Yibo Wang
32 papers · 2022–2026 · 13 conferences · across top CS/AI conferences
Achievements
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(15)
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(40)
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(5)
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(30)
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(15)
Conferences
NIPS (6)
AAAI (5)
ICML (5)
AACL (2)
ACL (2)
CVPR (2)
EMNLP (2)
ICLR (2)
IJCNLP (2)
ECCV (1)
ICCV (1)
JMLR (1)
NAACL (1)
Top co-authors
Research topics
Keywords
regret bound
(5)
online convex optimization
(4)
large language model
(4)
non-convex optimization
(3)
compositional optimization
(3)
stochastic optimization
(3)
online learning
(3)
variance reduction
(3)
object detection
(2)
multi-label learning
(2)
meta algorithm
(2)
strong convexity
(2)
sample complexity
(2)
feature space
(2)
preference learning
(1)
motion estimation
(1)
representation learning
(1)
text classification
(1)
knowledge representation
(1)
convex optimization
(1)
Papers
Classifier-induced Reciprocal Points for Multi-label Open-set Recognition
AAAI 2026
Why LLMs Hallucinate on Structured Knowledge: A Mechanistic Analysis of Reasoning over Linearized Representations
ACL 2026
TestNUC: Enhancing Test-Time Computing Approaches and Scaling through Neighboring Unlabeled Data Consistency
ACL 2025
Dimension-Free Adaptive Subgradient Methods with Frequent Directions
ICML 2025
Revisiting Projection-Free Online Learning with Time-Varying Constraints
AAAI 2025
Towards Unbiased Information Extraction and Adaptation in Cross-Domain Recommendation
AAAI 2025
KGARevion: An AI Agent for Knowledge-Intensive Biomedical QA
ICLR 2025
Universal Online Convex Optimization Meets Second-order Bounds
JMLR 2025
Joint RGB-Spectral Decomposition Model Guided Image Enhancement in Mobile Photography
ECCV 2024
LLMs Assist NLP Researchers: Critique Paper (Meta-)Reviewing
EMNLP 2024
DA3: A Distribution-Aware Adversarial Attack against Language Models
EMNLP 2024
Multi-Label Open Set Recognition
NIPS 2024
Adaptive Variance Reduction for Stochastic Optimization under Weaker Assumptions
NIPS 2024
Universal Online Convex Optimization with $1$ Projection per Round
NIPS 2024
Online Composite Optimization Between Stochastic and Adversarial Environments
NIPS 2024
Advancing Tool-Augmented Large Language Models: Integrating Insights from Errors in Inference Trees
NIPS 2024
Non-stationary Projection-Free Online Learning with Dynamic and Adaptive Regret Guarantees
AAAI 2024
DetDiffusion: Synergizing Generative and Perceptive Models for Enhanced Data Generation and Perception
CVPR 2024
GeoDiffusion: Text-Prompted Geometric Control for Object Detection Data Generation
ICLR 2024
Projection-Free Variance Reduction Methods for Stochastic Constrained Multi-Level Compositional Optimization
ICML 2024
High-Probability Bound for Non-Smooth Non-Convex Stochastic Optimization with Heavy Tails
ICML 2024
Small-loss Adaptive Regret for Online Convex Optimization
ICML 2024
kNN-ICL: Compositional Task-Oriented Parsing Generalization with Nearest Neighbor In-Context Learning
NAACL 2024
Named Entity Recognition via Machine Reading Comprehension: A Multi-Task Learning Approach
AACL 2023
Localize, Retrieve and Fuse: A Generalized Framework for Free-Form Question Answering over Tables
AACL 2023
Aperture Diffraction for Compact Snapshot Spectral Imaging
ICCV 2023
Named Entity Recognition via Machine Reading Comprehension: A Multi-Task Learning Approach
IJCNLP 2023
Distributed Projection-Free Online Learning for Smooth and Convex Losses
AAAI 2023
Localize, Retrieve and Fuse: A Generalized Framework for Free-Form Question Answering over Tables
IJCNLP 2023
Explore Spatio-Temporal Aggregation for Insubstantial Object Detection: Benchmark Dataset and Baseline
CVPR 2022
Optimal Algorithms for Stochastic Multi-Level Compositional Optimization
ICML 2022
Multi-block-Single-probe Variance Reduced Estimator for Coupled Compositional Optimization
NIPS 2022