Yidong Wang
23 papers · 2021–2026 · 8 venues · across top CS/AI venues
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Research topics
Machine Learning
(19)
Learning Types Β· Machine Learning
(13)
Artificial Intelligence
(11)
Natural Language Processing
(9)
Deep Learning
(8)
Core AI
(8)
Resources & Methods
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Optimization & Theory
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Computer Vision
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(2)
Keywords
large language model
(6)
semi-supervised learning
(6)
in-context learning
(3)
pseudo labeling
(3)
logit calibration
(2)
natural language understanding
(2)
domain generalization
(2)
consistency regularization
(2)
pre-trained language model
(2)
evaluation benchmark
(2)
benchmark evaluation
(2)
confidence threshold
(2)
out-of-distribution generalization
(2)
expectation maximization
(2)
distribution shift
(2)
data contamination
(2)
noisy label learning
(1)
direct preference optimization
(1)
few-shot learning
(1)
curriculum learning
(1)
Papers
UDA: Unsupervised Debiasing Alignment for Pair-wise LLM-as-a-Judge
AAAI 2026
Masked Autoencoders Are Effective Tokenizers for Diffusion Models
ICML 2025
Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation
ICML 2025
A General Framework for Learning from Weak Supervision
ICML 2024
AutoSurvey: Large Language Models Can Automatically Write Surveys
NeurIPS 2024
Enhancing In-Context Learning via Implicit Demonstration Augmentation
ACL 2024
FreeEval: A Modular Framework for Trustworthy and Efficient Evaluation of Large Language Models
EMNLP 2024
Imprecise Label Learning: A Unified Framework for Learning with Various Imprecise Label Configurations
NeurIPS 2024
KIEval: A Knowledge-grounded Interactive Evaluation Framework for Large Language Models
ACL 2024
PandaLM: An Automatic Evaluation Benchmark for LLM Instruction Tuning Optimization
ICLR 2024
PURE: Aligning LLM via Pluggable Query Reformulation for Enhanced Helpfulness
EMNLP 2024
RAGLAB: A Modular and Research-Oriented Unified Framework for Retrieval-Augmented Generation
EMNLP 2024
Supervised Knowledge Makes Large Language Models Better In-context Learners
ICLR 2024
What Makes a Good Order of Examples in In-Context Learning
ACL 2024
Evaluating Open-QA Evaluation
NeurIPS 2023
FreeMatch: Self-adaptive Thresholding for Semi-supervised Learning
ICLR 2023
GLUE-X: Evaluating Natural Language Understanding Models from an Out-of-Distribution Generalization Perspective
ACL 2023
Out-of-Distribution Generalization in Natural Language Processing: Past, Present, and Future
EMNLP 2023
SoftMatch: Addressing the Quantity-Quality Tradeoff in Semi-supervised Learning
ICLR 2023
Exploiting Unlabeled Data for Target-Oriented Opinion Words Extraction
COLING 2022
Margin Calibration for Long-Tailed Visual
Recognition
ACML 2022
USB: A Unified Semi-supervised Learning Benchmark for Classification
NeurIPS 2022
FlexMatch: Boosting Semi-Supervised Learning with Curriculum Pseudo Labeling
NeurIPS 2021