← Authors

Jie Ren

46 papers · 2019–2025 · 14 conferences · across top CS/AI conferences

Achievements

🌍 Conference Polyglot (14) 🌈 Renaissance Researcher (5) 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (10) πŸ—ΊοΈ Taxonomy Completionist (15) 🧭 Keyword Pioneer πŸƒ Academic Marathon (6) πŸŒ‰ Interdisciplinary Bridge 🀝 Dynamic Duo (11) πŸ† Grand Slam πŸ‘‘ Triple Crown πŸ—ƒοΈ Keyword Collector (211) ❓ The Questioner (2) ⚑ Prolific Year (5) πŸ’Ž Century Club (46) πŸ”₯ Unstoppable (7)

Conferences

ICLR (8) NIPS (8) EMNLP (6) ACL (5) ICML (5) AAAI (3) CVPR (3) ECCV (2) AISTATS (1) ICCV (1) IJCAI (1) JMLR (1) NAACL (1) WACV (1)

Top co-authors

Jiliang Tang (11) Han Xu (10) Quanshi Zhang (10) Hui LIU (9) Balaji Lakshminarayanan (8) Shenglai Zeng (8) Yue Xing (7) Pengfei He (7) Yingqian Cui (5) Jiankun Zhang (3)

Research topics

Privacy (2) Science (1)

Keywords

large language model (8) retrieval-augmented generation (3) image generation (3) out-of-distribution detection (3) neural network (3) contrastive learning (2) image classification (2) distribution shift (2) adversarial perturbation (2) language model (2) knowledge graph (2) machine unlearning (2) deep neural network (2) training datum (2) knowledge distillation (2) multimodal learning (2) neural network interpretability (2) few-shot learning (1) neural network training (1) adversarial robustness (1)

Papers

Six-CD: Benchmarking Concept Removals for Text-to-image Diffusion Models CVPR 2025
Optimizing Personalized Federated Learning Through Adaptive Layer-Wise Learning IJCAI 2025
RRM: Robust Reward Model Training Mitigates Reward Hacking ICLR 2025
Revisiting Mode Connectivity in Neural Networks with Bezier Surface ICLR 2025
HS-FPN: High Frequency and Spatial Perception FPN for Tiny Object Detection AAAI 2025
Monitoring Primitive Interactions During the Training of DNNs AAAI 2025
Beyond Text: Unveiling Privacy Vulnerabilities in Multi-modal Retrieval-Augmented Generation EMNLP 2025
A General Framework to Enhance Fine-tuning-based LLM Unlearning ACL 2025
Superiority of Multi-Head Attention: A Theoretical Study in Shallow Transformers in In-Context Linear Regression AISTATS 2025
Mitigating the Privacy Issues in Retrieval-Augmented Generation (RAG) via Pure Synthetic Data EMNLP 2025
A Robust Semantics-based Watermark for Large Language Model against Paraphrasing NAACL 2024
Unveiling and Mitigating Memorization in Text-to-image Diffusion Models through Cross Attention ECCV 2024
On the Generalization of Training-based ChatGPT Detection Methods EMNLP 2024
Exploring Memorization in Fine-tuned Language Models ACL 2024
QUIK: Towards End-to-end 4-Bit Inference on Generative Large Language Models EMNLP 2024
The Good and The Bad: Exploring Privacy Issues in Retrieval-Augmented Generation (RAG) ACL 2024
Sharpness-Aware Data Poisoning Attack ICLR 2024
Construction and Application of Materials Knowledge Graph in Multidisciplinary Materials Science via Large Language Model NIPS 2024
Neural Style Protection: Counteracting Unauthorized Neural Style Transfer WACV 2024
Identifying Semantic Induction Heads to Understand In-Context Learning ACL 2024
Defining and Quantifying the Emergence of Sparse Concepts in DNNs CVPR 2023
DrugOOD: Out-of-Distribution Dataset Curator and Benchmark for AI-Aided Drug Discovery – a Focus on Affinity Prediction Problems with Noise Annotations AAAI 2023
Improving Zero-Shot Generalization and Robustness of Multi-Modal Models CVPR 2023
Improving the Robustness of Summarization Models by Detecting and Removing Input Noise EMNLP 2023
On Uncertainty Calibration and Selective Generation in Probabilistic Neural Summarization: A Benchmark Study EMNLP 2023
Transferable Unlearnable Examples ICLR 2023
Can We Faithfully Represent Absence States to Compute Shapley Values on a DNN? ICLR 2023
Out-of-Distribution Detection and Selective Generation for Conditional Language Models ICLR 2023
A Simple Zero-shot Prompt Weighting Technique to Improve Prompt Ensembling in Text-Image Models ICML 2023
Probabilistic Categorical Adversarial Attack and Adversarial Training ICML 2023
A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness JMLR 2023
Exploring the Impact of Negative Samples of Contrastive Learning: A Case Study of Sentence Embedding ACL 2022
A Theoretical Understanding of Gradient Bias in Meta-Reinforcement Learning NIPS 2022
Pluralistic Image Completion with Gaussian Mixture Models NIPS 2022
Towards Theoretical Analysis of Transformation Complexity of ReLU DNNs ICML 2022
MegBA: A GPU-Based Distributed Library for Large-Scale Bundle Adjustment ECCV 2022
A Unified Approach to Interpreting and Boosting Adversarial Transferability ICLR 2021
Towards a Unified Game-Theoretic View of Adversarial Perturbations and Robustness NIPS 2021
Exploring the Limits of Out-of-Distribution Detection NIPS 2021
Sawtooth Factorial Topic Embeddings Guided Gamma Belief Network ICML 2021
Interpreting and Disentangling Feature Components of Various Complexity from DNNs ICML 2021
HM-ANN: Efficient Billion-Point Nearest Neighbor Search on Heterogeneous Memory NIPS 2020
Interpretable Complex-Valued Neural Networks for Privacy Protection ICLR 2020
Likelihood Ratios for Out-of-Distribution Detection NIPS 2019
Explaining Neural Networks Semantically and Quantitatively ICCV 2019
Can you trust your model's uncertainty? Evaluating predictive uncertainty under dataset shift NIPS 2019