Yonggang Zhang
41 papers · 2020–2026 · 7 conferences · across top CS/AI conferences
Achievements
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π Conference Polyglot (7) π Academic Marathon (5) π Interdisciplinary Bridge π§ Keyword Pioneer π Cross-Pollinator (12)
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Cross-Pollinator
(12)
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Renaissance Researcher
(6)
πΊοΈ
Taxonomy Completionist
(57)
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Grand Slam
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Topic Evolution
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Triple Crown
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Dynamic Duo
(20)
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Keyword Champion
(2)
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Century Club
(37)
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Trend Setter
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Unstoppable
(6)
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Keyword Collector
(121)
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Prolific Year
(8)
Conferences
ICLR (12)
NIPS (11)
ICML (6)
AAAI (4)
ACL (4)
CVPR (3)
EMNLP (1)
Top co-authors
Keywords
federated learning
(4)
data heterogeneity
(3)
causal inference
(3)
domain generalization
(3)
out-of-distribution detection
(3)
feature perturbation
(2)
representation learning
(2)
large language model
(2)
attention head
(2)
representation engineering
(2)
adversarial example
(2)
transfer learning
(2)
multi-hop reasoning
(2)
feature distillation
(2)
black-box attack
(2)
out-of-distribution generalization
(2)
distribution shift
(2)
knowledge distillation
(2)
invariant learning
(2)
graph classification
(1)
Papers
Bridging the Language Gap: Uncovering and Aligning Shared Circuits for Multi-Hop Reasoning in Multilingual LLMs
AAAI 2026
Generating then Refining for Reliable Knowledge Base Question Answering
ACL 2026
Trust Within? Seek Beyond? Knowledge Boundary Aware Policy Optimization for Agentic Search
ACL 2026
Frequency-Dependent Scheduled SchrΓΆdinger Bridge for Underwater Acoustic Signal Denoising
AAAI 2026
MOS: Model Synergy for Test-Time Adaptation on LiDAR-Based 3D Object Detection
ICLR 2025
Leveraging Submodule Linearity Enhances Task Arithmetic Performance in LLMs
ICLR 2025
Component-Level Segmentation for Oracle Bone Inscription Decipherment
AAAI 2025
Hot-pluggable Federated Learning: Bridging General and Personalized FL via Dynamic Selection
ICLR 2025
Interpret and Improve In-Context Learning via the Lens of Input-Label Mappings
ACL 2025
Tracing and Dissecting How LLMs Recall Factual Knowledge for Real World Questions
ACL 2025
Enhancing Target-unspecific Tasks through a Features Matrix
ICML 2025
ConjNorm: Tractable Density Estimation for Out-of-Distribution Detection
ICLR 2024
Robust Training of Federated Models with Extremely Label Deficiency
ICLR 2024
FedImpro: Measuring and Improving Client Update in Federated Learning
ICLR 2024
NoiseDiffusion: Correcting Noise for Image Interpolation with Diffusion Models beyond Spherical Linear Interpolation
ICLR 2024
Out-of-Distribution Detection with Negative Prompts
ICLR 2024
Enhancing One-Shot Federated Learning Through Data and Ensemble Co-Boosting
ICLR 2024
Enhancing Multiple Dimensions of Trustworthiness in LLMs via Sparse Activation Control
NIPS 2024
FuseFL: One-Shot Federated Learning through the Lens of Causality with Progressive Model Fusion
NIPS 2024
Learning to Shape In-distribution Feature Space for Out-of-distribution Detection
NIPS 2024
Federated Learning with Extremely Noisy Clients via Negative Distillation
AAAI 2024
Interpreting and Improving Large Language Models in Arithmetic Calculation
ICML 2024
From Yes-Men to Truth-Tellers: Addressing Sycophancy in Large Language Models with Pinpoint Tuning
ICML 2024
FedFed: Feature Distillation against Data Heterogeneity in Federated Learning
NIPS 2023
SODA: Robust Training of Test-Time Data Adaptors
NIPS 2023
Learning to Augment Distributions for Out-of-distribution Detection
NIPS 2023
Invariant Learning via Probability of Sufficient and Necessary Causes
NIPS 2023
Hard Sample Matters a Lot in Zero-Shot Quantization
CVPR 2023
Continual Named Entity Recognition without Catastrophic Forgetting
EMNLP 2023
Pareto Invariant Risk Minimization: Towards Mitigating the Optimization Dilemma in Out-of-Distribution Generalization
ICLR 2023
Moderately Distributional Exploration for Domain Generalization
ICML 2023
Understanding and Improving Graph Injection Attack by Promoting Unnoticeability
ICLR 2022
Virtual Homogeneity Learning: Defending against Data Heterogeneity in Federated Learning
ICML 2022
Watermarking for Out-of-distribution Detection
NIPS 2022
Adversarial Robustness Through the Lens of Causality
ICLR 2022
Meta Convolutional Neural Networks for Single Domain Generalization
CVPR 2022
Prompt Distribution Learning
CVPR 2022
Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs
NIPS 2022
Towards Lightweight Black-Box Attack Against Deep Neural Networks
NIPS 2022
Class-Disentanglement and Applications in Adversarial Detection and Defense
NIPS 2021
Dual-Path Distillation: A Unified Framework to Improve Black-Box Attacks
ICML 2020