Yong Lin
16 papers · 2022–2025 · 8 venues · across top CS/AI venues
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Achievements
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🌉 Interdisciplinary Bridge · Silver 🗺️ Taxonomy Completionist (33) 🌍 Conference Polyglot · Silver 🐣 Hot Topic Early Bird 🤝 Dynamic Duo (13)
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Prolific Year · Productive
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The Questioner
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Century Club · Bronze
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Research topics
Machine Learning
(14)
Optimization & Theory
(10)
Artificial Intelligence
(7)
Application Areas
(7)
Core AI
(6)
Learning Types · Machine Learning
(5)
Deep Learning
(4)
Learning Types · Deep Learning
(4)
Reinforcement Learning
(3)
Core Methods
(3)
Methods
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Natural Language Processing
(2)
Resources & Methods
(2)
Bayesian & Probabilistic
(1)
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Keywords
out-of-distribution generalization
(4)
reinforcement learning from human feedback
(3)
large language model
(3)
distribution shift
(3)
bilevel optimization
(2)
domain generalization
(2)
sample reweighting
(2)
reward model
(2)
uncertainty estimation
(2)
invariant risk minimization
(2)
active learning
(2)
spurious correlation
(2)
preference learning
(1)
coreset selection
(1)
model robustness
(1)
uncertainty quantification
(1)
model selection
(1)
continual learning
(1)
feature selection
(1)
policy learning
(1)
Papers
Optimal Sample Selection Through Uncertainty Estimation and Its Application in Deep Learning
JMLR 2025
Active Prompting with Chain-of-Thought for Large Language Models
ACL 2024
Arithmetic Control of LLMs for Diverse User Preferences: Directional Preference Alignment with Multi-Objective Rewards
ACL 2024
A Sober Look at the Robustness of CLIPs to Spurious Features
NeurIPS 2024
Mitigating the Alignment Tax of RLHF
EMNLP 2024
On the Limited Generalization Capability of the Implicit Reward Model Induced by Direct Preference Optimization
EMNLP 2024
Regularizing Hidden States Enables Learning Generalizable Reward Model for LLMs
NeurIPS 2024
R-Tuning: Instructing Large Language Models to Say ‘I Don’t Know’
NAACL 2024
The Instinctive Bias: Spurious Images lead to Illusion in MLLMs
EMNLP 2024
ID and OOD Performance Are Sometimes Inversely Correlated on Real-world Datasets
NeurIPS 2023
Stable Learning via Sparse Variable Independence
AAAI 2023
Bayesian Invariant Risk Minimization
CVPR 2022
Model Agnostic Sample Reweighting for Out-of-Distribution Learning
ICML 2022
Probabilistic Bilevel Coreset Selection
ICML 2022
Sparse Invariant Risk Minimization
ICML 2022
ZIN: When and How to Learn Invariance Without Environment Partition?
NeurIPS 2022