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Kaidi Xu

46 papers · 2019–2026 · 13 conferences · across top CS/AI conferences

Achievements

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+14 more ↓ πŸ—ΊοΈ Taxonomy Completionist (10) 🧭 Keyword Pioneer πŸŒ‰ Interdisciplinary Bridge 🌈 Renaissance Researcher (5) 🌍 Conference Polyglot (12)
πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (10) 🧭 Keyword Pioneer πŸ† Grand Slam πŸ‘‘ Triple Crown 🀝 Dynamic Duo (15) πŸ‘₯ Mega-Team (71) πŸ”¬ Deep Specialist (10) 🧬 Topic Evolution ⚑ Prolific Year (14) πŸ—ƒοΈ Keyword Collector (161) πŸ’Ž Century Club (42) πŸ”₯ Unstoppable (7) ❓ The Questioner (4)

Conferences

NIPS (8) ICML (6) ACL (5) CVPR (4) ICCV (4) ICLR (4) AAAI (3) EMNLP (3) NAACL (3) ECCV (2) IJCAI (2) EACL (1) RSS (1)

Top co-authors

Jinhao Duan (18) Xue Lin (9) Tianlong Chen (9) Huan Zhang (9) Sijia Liu (8) Bhavya Kailkhura (8) Xiaoshuang Shi (8) Shiqi Wang (7) Hao Cheng (7) Lichao Sun (6)

Research topics

Systems (1) Applications (1) Privacy (1) Probability (1)

Keywords

large language model (10) adversarial attack (9) neural network verification (5) uncertainty quantification (5) adversarial robustness (4) adversarial training (4) image generation (3) zeroth-order optimization (3) diffusion model (3) conformal prediction (3) branch and bound (3) evasion attack (2) prediction set (2) privacy protection (2) black-box attack (2) benchmark evaluation (2) mixed integer programming (2) black-box optimization (2) strategic reasoning (2) adversarial perturbation (2)

Papers

Safety Alignment of Large Language Models via Contrasting Safe and Harmful Distributions AAAI 2026 COIN: Uncertainty-Guarding Selective Question Answering for Foundation Models with Provable Risk Guarantees AAAI 2026 IUQ: Interrogative Uncertainty Quantification for Long-Form Large Language Model Generation ACL 2026 Dialogue is Better Than Monologue: Instructing Meidcal LLMs via Strategic Conversations EACL 2026 DiffZOO: A Purely Query-Based Black-Box Attack for Red-teaming Text-to-Image Generative Model via Zeroth Order Optimization NAACL 2025 TruthPrInt: Mitigating Large Vision-Language Models Object Hallucination Via Latent Truthful-Guided Pre-Intervention ICCV 2025 DynaCode: A Dynamic Complexity-Aware Code Benchmark for Evaluating Large Language Models in Code Generation ACL 2025 MedHallu: A Comprehensive Benchmark for Detecting Medical Hallucinations in Large Language Models EMNLP 2025 Sparse Neurons Carry Strong Signals of Question Ambiguity in LLMs EMNLP 2025 GuideLLM: Exploring LLM-Guided Conversation with Applications in Autobiography Interviewing NAACL 2025 Optimizing Robustness and Accuracy in Mixture of Experts: A Dual-Model Approach ICML 2025 SConU: Selective Conformal Uncertainty in Large Language Models ACL 2025 Not Just Text: Uncovering Vision Modality Typographic Threats in Image Generation Models CVPR 2025 An Efficient Membership Inference Attack for the Diffusion Model by Proximal Initialization ICLR 2024 GTBench: Uncovering the Strategic Reasoning Capabilities of LLMs via Game-Theoretic Evaluations NIPS 2024 NN4SysBench: Characterizing Neural Network Verification for Computer Systems NIPS 2024 Stable Unlearnable Example: Enhancing the Robustness of Unlearnable Examples via Stable Error-Minimizing Noise AAAI 2024 Shifting Attention to Relevance: Towards the Predictive Uncertainty Quantification of Free-Form Large Language Models ACL 2024 Reinforcement Learning-Driven LLM Agent for Automated Attacks on LLMs ACL 2024 Dynamic Adversarial Attacks on Autonomous Driving Systems RSS 2024 Can Protective Perturbation Safeguard Personal Data from Being Exploited by Stable Diffusion? CVPR 2024 ACT-Diffusion: Efficient Adversarial Consistency Training for One-step Diffusion Models CVPR 2024 Unveiling Typographic Deceptions: Insights of the Typographic Vulnerability in Large Vision-Language Models ECCV 2024 ConU: Conformal Uncertainty in Large Language Models with Correctness Coverage Guarantees EMNLP 2024 ReTA: Recursively Thinking Ahead to Improve the Strategic Reasoning of Large Language Models NAACL 2024 Position: TrustLLM: Trustworthiness in Large Language Models ICML 2024 Decoding Compressed Trust: Scrutinizing the Trustworthiness of Efficient LLMs Under Compression ICML 2024 Are Diffusion Models Vulnerable to Membership Inference Attacks? ICML 2023 Does Physical Adversarial Example Really Matter to Autonomous Driving? Towards System-Level Effect of Adversarial Object Evasion Attack ICCV 2023 Improve Video Representation with Temporal Adversarial Augmentation IJCAI 2023 Toward Robust Spiking Neural Network Against Adversarial Perturbation NIPS 2022 General Cutting Planes for Bound-Propagation-Based Neural Network Verification NIPS 2022 A Branch and Bound Framework for Stronger Adversarial Attacks of ReLU Networks ICML 2022 Beta-CROWN: Efficient Bound Propagation with Per-neuron Split Constraints for Neural Network Robustness Verification NIPS 2021 On Fast Adversarial Robustness Adaptation in Model-Agnostic Meta-Learning ICLR 2021 Fast and Complete: Enabling Complete Neural Network Verification with Rapid and Massively Parallel Incomplete Verifiers ICLR 2021 ScaleCert: Scalable Certified Defense against Adversarial Patches with Sparse Superficial Layers NIPS 2021 Min-Max Optimization without Gradients: Convergence and Applications to Black-Box Evasion and Poisoning Attacks ICML 2020 Adversarial T-shirt! Evading Person Detectors in A Physical World ECCV 2020 Light-weight Calibrator: A Separable Component for Unsupervised Domain Adaptation CVPR 2020 Automatic Perturbation Analysis for Scalable Certified Robustness and Beyond NIPS 2020 Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective IJCAI 2019 ZO-AdaMM: Zeroth-Order Adaptive Momentum Method for Black-Box Optimization NIPS 2019 On the Design of Black-Box Adversarial Examples by Leveraging Gradient-Free Optimization and Operator Splitting Method ICCV 2019 Adversarial Robustness vs. Model Compression, or Both? ICCV 2019 Structured Adversarial Attack: Towards General Implementation and Better Interpretability ICLR 2019