Lan-Zhe Guo

Orcid: 0000-0001-8965-1288

According to our database1, Lan-Zhe Guo authored at least 87 papers between 2018 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
Roles with Rails: Contract-Preserving Role Evolution in Multi-Agent Structured Reasoning.
CoRR, May, 2026

On the Learnability of Test-Time Adaptation: A Recovery Complexity Perspective.
CoRR, May, 2026

Stabilizing Recurrent Dynamics for Test-Time Scalable Latent Reasoning in Looped Language Models.
CoRR, May, 2026

TRACE: Distilling Where It Matters via Token-Routed Self On-Policy Alignment.
CoRR, May, 2026

VT-Bench: A Unified Benchmark for Visual-Tabular Multi-Modal Learning.
CoRR, May, 2026

Revisiting the Travel Planning Capabilities of Large Language Models.
CoRR, May, 2026

Programmatic Context Augmentation for LLM-based Symbolic Regression.
CoRR, May, 2026

Lifting Traces to Logic: Programmatic Skill Induction with Neuro-Symbolic Learning for Long-Horizon Agentic Tasks.
CoRR, May, 2026

LAST: Leveraging Tools as Hints to Enhance Spatial Reasoning for Multimodal Large Language Models.
CoRR, April, 2026

Aligning Progress and Feasibility: A Neuro-Symbolic Dual Memory Framework for Long-Horizon LLM Agents.
CoRR, April, 2026

Thinking with Tables: Enhancing Multi-Modal Tabular Understanding via Neuro-Symbolic Reasoning.
CoRR, March, 2026

A Progressive Visual-Logic-Aligned Framework for Ride-Hailing Adjudication.
CoRR, March, 2026

NeSy-Route: A Neuro-Symbolic Benchmark for Constrained Route Planning in Remote Sensing.
CoRR, March, 2026

Hindsight Credit Assignment for Long-Horizon LLM Agents.
CoRR, March, 2026

MapTab: Can MLLMs Master Constrained Route Planning?
CoRR, February, 2026

Learning contrastive feature representations for facial action unit detection.
Pattern Recognit., 2026

Multi-field Balance-aware Calibration of Predictions in Online Advertising.
Proceedings of the ACM Web Conference 2026, 2026

Aligning Agents via Planning: A Benchmark for Trajectory-Level Reward Modeling.
Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2026

Step Back to Leap Forward: Self-Backtracking for Symbolic Reasoning and Planning in Language Models.
Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025
Pianist Transformer: Towards Expressive Piano Performance Rendering via Scalable Self-Supervised Pre-Training.
CoRR, December, 2025

Bi-CoG: Bi-Consistency-Guided Self-Training for Vision-Language Models.
CoRR, October, 2025

FormalML: A Benchmark for Evaluating Formal Subgoal Completion in Machine Learning Theory.
CoRR, October, 2025

Robust semi-supervised learning in open environments.
Frontiers Comput. Sci., August, 2025

Beyond Single: A Data Selection Principle for LLM Alignment via Fine-Grained Preference Signals.
CoRR, August, 2025

When Is Prior Knowledge Helpful? Exploring the Evaluation and Selection of Unsupervised Pretext Tasks from a Neuro-Symbolic Perspective.
CoRR, August, 2025

Automated Text-to-Table for Reasoning-Intensive Table QA: Pipeline Design and Benchmarking Insights.
CoRR, May, 2025

NeSyGeo: A Neuro-Symbolic Framework for Multimodal Geometric Reasoning Data Generation.
CoRR, May, 2025

Realistic Evaluation of TabPFN v2 in Open Environments.
CoRR, May, 2025

Unlabeled Data or Pre-trained Model: Rethinking Semi-Supervised Learning and Pretrain-Finetuning.
CoRR, May, 2025

Micro Text Classification Based on Balanced Positive-Unlabeled Learning.
CoRR, March, 2025

A Smooth Transition Between Induction and Deduction: Fast Abductive Learning Based on Probabilistic Symbol Perception.
CoRR, February, 2025

LawGPT: Knowledge-Guided Data Generation and Its Application to Legal LLM.
CoRR, February, 2025

Step Back to Leap Forward: Self-Backtracking for Boosting Reasoning of Language Models.
CoRR, February, 2025

Bridging Internal Probability and Self-Consistency for Effective and Efficient LLM Reasoning.
CoRR, February, 2025

Contrast-Aware Calibration for Fine-Tuned CLIP: Leveraging Image-Text Alignment.
CoRR, January, 2025

TabFSBench: Tabular Benchmark for Feature Shifts in Open Environment.
CoRR, January, 2025

Pre-Trained Vision-Language Model Selection and Reuse for Downstream Tasks.
CoRR, January, 2025

A Theoretical Study on Bridging Internal Probability and Self-Consistency for LLM Reasoning.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

CGI: Identifying Conditional Generative Models with Example Images.
Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, 2025

D3: Diversity, Difficulty, and Dependability-Aware Data Selection for Sample-Efficient LLM Instruction Tuning.
Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, 2025

Neuro-Symbolic Artificial Intelligence: Towards Improving the Reasoning Abilities of Large Language Models.
Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, 2025

Curriculum Abductive Learning for Mitigating Reasoning Shortcuts.
Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, 2025

Breaking the Self-Evaluation Barrier: Reinforced Neuro-Symbolic Planning with Large Language Models.
Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, 2025

BMIP: Bi-directional Modality Interaction Prompt Learning for VLM.
Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, 2025

Fully Test-Time Adaptation for Feature Decrement in Tabular Data.
Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, 2025

Vision-Language Model Selection and Reuse for Downstream Adaptation.
Proceedings of the Forty-second International Conference on Machine Learning, 2025

Verification Learning: Make Unsupervised Neuro-Symbolic System Feasible.
Proceedings of the Forty-second International Conference on Machine Learning, 2025

TabFSBench: Tabular Benchmark for Feature Shifts in Open Environments.
Proceedings of the Forty-second International Conference on Machine Learning, 2025

VCSearch: Bridging the Gap Between Well-Defined and Ill-Defined Problems in Mathematical Reasoning.
Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 2025

Fully Test-time Adaptation for Tabular Data.
Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024
Transfer and share: semi-supervised learning from long-tailed data.
Mach. Learn., April, 2024

Open-set learning under covariate shift.
Mach. Learn., April, 2024

Interactive Reweighting for Mitigating Label Quality Issues.
IEEE Trans. Vis. Comput. Graph., March, 2024

Robust Semi-Supervised Learning in Open Environments.
CoRR, 2024

ChinaTravel: A Real-World Benchmark for Language Agents in Chinese Travel Planning.
CoRR, 2024

You Only Submit One Image to Find the Most Suitable Generative Model.
CoRR, 2024

Enabling Small Models for Zero-Shot Classification through Model Label Learning.
CoRR, 2024

Robustness Assessment of Mathematical Reasoning in the Presence of Missing and Contradictory Conditions.
CoRR, 2024

LawGPT: A Chinese Legal Knowledge-Enhanced Large Language Model.
CoRR, 2024

LAMDA-SSL: a comprehensive semi-supervised learning toolkit.
Sci. China Inf. Sci., 2024

Offline Imitation Learning with Model-based Reverse Augmentation.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

DeCoOp: Robust Prompt Tuning with Out-of-Distribution Detection.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Realistic Evaluation of Semi-supervised Learning Algorithms in Open Environments.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
Investigating the Limitation of CLIP Models: The Worst-Performing Categories.
CoRR, 2023

Bidirectional Adaptation for Robust Semi-Supervised Learning with Inconsistent Data Distributions.
Proceedings of the International Conference on Machine Learning, 2023

Identifying Useful Learnwares for Heterogeneous Label Spaces.
Proceedings of the International Conference on Machine Learning, 2023

ODS: Test-Time Adaptation in the Presence of Open-World Data Shift.
Proceedings of the International Conference on Machine Learning, 2023

2022
USB: A Unified Semi-supervised Learning Benchmark.
CoRR, 2022

LAMDA-SSL: Semi-Supervised Learning in Python.
CoRR, 2022

USB: A Unified Semi-supervised Learning Benchmark for Classification.
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.
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.
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.
Proceedings of the International Conference on Machine Learning, 2022

2021
Interactive Graph Construction for Graph-Based Semi-Supervised Learning.
IEEE Trans. Vis. Comput. Graph., 2021

Towards Safe Weakly Supervised Learning.
IEEE Trans. Pattern Anal. Mach. Intell., 2021

Learning from group supervision: the impact of supervision deficiency on multi-label learning.
Sci. China Inf. Sci., 2021

STEP: Out-of-Distribution Detection in the Presence of Limited In-Distribution Labeled Data.
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.
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.
CoRR, 2020

RECORD: Resource Constrained Semi-Supervised Learning under Distribution Shift.
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.
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.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Reliable Weakly Supervised Learning: Maximize Gain and Maintain Safeness.
CoRR, 2019

Robust Semi-supervised Representation Learning for Graph-Structured Data.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2019

2018
Learning safe multi-label prediction for weakly labeled data.
Mach. Learn., 2018

Large Margin Graph Construction for Semi-Supervised Learning.
Proceedings of the 2018 IEEE International Conference on Data Mining Workshops, 2018

A General Formulation for Safely Exploiting Weakly Supervised Data.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018


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