Yonggang Zhang

Bridging the Language Gap: Uncovering and Aligning Shared Circuits for Multi-Hop Reasoning in Multilingual LLMs AAAI 2026 Decision Boundary-aware Generation for Long-tailed Learning CVPR 2026 FedRG: Unleashing the Representation Geometry for Federated Learning with Noisy Clients CVPR 2026 Frequency-Dependent Scheduled Schrödinger Bridge for Underwater Acoustic Signal Denoising 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 Component-Level Segmentation for Oracle Bone Inscription Decipherment AAAI 2025 Enhancing Target-unspecific Tasks through a Features Matrix ICML 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 Leveraging Submodule Linearity Enhances Task Arithmetic Performance in LLMs ICLR 2025 MOS: Model Synergy for Test-Time Adaptation on LiDAR-Based 3D Object Detection ICLR 2025 Tracing and Dissecting How LLMs Recall Factual Knowledge for Real World Questions ACL 2025 ConjNorm: Tractable Density Estimation for Out-of-Distribution Detection ICLR 2024 Enhancing Multiple Dimensions of Trustworthiness in LLMs via Sparse Activation Control NeurIPS 2024 Enhancing One-Shot Federated Learning Through Data and Ensemble Co-Boosting ICLR 2024 Federated Learning with Extremely Noisy Clients via Negative Distillation AAAI 2024 FedImpro: Measuring and Improving Client Update in Federated Learning ICLR 2024 From Yes-Men to Truth-Tellers: Addressing Sycophancy in Large Language Models with Pinpoint Tuning ICML 2024 FuseFL: One-Shot Federated Learning through the Lens of Causality with Progressive Model Fusion NeurIPS 2024 Interpreting and Improving Large Language Models in Arithmetic Calculation ICML 2024 Learning to Shape In-distribution Feature Space for Out-of-distribution Detection NeurIPS 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 Robust Training of Federated Models with Extremely Label Deficiency ICLR 2024 Continual Named Entity Recognition without Catastrophic Forgetting EMNLP 2023 FedFed: Feature Distillation against Data Heterogeneity in Federated Learning NeurIPS 2023 Hard Sample Matters a Lot in Zero-Shot Quantization CVPR 2023 Invariant Learning via Probability of Sufficient and Necessary Causes NeurIPS 2023 Learning to Augment Distributions for Out-of-distribution Detection NeurIPS 2023 Moderately Distributional Exploration for Domain Generalization ICML 2023 Pareto Invariant Risk Minimization: Towards Mitigating the Optimization Dilemma in Out-of-Distribution Generalization ICLR 2023 SODA: Robust Training of Test-Time Data Adaptors NeurIPS 2023 Adversarial Robustness Through the Lens of Causality ICLR 2022 Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs NeurIPS 2022 Meta Convolutional Neural Networks for Single Domain Generalization CVPR 2022 Prompt Distribution Learning CVPR 2022 Towards Lightweight Black-Box Attack Against Deep Neural Networks NeurIPS 2022 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 NeurIPS 2022 Class-Disentanglement and Applications in Adversarial Detection and Defense NeurIPS 2021 Dual-Path Distillation: A Unified Framework to Improve Black-Box Attacks ICML 2020