Lan-Zhe Guo

Orcid: 0000-0001-8965-1288

According to our database¹, Lan-Zhe Guo authored at least 59 papers between 2018 and 2025.

Collaborative distances:

Dijkstra number² of five.
Erdős number³ of four.

Timeline

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In proceedings

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On csauthors.net:

Bibliography

2025

Robust semi-supervised learning in open environments.

[BibT_eX]

[DOI]

Frontiers Comput. Sci., August, 2025

Neuro-Symbolic Artificial Intelligence: Towards Improving the Reasoning Abilities of Large Language Models.

[BibT_eX]

[DOI]

CoRR, August, 2025

Beyond Single: A Data Selection Principle for LLM Alignment via Fine-Grained Preference Signals.

[BibT_eX]

[DOI]

CoRR, August, 2025

When Is Prior Knowledge Helpful? Exploring the Evaluation and Selection of Unsupervised Pretext Tasks from a Neuro-Symbolic Perspective.

[BibT_eX]

[DOI]

CoRR, August, 2025

Automated Text-to-Table for Reasoning-Intensive Table QA: Pipeline Design and Benchmarking Insights.

[BibT_eX]

[DOI]

CoRR, May, 2025

NeSyGeo: A Neuro-Symbolic Framework for Multimodal Geometric Reasoning Data Generation.

[BibT_eX]

[DOI]

CoRR, May, 2025

Realistic Evaluation of TabPFN v2 in Open Environments.

[BibT_eX]

[DOI]

CoRR, May, 2025

Unlabeled Data or Pre-trained Model: Rethinking Semi-Supervised Learning and Pretrain-Finetuning.

[BibT_eX]

[DOI]

CoRR, May, 2025

Micro Text Classification Based on Balanced Positive-Unlabeled Learning.

[BibT_eX]

[DOI]

CoRR, March, 2025

Verification Learning: Make Unsupervised Neuro-Symbolic System Feasible.

[BibT_eX]

[DOI]

CoRR, March, 2025

D3: Diversity, Difficulty, and Dependability-Aware Data Selection for Sample-Efficient LLM Instruction Tuning.

[BibT_eX]

[DOI]

CoRR, March, 2025

A Smooth Transition Between Induction and Deduction: Fast Abductive Learning Based on Probabilistic Symbol Perception.

[BibT_eX]

[DOI]

CoRR, February, 2025

LawGPT: Knowledge-Guided Data Generation and Its Application to Legal LLM.

[BibT_eX]

[DOI]

CoRR, February, 2025

Step Back to Leap Forward: Self-Backtracking for Boosting Reasoning of Language Models.

[BibT_eX]

[DOI]

CoRR, February, 2025

Bridging Internal Probability and Self-Consistency for Effective and Efficient LLM Reasoning.

[BibT_eX]

[DOI]

CoRR, February, 2025

Contrast-Aware Calibration for Fine-Tuned CLIP: Leveraging Image-Text Alignment.

[BibT_eX]

[DOI]

CoRR, January, 2025

TabFSBench: Tabular Benchmark for Feature Shifts in Open Environment.

[BibT_eX]

[DOI]

CoRR, January, 2025

Pre-Trained Vision-Language Model Selection and Reuse for Downstream Tasks.

[BibT_eX]

[DOI]

CoRR, January, 2025

CGI: Identifying Conditional Generative Models with Example Images.

[BibT_eX]

[DOI]

CoRR, January, 2025

BMIP: Bi-directional Modality Interaction Prompt Learning for VLM.

[BibT_eX]

[DOI]

CoRR, January, 2025

Fully Test-time Adaptation for Tabular Data.

[BibT_eX]

[DOI]

Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024

Transfer and share: semi-supervised learning from long-tailed data.

[BibT_eX]

[DOI]

Mach. Learn., April, 2024

Open-set learning under covariate shift.

[BibT_eX]

[DOI]

Jie-Jing Shao

Xiaowen Yang

Lan-Zhe Guo

Mach. Learn., April, 2024

Interactive Reweighting for Mitigating Label Quality Issues.

[BibT_eX]

[DOI]

IEEE Trans. Vis. Comput. Graph., March, 2024

Robust Semi-Supervised Learning in Open Environments.

[BibT_eX]

[DOI]

CoRR, 2024

ChinaTravel: A Real-World Benchmark for Language Agents in Chinese Travel Planning.

[BibT_eX]

[DOI]

CoRR, 2024

You Only Submit One Image to Find the Most Suitable Generative Model.

[BibT_eX]

[DOI]

CoRR, 2024

Enabling Small Models for Zero-Shot Classification through Model Label Learning.

[BibT_eX]

[DOI]

CoRR, 2024

Robustness Assessment of Mathematical Reasoning in the Presence of Missing and Contradictory Conditions.

[BibT_eX]

[DOI]

CoRR, 2024

LawGPT: A Chinese Legal Knowledge-Enhanced Large Language Model.

[BibT_eX]

[DOI]

CoRR, 2024

DeCoOp: Robust Prompt Tuning with Out-of-Distribution Detection.

[BibT_eX]

[DOI]

CoRR, 2024

LAMDA-SSL: a comprehensive semi-supervised learning toolkit.

[BibT_eX]

[DOI]

Sci. China Inf. Sci., 2024

Offline Imitation Learning with Model-based Reverse Augmentation.

[BibT_eX]

[DOI]

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

DeCoOp: Robust Prompt Tuning with Out-of-Distribution Detection.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Realistic Evaluation of Semi-supervised Learning Algorithms in Open Environments.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Investigating the Limitation of CLIP Models: The Worst-Performing Categories.

[BibT_eX]

[DOI]

CoRR, 2023

Bidirectional Adaptation for Robust Semi-Supervised Learning with Inconsistent Data Distributions.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Identifying Useful Learnwares for Heterogeneous Label Spaces.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

ODS: Test-Time Adaptation in the Presence of Open-World Data Shift.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

2022

USB: A Unified Semi-supervised Learning Benchmark.

[BibT_eX]

[DOI]

CoRR, 2022

LAMDA-SSL: Semi-Supervised Learning in Python.

[BibT_eX]

[DOI]

CoRR, 2022

USB: A Unified Semi-supervised Learning Benchmark for Classification.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

LOG: Active Model Adaptation for Label-Efficient OOD Generalization.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Robust Semi-Supervised Learning when Not All Classes have Labels.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Class-Imbalanced Semi-Supervised Learning with Adaptive Thresholding.

[BibT_eX]

[DOI]

Lan-Zhe Guo

Yufeng Li

Proceedings of the International Conference on Machine Learning, 2022

2021

Interactive Graph Construction for Graph-Based Semi-Supervised Learning.

[BibT_eX]

[DOI]

IEEE Trans. Vis. Comput. Graph., 2021

Towards Safe Weakly Supervised Learning.

[BibT_eX]

[DOI]

Yufeng Li

Lan-Zhe Guo

Zhi-Hua Zhou

IEEE Trans. Pattern Anal. Mach. Intell., 2021

Learning from group supervision: the impact of supervision deficiency on multi-label learning.

[BibT_eX]

[DOI]

Miao Xu

Lan-Zhe Guo

Sci. China Inf. Sci., 2021

STEP: Out-of-Distribution Detection in the Presence of Limited In-Distribution Labeled Data.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Learning from Imbalanced and Incomplete Supervision with Its Application to Ride-Sharing Liability Judgment.

[BibT_eX]

[DOI]

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

2020

Weakly Supervised Learning Meets Ride-Sharing User Experience Enhancement.

[BibT_eX]

[DOI]

CoRR, 2020

RECORD: Resource Constrained Semi-Supervised Learning under Distribution Shift.

[BibT_eX]

[DOI]

Lan-Zhe Guo

Zhi Zhou

Yufeng Li

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Safe Deep Semi-Supervised Learning for Unseen-Class Unlabeled Data.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

IWE-Net: Instance Weight Network for Locating Negative Comments and its application to improve Traffic User Experience.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Reliable Weakly Supervised Learning: Maximize Gain and Maintain Safeness.

[BibT_eX]

[DOI]

CoRR, 2019

Robust Semi-supervised Representation Learning for Graph-Structured Data.

[BibT_eX]

[DOI]

Lan-Zhe Guo

Tao Han

Yufeng Li

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2019

2018

Learning safe multi-label prediction for weakly labeled data.

[BibT_eX]

[DOI]

Mach. Learn., 2018

Large Margin Graph Construction for Semi-Supervised Learning.

[BibT_eX]

[DOI]

Lan-Zhe Guo

Shao-Bo Wang

Yufeng Li

Proceedings of the 2018 IEEE International Conference on Data Mining Workshops, 2018

A General Formulation for Safely Exploiting Weakly Supervised Data.

[BibT_eX]

[DOI]

Lan-Zhe Guo

Yufeng Li

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

Lan-Zhe Guo

Timeline

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On csauthors.net:

Bibliography

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