A New Benchmark and Multi-task Knowledge Transfer Learning for Vietnamese Natural Language Understanding (2024.findings-naacl)

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Challenge: a lack of standard evaluation metrics and benchmarks makes it difficult to identify strengths of Vietnamese NLP models.
Approach: They propose to establish a standardized set of benchmarks for Vietnamese NLU . they propose to evaluate Vietnamese language understanding models using a pre-trained model .
Outcome: The proposed model combines proficiency of a multilingual pre-trained model with Vietnamese linguistic knowledge.
ViHOS: Hate Speech Spans Detection for Vietnamese (2023.eacl-main)

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Challenge: Increasing use of social networking sites can cause problems for human moderators to review tagged comments.
Approach: They present a dataset that contains 26k spans on 11k comments and detailed annotation guidelines . they also provide definitions of hateful and offensive spans in Vietnamese comments .
Outcome: The proposed dataset shows that it is difficult to detect specific types of spans in the dataset . the dataset is the first human-annotated corpus containing 26k spans on 11k comments .
Class based Influence Functions for Error Detection (2023.acl-short)

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Challenge: Influence functions (IFs) are powerful tools for detecting anomalous examples in large scale datasets.
Approach: They propose a method to explain the instability of IFs by leveraging class information to improve the stability of ifs.
Outcome: The proposed method improves performance and stability while incurring no additional computational cost.
SemViQA: A Semantic Question Answering System for Vietnamese Information Fact-Checking (2026.acl-industry)

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Challenge: Existing methods struggle with semantic ambiguity, homonyms, and complex linguistic structures, often trading accuracy for efficiency.
Approach: They propose a Vietnamese fact-checking framework that integrates SER and TVC to achieve 78.97% strict accuracy.
Outcome: The proposed framework achieves state-of-the-art accuracy with 78.97% strict accuracy on ISE-DSC01 and 80.82% on ViWikiFC while maintaining competitive accuracy.
ViHealthBERT: Pre-trained Language Models for Vietnamese in Health Text Mining (2022.lrec-1)

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Challenge: Recent large-scale language models show remarkable achievements in key NLP tasks such as Question Answering and Text Summarization.
Approach: They propose a domain-specific pre-trained Vietnamese language model that outperforms the general domain language models.
Outcome: The proposed model outperforms the general domain language models in Vietnamese datasets while outperforming the general-domain language models.

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