Xia Hu
82 papers · 2009–2026 · 16 conferences · across top CS/AI conferences
Achievements
Jump to papers ↓+15 more ↓ Show less ↑
πΊοΈ Taxonomy Completionist (13) π§ Keyword Pioneer π Interdisciplinary Bridge π Renaissance Researcher (5) π Conference Polyglot (16)
π§
Keyword Pioneer
π
Renaissance Researcher
(5)
π
Conference Polyglot
(16)
π
Grand Slam
π¬
Deep Specialist
(13)
π§¬
Topic Evolution
π€
Dynamic Duo
(24)
π
Triple Crown
ποΈ
Keyword Collector
(282)
β
The Questioner
(2)
β‘
Prolific Year
(5)
π
Conference Pioneer
π
Trend Setter
π
Century Club
(80)
π₯
Unstoppable
(9)
Conferences
IJCAI (13)
NIPS (12)
AAAI (11)
ICML (11)
ICLR (9)
EMNLP (6)
NAACL (4)
ACL (3)
CVPR (3)
EACL (3)
IJCNLP (2)
AACL (1)
AUTOML (1)
COLING (1)
ICCV (1)
JMLR (1)
Top co-authors
Research topics
Keywords
graph neural network
(12)
large language model
(10)
deep neural network
(6)
model compression
(6)
reinforcement learning
(5)
anomaly detection
(4)
outlier detection
(3)
feature attribution
(3)
multi-agent system
(3)
neural network
(3)
automated machine learning
(3)
attention mechanism
(3)
language model
(3)
model interpretability
(2)
deep learning
(2)
sql generation
(2)
message passing
(2)
data augmentation
(2)
representation learning
(2)
knowledge distillation
(2)
Papers
FaithLM: Towards Faithful Explanations for Large Language Models
EACL 2026
Dialogue is Better Than Monologue: Instructing Meidcal LLMs via Strategic Conversations
EACL 2026
Learning to Route LLMs with Confidence Tokens
ICML 2025
Flexible Group Count Enables Hassle-Free Structured Pruning
CVPR 2025
ReasonerRank: Redefining Language Model Evaluation with Ground-Truth-Free Ranking Frameworks
ACL 2025
LoRATK: LoRA Once, Backdoor Everywhere in the Share-and-Play Ecosystem
EMNLP 2025
MQuAKE-Remastered: Multi-Hop Knowledge Editing Can Only Be Advanced with Reliable Evaluations
ICLR 2025
AD-LLM: Benchmarking Large Language Models for Anomaly Detection
ACL 2025
A Decoupled Multi-Agent Framework for Complex Text Style Transfer
EMNLP 2025
DHP Benchmark: Are LLMs Good NLG Evaluators?
NAACL 2025
Chain-of-Query: Unleashing the Power of LLMs in SQL-Aided Table Understanding via Multi-Agent Collaboration
AACL 2025
TopV: Compatible Token Pruning with Inference Time Optimization for Fast and Low-Memory Multimodal Vision Language Model
CVPR 2025
Self-Ensemble: Mitigating Confidence Distortion for Large Language Models
EMNLP 2025
Chain-of-Query: Unleashing the Power of LLMs in SQL-Aided Table Understanding via Multi-Agent Collaboration
IJCNLP 2025
KIVI: A Tuning-Free Asymmetric 2bit Quantization for KV Cache
ICML 2024
FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods
ICLR 2024
Gradient Rewiring for Editable Graph Neural Network Training
NIPS 2024
Secure Your Model: An Effective Key Prompt Protection Mechanism for Large Language Models
NAACL 2024
Learning to Compress Prompt in Natural Language Formats
NAACL 2024
GNNs Also Deserve Editing, and They Need It More Than Once
ICML 2024
Chasing Fairness in Graphs: A GNN Architecture Perspective
AAAI 2024
Soft Prompt Recovers Compressed LLMs, Transferably
ICML 2024
TVE: Learning Meta-attribution for Transferable Vision Explainer
ICML 2024
Omni-SMoLA: Boosting Generalist Multimodal Models with Soft Mixture of Low-rank Experts
CVPR 2024
Taylor Unswift: Secured Weight Release for Large Language Models via Taylor Expansion
EMNLP 2024
KV Cache Compression, But What Must We Give in Return? A Comprehensive Benchmark of Long Context Capable Approaches
EMNLP 2024
LLM Maybe LongLM: SelfExtend LLM Context Window Without Tuning
ICML 2024
CoRTX: Contrastive Framework for Real-time Explanation
ICLR 2023
One Less Reason for Filter Pruning: Gaining Free Adversarial Robustness with Structured Grouped Kernel Pruning
NIPS 2023
Setting the Trap: Capturing and Defeating Backdoors in Pretrained Language Models through Honeypots
NIPS 2023
MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization
ICLR 2023
Fair Graph Distillation
NIPS 2023
Robustness Challenges in Model Distillation and Pruning for Natural Language Understanding
EACL 2023
Probabilistic Masked Attention Networks for Explainable Sequential Recommendation
IJCAI 2023
AutoKeras: An AutoML Library for Deep Learning
JMLR 2023
Winner-Take-All Column Row Sampling for Memory Efficient Adaptation of Language Model
NIPS 2023
Assessing Privacy Risks in Language Models: A Case Study on Summarization Tasks
EMNLP 2023
RSC: Accelerate Graph Neural Networks Training via Randomized Sparse Computations
ICML 2023
Chasing Fairness Under Distribution Shift: A Model Weight Perturbation Approach
NIPS 2023
DIVISION: Memory Efficient Training via Dual Activation Precision
ICML 2023
AutoVideo: An Automated Video Action Recognition System
IJCAI 2022
A Comprehensive Study on Large-Scale Graph Training: Benchmarking and Rethinking
NIPS 2022
DreamShard: Generalizable Embedding Table Placement for Recommender Systems
NIPS 2022
AutoCoG: A Unified Data-Model Co-Search Framework for Graph Neural Networks
AUTOML 2022
Orthogonal Graph Neural Networks
AAAI 2022
Towards Debiasing DNN Models from Spurious Feature Influence
AAAI 2022
RES: An Interpretable Replicability Estimation System for Research Publications
AAAI 2022
DEGREE: Decomposition Based Explanation for Graph Neural Networks
ICLR 2022
EXACT: Scalable Graph Neural Networks Training via Extreme Activation Compression
ICLR 2022
An Information Fusion Approach to Learning with Instance-Dependent Label Noise
ICLR 2022
Generalized Demographic Parity for Group Fairness
ICLR 2022
G-Mixup: Graph Data Augmentation for Graph Classification
ICML 2022
Accelerating Shapley Explanation via Contributive Cooperator Selection
ICML 2022
Table2Graph: Transforming Tabular Data to Unified Weighted Graph
IJCAI 2022
Rank the Episodes: A Simple Approach for Exploration in Procedurally-Generated Environments
ICLR 2021
DivAug: Plug-In Automated Data Augmentation With Explicit Diversity Maximization
ICCV 2021
TODS: An Automated Time Series Outlier Detection System
AAAI 2021
A Unified Taylor Framework for Revisiting Attribution Methods
AAAI 2021
Dynamic Memory based Attention Network for Sequential Recommendation
AAAI 2021
Towards Interpreting and Mitigating Shortcut Learning Behavior of NLU models
NAACL 2021
Dirichlet Energy Constrained Learning for Deep Graph Neural Networks
NIPS 2021
Fairness via Representation Neutralization
NIPS 2021
DouZero: Mastering DouDizhu with Self-Play Deep Reinforcement Learning
ICML 2021
Dual Policy Distillation
IJCAI 2020
RLCard: A Platform for Reinforcement Learning in Card Games
IJCAI 2020
Detecting Interactions from Neural Networks via Topological Analysis
NIPS 2020
Towards Deeper Graph Neural Networks with Differentiable Group Normalization
NIPS 2020
Multi-Channel Graph Neural Networks
IJCAI 2020
Deep Bayesian Optimization on Attributed Graphs
AAAI 2019
Large-Scale Heterogeneous Feature Embedding
AAAI 2019
Experience Replay Optimization
IJCAI 2019
Interpreting Deep Models for Text Analysis via Optimization and Regularization Methods
AAAI 2019
Robust Negative Sampling for Network Embedding
AAAI 2019
Contextual Outlier Interpretation
IJCAI 2018
Radar: Residual Analysis for Anomaly Detection in Attributed Networks
IJCAI 2017
Accelerated Local Anomaly Detection via Resolving Attributed Networks
IJCAI 2017
Learning Geographical Hierarchy Features for Social Image Location Prediction
IJCAI 2015
Social Spammer Detection in Microblogging
IJCAI 2013
Exploiting Local and Global Social Context for Recommendation
IJCAI 2013
A Semi-Supervised Bayesian Network Model for Microblog Topic Classification
COLING 2012
Query Segmentation Based on Eigenspace Similarity
ACL 2009
Query Segmentation Based on Eigenspace Similarity
IJCNLP 2009