Kezhi Mao
Associate Professor
Works on feature selection and compact interpretable modelling, knowledge-augmented language models for low-resource settings, and machine learning for machine health monitoring.
Kezhi Mao's lab at NTU works on trustworthy & safe ML, large language models and knowledge, QA & retrieval. 25 papers since 2023, 13 at top venues, mostly NeurIPS and Neurocomputing.
At a glance
- papers, 2023–2026
- 7/ year
- at T1 venues
- 52%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom DBLP, 2023–2026
- 3 papers2026 · T1 2 · collecting
- 4 papers2025 · T1 4
- 13 papers2024 · T1 6
- 5 papers2023 · T1 1
T1 venuesOtherVenues: NeurIPS, Neurocomputing, ACL, Expert Systems with Applications, ICLR
Research focuspaper titles that use each topic's words
- Large language models6 papers
- Knowledge, QA & retrieval6 papers
- feature1 paper
- Trustworthy & safe ML0 papers
- low-resource settings0 papers
Paper list
From DBLP.
20263 papers
20254 papers
- NAACL (T1)Beyond the Next Token: Towards Prompt-Robust Zero-Shot Classification via Efficient Multi-Token Prediction (opens in a new tab)
- ICCV (T1)HFD-Teacher: High-Frequency Depth Distillation From Depth Foundation Models for Enhanced Depth Completion (opens in a new tab)
- NAACL (T1)Logit Separability-Driven Samples and Multiple Class-Related Words Selection for Advancing In-Context Learning (opens in a new tab)
- NeurIPS (T1)Restoring Pruned Large Language Models via Lost Component Compensation (opens in a new tab)
202413 papers
- Expert Systems with ApplicationsAdaptive micro- and macro-knowledge incorporation for hierarchical text classification (opens in a new tab)
- IEEE Trans. Neural Networks Learn. Syst.Aligning Correlation Information for Domain Adaptation in Action Recognition (opens in a new tab)
- Findings of NAACLEDEntail: An Entailment-based Few-shot Text Classification with Extensional Definition (opens in a new tab)
- Expert Systems with ApplicationsExplicit and implicit knowledge-enhanced model for event causality identification (opens in a new tab)
- ACL (T1)FreeCtrl: Constructing Control Centers with Feedforward Layers for Learning-Free Controllable Text Generation (opens in a new tab)
- ICRA (T1)GAM-Depth: Self-Supervised Indoor Depth Estimation Leveraging a Gradient-Aware Mask and Semantic Constraints (opens in a new tab)
- ACL (T1)LLMs Learn Task Heuristics from Demonstrations: A Heuristic-Driven Prompting Strategy for Document-Level Event Argument Extraction (opens in a new tab)
- Findings of EACLPromptExplainer: Explaining Language Models through Prompt-based Learning (opens in a new tab)
- NeurIPS (T1)Reinforced Cross-Domain Knowledge Distillation on Time Series Data (opens in a new tab)
- IEEE Trans. Artif. Intell.Reinforced Knowledge Distillation for Time Series Regression (opens in a new tab)
- IEEE Trans. Cybern.Self-Supervised Video Representation Learning by Video Incoherence Detection (opens in a new tab)
- NeurIPS (T1)UniBias: Unveiling and Mitigating LLM Bias through Internal Attention and FFN Manipulation (opens in a new tab)
20235 papers
- NeurocomputingA graph attention network utilizing multi-granular information for emotion-cause pair extraction (opens in a new tab)
- Findings of EMNLPClosed Boundary Learning for Classification Tasks with the Universum Class (opens in a new tab)
- IJCAI (T1)Distilling Universal and Joint Knowledge for Cross-Domain Model Compression on Time Series Data (opens in a new tab)
- NeurocomputingFeature-aware conditional GAN for category text generation (opens in a new tab)
- NeurocomputingKnowledge-based BERT word embedding fine-tuning for emotion recognition (opens in a new tab)
Where alumni went
Alumni are not listed on the lab homepage.
Apply to NTUFall 2027
Not announced yet
Computing and Data Science PhD
- Round
- Main
- Opens
- —
- GRE
- not required
- English
- TOEFL/IELTS
- Fee
- See program page
Not yet confirmed for this intake.
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Data
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