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Ziquan Liu

22 papers · 2019–2026 · 10 conferences · across top CS/AI conferences

Achievements

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+10 more ↓ πŸƒ Academic Marathon (6) πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (9) 🧭 Keyword Pioneer 🐝 Cross-Pollinator (14)
🐝 Cross-Pollinator (14) 🌈 Renaissance Researcher (6) πŸ—ΊοΈ Taxonomy Completionist (53) πŸ† Grand Slam 🀝 Dynamic Duo (11) πŸ“ˆ Trend Setter ⚑ Prolific Year (8) πŸ’Ž Century Club (19) πŸ”₯ Unstoppable (7) πŸ—ƒοΈ Keyword Collector (93)

Conferences

CVPR (5) ICLR (3) AAAI (2) ACL (2) COLING (2) ICCV (2) IJCAI (2) NIPS (2) ECCV (1) ICML (1)

Papers

Confidence Should Be Calibrated More Than One Turn Deep ACL 2026 GrACE: A Generative Approach to Better Confidence Elicitation and Efficient Test-Time Scaling in Large Language Models ACL 2026 Cost-Sensitive Conformal Training with Provably Controllable Learning Bounds AAAI 2026 Get Confused Cautiously: Textual Sequence Memorization Erasure with Selective Entropy Maximization COLING 2025 ConformalSAM: Unlocking the Potential of Foundational Segmentation Models in Semi-Supervised Semantic Segmentation with Conformal Prediction ICCV 2025 PROSAC: Provably Safe Certification for Machine Learning Models under Adversarial Attacks AAAI 2025 Cultural Alignment in Large Language Models: An Explanatory Analysis Based on Hofstede’s Cultural Dimensions COLING 2025 AIM-Fair: Advancing Algorithmic Fairness via Selectively Fine-Tuning Biased Models with Contextual Synthetic Data CVPR 2025 Temporal Unlearnable Examples: Preventing Personal Video Data from Unauthorized Exploitation by Object Tracking ICCV 2025 Query-based Knowledge Transfer for Heterogeneous Learning Environments ICLR 2025 SEBRA : Debiasing through Self-Guided Bias Ranking ICLR 2025 A Secure Image Watermarking Framework with Statistical Guarantees via Adversarial Attacks on Secret Key Networks ECCV 2024 The Pitfalls and Promise of Conformal Inference Under Adversarial Attacks ICML 2024 TWINS: A Fine-Tuning Framework for Improved Transferability of Adversarial Robustness and Generalization CVPR 2023 DropMAE: Masked Autoencoders With Spatial-Attention Dropout for Tracking Tasks CVPR 2023 Retrieval-Augmented Multiple Instance Learning NIPS 2023 Bayes-MIL: A New Probabilistic Perspective on Attention-based Multiple Instance Learning for Whole Slide Images ICLR 2023 Improved Fine-Tuning by Better Leveraging Pre-Training Data NIPS 2022 A Generalized Loss Function for Crowd Counting and Localization CVPR 2021 Bayesian Nested Neural Networks for Uncertainty Calibration and Adaptive Compression CVPR 2021 Fully Nested Neural Network for Adaptive Compression and Quantization IJCAI 2020 Parametric Manifold Learning of Gaussian Mixture Models IJCAI 2019