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Jianyi Zhang

17 papers · 2019–2025 · 9 conferences · across top CS/AI conferences

Achievements

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+11 more ↓ 🌍 Conference Polyglot (9) πŸƒ Academic Marathon (6) 🧭 Keyword Pioneer πŸŒ‰ Interdisciplinary Bridge 🐝 Cross-Pollinator (12)
🐝 Cross-Pollinator (12) 🌈 Renaissance Researcher (5) πŸ—ΊοΈ Taxonomy Completionist (28) πŸ† Grand Slam 🀝 Dynamic Duo (11) πŸ† Keyword Champion πŸš€ Conference Pioneer πŸ’Ž Century Club (17) πŸ—ƒοΈ Keyword Collector (56) ❓ The Questioner ⚑ Prolific Year (8)

Conferences

ICLR (4) ICML (4) NIPS (2) WACV (2) AAAI (1) ACL (1) AISTATS (1) ECCV (1) ICCV (1)

Papers

ARTIST: Improving the Generation of Text-Rich Images with Disentangled Diffusion Models and Large Language Models WACV 2025 Keyframe-oriented Vision Token Pruning: Enhancing Efficiency of Large Vision Language Models on Long-Form Video Processing ICCV 2025 Sufficient Context: A New Lens on Retrieval Augmented Generation Systems ICLR 2025 Proactive Privacy Amnesia for Large Language Models: Safeguarding PII with Negligible Impact on Model Utility ICLR 2025 Min-K%++: Improved Baseline for Pre-Training Data Detection from Large Language Models ICLR 2025 SADA: Stability-guided Adaptive Diffusion Acceleration ICML 2025 CoreMatching: A Co-adaptive Sparse Inference Framework with Token and Neuron Pruning for Comprehensive Acceleration of Vision-Language Models ICML 2025 MLLM-LLaVA-FL: Multimodal Large Language Model Assisted Federated Learning WACV 2025 Unlocking the Potential of Federated Learning: The Symphony of Dataset Distillation via Deep Generative Latents ECCV 2024 SLED: Self Logits Evolution Decoding for Improving Factuality in Large Language Models NIPS 2024 Fed-CBS: A Heterogeneity-Aware Client Sampling Mechanism for Federated Learning via Class-Imbalance Reduction ICML 2023 ReAugKD: Retrieval-Augmented Knowledge Distillation For Pre-trained Language Models ACL 2023 Why do We Need Large Batchsizes in Contrastive Learning? A Gradient-Bias Perspective NIPS 2022 Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning ICLR 2020 Stochastic Particle-Optimization Sampling and the Non-Asymptotic Convergence Theory AISTATS 2020 Variance Reduction in Stochastic Particle-Optimization Sampling ICML 2020 Self-Adversarially Learned Bayesian Sampling AAAI 2019