Guanchu Wang
18 papers · 2020–2026 · 9 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (42) π Conference Polyglot Β· Silver π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Bronze π£ Hot Topic Early Bird
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Triple Crown
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Dynamic Duo
(13)
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Prolific Year Β· Productive
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Renaissance Researcher
(5)
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Century Club Β· Bronze
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Trend Setter
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The Questioner
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Keyword Collector
(95)
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Unstoppable Β· Bronze
Top co-authors
Research topics
Machine Learning
(15)
Artificial Intelligence
(14)
Core AI
(12)
Deep Learning
(8)
Application Areas
(8)
Learning Types Β· Machine Learning
(6)
Natural Language Processing
(4)
Core Methods
(4)
Optimization & Theory Β· Machine Learning
(4)
Optimization & Theory Β· Deep Learning
(4)
Learning Paradigms
(3)
Learning Types Β· Deep Learning
(3)
Models
(3)
Generation
(2)
Resources & Methods
(2)
Keywords
large language model
(7)
representation learning
(3)
deep neural network
(3)
model compression
(2)
reinforcement learning
(2)
model explanation
(2)
multi-agent system
(2)
question answering
(2)
model calibration
(2)
memory efficiency
(2)
domain generalization
(1)
model security
(1)
algorithmic fairness
(1)
anomaly detection
(1)
contrastive learning
(1)
few-shot learning
(1)
stochastic gradient descent
(1)
uncertainty quantification
(1)
matrix factorization
(1)
catastrophic forgetting
(1)
Papers
Catastrophic Forgetting in Kolmogorov-Arnold Networks
AAAI 2026
FaithLM: Towards Faithful Explanations for Large Language Models
EACL 2026
A Decoupled Multi-Agent Framework for Complex Text Style Transfer
EMNLP 2025
MAIN-RAG: Multi-Agent Filtering Retrieval-Augmented Generation
ACL 2025
Personalizing Low-Rank Bayesian Neural Networks Via Federated Learning
AISTATS 2025
Quantized Can Still Be Calibrated: A Unified Framework to Calibration in Quantized Large Language Models
ACL 2025
Self-Ensemble: Mitigating Confidence Distortion for Large Language Models
EMNLP 2025
KV Cache Compression, But What Must We Give in Return? A Comprehensive Benchmark of Long Context Capable Approaches
EMNLP 2024
Taylor Unswift: Secured Weight Release for Large Language Models via Taylor Expansion
EMNLP 2024
TVE: Learning Meta-attribution for Transferable Vision Explainer
ICML 2024
Chasing Fairness Under Distribution Shift: A Model Weight Perturbation Approach
NeurIPS 2023
CoRTX: Contrastive Framework for Real-time Explanation
ICLR 2023
DIVISION: Memory Efficient Training via Dual Activation Precision
ICML 2023
Winner-Take-All Column Row Sampling for Memory Efficient Adaptation of Language Model
NeurIPS 2023
Accelerating Shapley Explanation via Contributive Cooperator Selection
ICML 2022
Fairness via Representation Neutralization
NeurIPS 2021
TODS: An Automated Time Series Outlier Detection System
AAAI 2021
Independent Skill Transfer for Deep Reinforcement Learning
IJCAI 2020