← Authors

Qi Yu

52 papers · 2014–2026 · 13 conferences · across top CS/AI conferences

Achievements

🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (14) πŸƒ Academic Marathon (11) 🌈 Renaissance Researcher (5) πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (13) πŸ—ΊοΈ Taxonomy Completionist (15) 🀝 Dynamic Duo (11) πŸ‘‘ Triple Crown πŸ† Grand Slam πŸ”¬ Deep Specialist (10) πŸ† Keyword Champion (4) ⚑ Prolific Year (11) πŸ”₯ Unstoppable (7) ❓ The Questioner πŸ’Ž Century Club (51) πŸ—ƒοΈ Keyword Collector (192) πŸ“ˆ Trend Setter

Conferences

NIPS (10) AAAI (9) ICML (9) AISTATS (4) COLING (3) CVPR (3) ICLR (3) EACL (2) ECCV (2) ICCV (2) IJCAI (2) NAACL (2) ACL (1)

Top co-authors

Ervine Zheng (11) Weishi Shi (9) Hitesh Sapkota (7) Anne Haake (6) Dayou Yu (6) Krishna Prasad Neupane (5) Deep Shankar Pandey (5) Rui Li (5) Pengcheng Shi (5) Yu Kong (4)

Research topics

Deep Learning (1) Reinforcement Learning (1)

Keywords

uncertainty quantification (12) active learning (8) uncertainty estimation (5) evidential learning (4) bayesian inference (4) few-shot learning (4) label correlation (3) gaussian process (3) evidential deep learning (3) text classification (3) label-efficient learning (3) model calibration (3) spiking neural network (2) multi-class classification (2) representation learning (2) bayesian nonparametric (2) reinforcement learning (2) eye tracking (2) multimodal learning (2) video anomaly detection (2)

Papers

Harnessing Consistency for Robust Test-Time LLM Ensemble EACL 2026
Learning State-Based Node Representations from a Class Hierarchy for Fine-Grained Open-Set Detection ICML 2025
Can We Ignore Labels in Out of Distribution Detection? ICLR 2025
Looking into User’s Long-term Interests through the Lens of Conservative Evidential Learning ICLR 2025
Hierarchical Multi-Source Uncertainty Aggregation for Interactive Video Captioning AAAI 2025
GLEN: Generalized Focal Loss Ensemble of Low-Rank Networks for Calibrated Visual Question Answering AAAI 2025
Meta Evidential Transformer for Few-Shot Open-Set Recognition ICML 2024
Be Confident in What You Know: Bayesian Parameter Efficient Fine-Tuning of Vision Foundation Models NIPS 2024
Adaptive Important Region Selection with Reinforced Hierarchical Search for Dense Object Detection NIPS 2024
Evidential Stochastic Differential Equations for Time-Aware Sequential Recommendation NIPS 2024
Evidential Mixture Machines: Deciphering Multi-Label Correlations for Active Learning Sensitivity NIPS 2024
Dual-Level Curriculum Meta-Learning for Noisy Few-Shot Learning Tasks AAAI 2024
GRIT: A Dataset of Group Reference Recognition in Italian COLING 2024
Ad Hoc Compounds for Stance Detection COLING 2024
Optimal Transport of Diverse Unsupervised Tasks for Robust Learning from Noisy Few-Shot Data ECCV 2024
Balancing Feature Similarity and Label Variability for Optimal Size-Aware One-shot Subset Selection ICML 2024
Hierarchical Novelty Detection via Fine-Grained Evidence Allocation ICML 2024
Learn to Accumulate Evidence from All Training Samples: Theory and Practice ICML 2023
Deep Temporal Sets with Evidential Reinforced Attentions for Unique Behavioral Pattern Discovery ICML 2023
Discover-Then-Rank Unlabeled Support Vectors in the Dual Space for Multi-Class Active Learning ICML 2023
Evidential Interactive Learning for Medical Image Captioning ICML 2023
Evidential Conditional Neural Processes AAAI 2023
Towards a More In-Depth Detection of Political Framing EACL 2023
Distributionally Robust Ensemble of Lottery Tickets Towards Calibrated Sparse Network Training NIPS 2023
Figurative Language Processing: A Linguistically Informed Feature Analysis of the Behavior of Language Models and Humans ACL 2023
Adaptive Robust Evidential Optimization For Open Set Detection from Imbalanced Data ICLR 2023
Actively Testing Your Model While It Learns: Realizing Label-Efficient Learning in Practice NIPS 2023
Knowledge Acquisition for Human-In-The-Loop Image Captioning AISTATS 2023
Scaling Up Dynamic Graph Representation Learning via Spiking Neural Networks AAAI 2023
Sparse Maximum Margin Learning from Multimodal Human Behavioral Patterns AAAI 2023
STARS: Spatial-Temporal Active Re-sampling for Label-Efficient Learning from Noisy Annotations AAAI 2023
β€œAgain, Dozens of Refugees Drowned”: A Computational Study of Political Framing Evoked by Presuppositions NAACL 2022
OpenTAL: Towards Open Set Temporal Action Localization CVPR 2022
A Dynamic Meta-Learning Model for Time-Sensitive Cold-Start Recommendations AAAI 2022
Dual-Level Adaptive Information Filtering for Interactive Image Segmentation AISTATS 2022
Towards Open Set Video Anomaly Detection ECCV 2022
Spiking Graph Convolutional Networks IJCAI 2022
Multidimensional Belief Quantification for Label-Efficient Meta-Learning CVPR 2022
Bayesian Nonparametric Submodular Video Partition for Robust Anomaly Detection CVPR 2022
A Continual Learning Framework for Uncertainty-Aware Interactive Image Segmentation AAAI 2021
Active Learning with Maximum Margin Sparse Gaussian Processes AISTATS 2021
Distributionally Robust Optimization for Deep Kernel Multiple Instance Learning AISTATS 2021
KonTra at CMCL 2021 Shared Task: Predicting Eye Movements by Combining BERT with Surface, Linguistic and Behavioral Information NAACL 2021
DRIVE: Deep Reinforced Accident Anticipation With Visual Explanation ICCV 2021
Evidential Deep Learning for Open Set Action Recognition ICCV 2021
A Gaussian Process-Bayesian Bernoulli Mixture Model for Multi-Label Active Learning NIPS 2021
Dynamic Fusion of Eye Movement Data and Verbal Narrations in Knowledge-rich Domains NIPS 2020
Multifaceted Uncertainty Estimation for Label-Efficient Deep Learning NIPS 2020
Integrating Bayesian and Discriminative Sparse Kernel Machines for Multi-class Active Learning NIPS 2019
Fast Direct Search in an Optimally Compressed Continuous Target Space for Efficient Multi-Label Active Learning ICML 2019
Modeling Physicians' Utterances to Explore Diagnostic Decision-making IJCAI 2017
Towards multimodal modeling of physicians’ diagnostic confidence and self-awareness using medical narratives COLING 2014