Jie Ren

47 papers · 2019–2026 · 14 conferences · across top CS/AI conferences

Achievements

+11 more ↓

🗺️ Taxonomy Completionist (15) 🧭 Keyword Pioneer 🌉 Interdisciplinary Bridge 🌈 Renaissance Researcher (5) 🌍 Conference Polyglot (14)

🧭 Keyword Pioneer 🏃 Academic Marathon (6) 🌉 Interdisciplinary Bridge 🤝 Dynamic Duo (11) 🏆 Grand Slam 👑 Triple Crown 🗃️ Keyword Collector (211) ❓ The Questioner (2) ⚡ Prolific Year (5) 💎 Century Club (46) 🔥 Unstoppable (7)

Conferences

ICLR (8) NIPS (8) ACL (6) EMNLP (6) 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) Quanshi Zhang (10) Han Xu (10) Hui LIU (9) Shenglai Zeng (8) Balaji Lakshminarayanan (8) Yue Xing (7) Pengfei He (7) Yingqian Cui (5) Zheng Wang (3)

Research topics

Privacy (2) Science (1)

Keywords

large language model (8) retrieval-augmented generation (4) 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

Lifting Optimized Binaries to Canonical Compiler IR via Structure-Aware Retrieval and Iterative Verification ACL 2026 Optimizing Personalized Federated Learning Through Adaptive Layer-Wise Learning IJCAI 2025 Mitigating the Privacy Issues in Retrieval-Augmented Generation (RAG) via Pure Synthetic Data EMNLP 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 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 Beyond Text: Unveiling Privacy Vulnerabilities in Multi-modal Retrieval-Augmented Generation EMNLP 2025 Six-CD: Benchmarking Concept Removals for Text-to-image Diffusion Models CVPR 2025 Sharpness-Aware Data Poisoning Attack ICLR 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 On the Generalization of Training-based ChatGPT Detection Methods EMNLP 2024 The Good and The Bad: Exploring Privacy Issues in Retrieval-Augmented Generation (RAG) ACL 2024 Identifying Semantic Induction Heads to Understand In-Context Learning ACL 2024 Construction and Application of Materials Knowledge Graph in Multidisciplinary Materials Science via Large Language Model NIPS 2024 A Robust Semantics-based Watermark for Large Language Model against Paraphrasing NAACL 2024 Neural Style Protection: Counteracting Unauthorized Neural Style Transfer WACV 2024 Unveiling and Mitigating Memorization in Text-to-image Diffusion Models through Cross Attention ECCV 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 MegBA: A GPU-Based Distributed Library for Large-Scale Bundle Adjustment ECCV 2022 Exploring the Impact of Negative Samples of Contrastive Learning: A Case Study of Sentence Embedding ACL 2022 Towards Theoretical Analysis of Transformation Complexity of ReLU DNNs ICML 2022 A Theoretical Understanding of Gradient Bias in Meta-Reinforcement Learning NIPS 2022 Pluralistic Image Completion with Gaussian Mixture Models NIPS 2022 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 Towards a Unified Game-Theoretic View of Adversarial Perturbations and Robustness NIPS 2021 A Unified Approach to Interpreting and Boosting Adversarial Transferability ICLR 2021 Interpretable Complex-Valued Neural Networks for Privacy Protection ICLR 2020 HM-ANN: Efficient Billion-Point Nearest Neighbor Search on Heterogeneous Memory NIPS 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