← Authors

Yu-feng Li

50 papers · 2012–2026 · 9 conferences · across top CS/AI conferences

Achievements

🌈 Renaissance Researcher (7) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (12) πŸƒ Academic Marathon (13) πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (9) πŸ—ΊοΈ Taxonomy Completionist (20) 🀝 Dynamic Duo (19) πŸ‘‘ Triple Crown πŸ† Keyword Champion πŸ† Grand Slam πŸ‘₯ Mega-Team (22) πŸ”¬ Deep Specialist (16) πŸ“ˆ Trend Setter πŸš€ Conference Pioneer πŸ”₯ Unstoppable (8) ❓ The Questioner πŸ—ƒοΈ Keyword Collector (56) πŸ’Ž Century Club (49) ⚑ Prolific Year (5)

Conferences

ICML (12) AAAI (11) IJCAI (11) NIPS (8) EMNLP (3) ICLR (2) CVPR (1) ICCV (1) JMLR (1)

Top co-authors

Zhi Zhou (20) Lan-Zhe Guo (19) Jie-Jing Shao (10) Tong Wei (8) Zhi-Hua Zhou (8) Xiao-wen Yang (7) Lin-Han Jia (6) Ding-Chu Zhang (4) Jiang-Xin Shi (4) Wei-Wei Tu (4)

Keywords

semi-supervised learning (15) domain adaptation (6) weakly supervised learning (4) test-time adaptation (3) label propagation (3) multi-label classification (3) symbolic reasoning (3) model reuse (3) large language model (3) covariate shift (2) deep learning (2) generalization error (2) abductive learning (2) class imbalance (2) active learning (2) multi-label learning (2) multi-instance learning (2) ensemble learning (2) model compression (2) mathematical reasoning (2)

Papers

Step Back to Leap Forward: Self-Backtracking for Symbolic Reasoning and Planning in Language Models AAAI 2026
CARTS: Advancing Neural Theorem Proving with Diversified Tactic Calibration and Bias-Resistant Tree Search ICLR 2025
AutoEvolve: Automatically Evolving Queries for Applicable and Scalable Retrieval-Augmented Generation Benchmarking EMNLP 2025
Neuro-Symbolic Artificial Intelligence: Towards Improving the Reasoning Abilities of Large Language Models IJCAI 2025
Vision-Language Model Selection and Reuse for Downstream Adaptation ICML 2025
Verification Learning: Make Unsupervised Neuro-Symbolic System Feasible ICML 2025
TabFSBench: Tabular Benchmark for Feature Shifts in Open Environments ICML 2025
Fully Test-time Adaptation for Tabular Data AAAI 2025
RAP: Retrieval-Augmented Personalization for Multimodal Large Language Models CVPR 2025
VCSearch: Bridging the Gap Between Well-Defined and Ill-Defined Problems in Mathematical Reasoning EMNLP 2025
EvolveSearch: An Iterative Self-Evolving Search Agent EMNLP 2025
Safe Abductive Learning in the Presence of Inaccurate Rules AAAI 2024
Robust Test-Time Adaptation for Zero-Shot Prompt Tuning AAAI 2024
Analysis for Abductive Learning and Neural-Symbolic Reasoning Shortcuts ICML 2024
DeCoOp: Robust Prompt Tuning with Out-of-Distribution Detection ICML 2024
Long-Tail Learning with Foundation Model: Heavy Fine-Tuning Hurts ICML 2024
Neuro-Symbolic Data Generation for Math Reasoning NIPS 2024
Vision-Language Models are Strong Noisy Label Detectors NIPS 2024
Realistic Evaluation of Semi-supervised Learning Algorithms in Open Environments ICLR 2024
HONGAT: Graph Attention Networks in the Presence of High-Order Neighbors AAAI 2024
LSPAN: Spectrally Localized Augmentation for Graph Consistency Learning IJCAI 2024
Identifying Useful Learnwares for Heterogeneous Label Spaces ICML 2023
ODS: Test-Time Adaptation in the Presence of Open-World Data Shift ICML 2023
How Re-sampling Helps for Long-Tail Learning? NIPS 2023
Bidirectional Adaptation for Robust Semi-Supervised Learning with Inconsistent Data Distributions ICML 2023
Robust Semi-Supervised Learning when Not All Classes have Labels NIPS 2022
LOG: Active Model Adaptation for Label-Efficient OOD Generalization NIPS 2022
Class-Imbalanced Semi-Supervised Learning with Adaptive Thresholding ICML 2022
USB: A Unified Semi-supervised Learning Benchmark for Classification NIPS 2022
Abductive Learning with Ground Knowledge Base IJCAI 2021
STEP: Out-of-Distribution Detection in the Presence of Limited In-Distribution Labeled Data NIPS 2021
Explanation Consistency Training: Facilitating Consistency-Based Semi-Supervised Learning with Interpretability AAAI 2021
NGC: A Unified Framework for Learning With Open-World Noisy Data ICCV 2021
Dash: Semi-Supervised Learning with Dynamic Thresholding ICML 2021
Towards Robust Model Reuse in the Presence of Latent Domains IJCAI 2021
Safe Weakly Supervised Learning IJCAI 2021
Learning from Weak-Label Data: A Deep Forest Expedition AAAI 2020
IWE-Net: Instance Weight Network for Locating Negative Comments and its application to improve Traffic User Experience AAAI 2020
Safe Deep Semi-Supervised Learning for Unseen-Class Unlabeled Data ICML 2020
Semi-Supervised Streaming Learning with Emerging New Labels AAAI 2020
Rapid Performance Gain through Active Model Reuse IJCAI 2019
Partial Label Learning with Unlabeled Data IJCAI 2019
Learning for Tail Label Data: A Label-Specific Feature Approach IJCAI 2019
Towards Automated Semi-Supervised Learning AAAI 2019
Learning Compact Model for Large-Scale Multi-Label Data AAAI 2019
Does Tail Label Help for Large-Scale Multi-Label Learning IJCAI 2018
Lightweight Label Propagation for Large-Scale Network Data IJCAI 2018
Graph Quality Judgement: A Large Margin Expedition IJCAI 2016
Convex and Scalable Weakly Labeled SVMs JMLR 2013
NystrΓΆm Method vs Random Fourier Features: A Theoretical and Empirical Comparison NIPS 2012