Ruochen Wang

19 papers · 2021–2025 · 7 conferences · across top CS/AI conferences

Achievements

🐝 Cross-Pollinator (15) 🌈 Renaissance Researcher (6) 🌉 Interdisciplinary Bridge 🗺️ Taxonomy Completionist (20) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌍 Conference Polyglot (7) 🤝 Dynamic Duo (19) ❓ The Questioner (3) ⚡ Prolific Year (6) 💎 Century Club (19) 🔥 Unstoppable (5)

Conferences

ICLR (7) ICML (4) EMNLP (3) NIPS (2) CVPR (1) ECCV (1) ICCV (1)

Top co-authors

Cho-jui Hsieh (19) Minhao Cheng (10) Tianyi Zhou (5) Yuanhao Xiong (4) Xiangning Chen (4) Justin CUI (3) Boqing Gong (3) Xiaocheng Tang (3) Si Si (3) Xirui Li (2)

Research topics

Differential Privacy (1)

Keywords

synthetic datum (2) large language model (2) prompt engineering (2) image classification (1) visual perception (1) hyperparameter optimization (1) iterative optimization (1) data augmentation (1) in-context learning (1) communication efficiency (1) neural architecture search (1) visual reasoning (1) neural network optimization (1) distribution matching (1) learning to rank (1) mathematical reasoning (1) adversarial attack (1) tree search (1) benchmark evaluation (1) differential privacy (1)

Papers

Is Your Multimodal Language Model Oversensitive to Safe Queries? ICLR 2025

The Crystal Ball Hypothesis in diffusion models: Anticipating object positions from initial noise ICLR 2025

Large Language Models are Interpretable Learners ICLR 2025

QG-CoC: Question-Guided Chain-of-Captions for Large Multimodal Models EMNLP 2025

DrAttack: Prompt Decomposition and Reconstruction Makes Powerful LLMs Jailbreakers EMNLP 2024

Solving for X and Beyond: Can Large Language Models Solve Complex Math Problems with More-Than-Two Unknowns? EMNLP 2024

When and How do negative prompts take effect? ECCV 2024

On Discrete Prompt Optimization for Diffusion Models ICML 2024

One Prompt is not Enough: Automated Construction of a Mixture-of-Expert Prompts ICML 2024

Ameliorate Spurious Correlations in Dataset Condensation ICML 2024

FedDM: Iterative Distribution Matching for Communication-Efficient Federated Learning CVPR 2023

Scaling Up Dataset Distillation to ImageNet-1K with Constant Memory ICML 2023

DC-BENCH: Dataset Condensation Benchmark NIPS 2022

Efficient Non-Parametric Optimizer Search for Diverse Tasks NIPS 2022

Generalizing Few-Shot NAS with Gradient Matching ICLR 2022

Learning to Schedule Learning rate with Graph Neural Networks ICLR 2022

Rethinking Architecture Selection in Differentiable NAS ICLR 2021

DrNAS: Dirichlet Neural Architecture Search ICLR 2021

RANK-NOSH: Efficient Predictor-Based Architecture Search via Non-Uniform Successive Halving ICCV 2021