Lecturer with PhD, Hanoi University of Science and Technology. At a Vietnamese institution since 2014.
Also published as: Ngô Văn Linh, Linh Ngo Van, Linh Ngo, Van Linh Ngo, Linh Van Ngo, Linh Van
24 accepted papers at the ten venues since 2020: 22 in the official lists and 2 known only from personal pages, shown as +2 and tagged "unofficial" below. 10 accepted before 2026, 14 from 2026. ICLR: 5 submitted, 1 accepted, 4 rejected. Rejected and on record at other venues (public rejections and papers placed in Findings): ACL 1, EMNLP 1.
Links
- Staff page: soict.hust.edu.vn/en/phd-ngo-van-linh.html
- OpenReview profile (~Linh_Ngo_Van1): openreview.net/profile?id=~Linh_Ngo_Van1
- Homepage: users.soict.hust.edu.vn/linhnv
- DBLP: dblp.org/pid/125/3578
- Google Scholar: scholar.google.com/citations?user=tZ78MoQAAAAJ
Co-authors
- Nguyen Thi Ngoc Diep (VNU-UET): 7 papers
- Dinh Viet Sang (HUST): 2 papers
- Nam Le Hai (HUST): 2 papers
- Khoa D. Doan (VinUni): 1 paper
- Than Quang Khoat (HUST): 1 paper
People on this site who share papers with this professor, accepted, rejected or workshop, with their institution today and the number of shared papers; see Researcher collaboration for the whole graph.
Google Scholar
A snapshot of the Google Scholar profile taken on 2026-10-02; it is not updated. Google Scholar counts every publication, not only the ten conferences.
| All | Since 2021 | |
|---|---|---|
| Citations | 1160 | 1091 |
| h-index | 18 | 17 |
| i10-index | 43 | 42 |
Submitted and accepted per year
Accepted papers per year by where the authors are
Each column is one year's accepted papers; grey papers are known only from announcements or personal pages.
Co-authors and topics
- 5.1 co-authors per paper on average, accepted or not (fewest on an accepted paper 3, most on any submission 9), 67 different co-authors over 30 papers.
- 2.4 foreign co-authors per paper on average: co-authors whose affiliation on the paper is outside Vietnam.
- 37 different co-authors are at another university or institution than HUST (25 abroad, 12 in Vietnam).
- The last two figures use the 24 of 30 papers whose list prints an affiliation for each author.
- 5 topics in 4 areas, from the conference's own label on 6 of 30 papers: Deep Learning (3), Online Learning (1), General Machine Learning (1), Optimization (1).
| Topic area | Topic | Papers |
|---|---|---|
| Deep Learning | Large Language Models | 2 |
| Deep Learning | Algorithms | 1 |
| General Machine Learning | Representation Learning | 1 |
| Online Learning | – | 1 |
| Optimization | Learning for Optimization | 1 |
Accepted papers (24)
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ICLR 2026
Align-SAM: Seeking Flatter Minima for Better Cross-Subset Alignment
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NeurIPS 2026unofficial
Conflict-Aware Logit Adapters for Utility-Preserving Anti-Distillation
Unofficial: name and affiliation; in the NeurIPS 2026 list, not yet confirmable on OpenReview.
-
NeurIPS 2026unofficial
Selective Off-Policy Reference Tuning with Plan Guidance
Unofficial: name and affiliation; in the NeurIPS 2026 list, not yet confirmable on OpenReview.
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ICML 2026
$f$-Divergence Self-Play for Tabular Anomaly Detection via Large Language Models
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ICML 2026
HieRD: Hierarchical Relational Distillation for Vision-Language Embedding Models
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ICML 2026
TokenRatio: Principled Token-Level Preference Optimization via Ratio Matching
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CVPR 2026
An Optimal Transport-driven Approach for Cultivating Latent Space in Online Incremental Learning
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ACL 2026
LLM-XTM: Enhancing Cross-Lingual Topic Models with Large Language Models
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ACL 2026
MTA: Multi-Granular Trajectory Alignment for Large Language Model Distillation
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ACL 2026
Octopus: Gated Selective Attention for Memory-Bounded Long-Context Inference in Large Language Models
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ACL 2026
SRA: Span Representation Alignment for Large Language Model Distillation
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ACL 2026
TALAS: Teacher-Anchored Layer Alignment with Adaptive Sharpness-Aware Minimization for Embedding Distillation
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AAAI 2026
GloCTM: Cross-Lingual Topic Modeling via a Global Context Space
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AAAI 2026
MCW-KD: Multi-Cost Wasserstein Knowledge Distillation for Large Language Models
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NeurIPS 2025
Token-Level Self-Play with Importance-Aware Guidance for Large Language Models
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ACL 2025
Mitigating Non-Representative Prototypes and Representation Bias in Few-Shot Continual Relation Extraction
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EMNLP 2025
EMO: Embedding Model Distillation via Intra-Model Relation and Optimal Transport Alignments
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AAAI 2025
Adaptive Prompting for Continual Relation Extraction: A Within-Task Variance Perspective
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AAAI 2025
Few-Shot, No Problem: Descriptive Continual Relation Extraction
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NeurIPS 2024
Mixture of Experts Meets Prompt-Based Continual Learning
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EMNLP 2024
Lifelong Event Detection via Optimal Transport
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EMNLP 2024
Preserving Generalization of Language models in Few-shot Continual Relation Extraction
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AAAI 2024
Continual Relation Extraction via Sequential Multi-Task Learning
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AAAI 2022
Selecting Optimal Context Sentences for Event-Event Relation Extraction
Rejected (6)
Submissions that were not accepted.
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ICLR 2026, rejected
DistillMoE: Multi-Faceted Knowledge Distillation for Cross-Tokenizer Embedding Models
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ICLR 2026, rejected
Reflecting and Linking knowledge: Dynamic Label Structures for Prompt-based Continual Learning
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ICLR 2026, rejected
Token-Regulated Group Relative Policy Optimization for Stable Reinforcement Learning in Large Language Models
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ICLR 2025, rejected
Exploiting Hierarchical Taxonomies in Pretrained Continual Learning
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ACL 2023, rejectedunofficial
Retrieving relevant context to align representations for cross-lingual event detection
Unofficial: listed on their own page; not in the official list yet.
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EMNLP 2023 · Findings, rejected
A Spectral Viewpoint on Continual Relation Extraction
Workshop papers (2)
Workshop papers found on OpenReview and papers placed in Findings, for reference; not counted, except that a Findings paper counts as a main-track rejection (see About).
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ACL 2023 · Findingsunofficial
Retrieving relevant context to align representations for cross-lingual event detection
Unofficial: listed on their own page; not in the official list yet.
-
EMNLP 2023 · Findings
A Spectral Viewpoint on Continual Relation Extraction