Yue Xing
29 papers · 2020–2026 · 8 conferences · across top CS/AI conferences
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Conferences
AISTATS (9)
ACL (8)
NIPS (4)
EMNLP (3)
NAACL (2)
CVPR (1)
EACL (1)
ECCV (1)
Top co-authors
Research topics
Keywords
large language model
(9)
adversarial training
(7)
adversarial robustness
(5)
retrieval-augmented generation
(5)
neural network
(3)
multi-agent system
(3)
representation learning
(2)
adversarial attack
(2)
representation fine-tuning
(2)
training datum
(2)
harmful content
(2)
robust learning
(2)
unlabeled datum
(2)
statistical learning theory
(1)
sparse coding
(1)
domain adaptation
(1)
transfer learning
(1)
adversarial learning
(1)
data poisoning
(1)
autoregressive generation
(1)
Papers
PEAR: Planner-Executor Agent Robustness Benchmark
EACL 2026
Retrieval Heads are Dynamic
ACL 2026
Six-CD: Benchmarking Concept Removals for Text-to-image Diffusion Models
CVPR 2025
Mitigating the Privacy Issues in Retrieval-Augmented Generation (RAG) via Pure Synthetic Data
EMNLP 2025
Data Poisoning for In-context Learning
NAACL 2025
Towards Knowledge Checking in Retrieval-augmented Generation: A Representation Perspective
NAACL 2025
Advancing Reasoning with Off-the-Shelf LLMs: A Semantic Structure Perspective
EMNLP 2025
Adversarial Training in High-Dimensional Regression: Generated Data and Neural Networks
AISTATS 2025
Superiority of Multi-Head Attention: A Theoretical Study in Shallow Transformers in In-Context Linear Regression
AISTATS 2025
A Theoretical Understanding of Chain-of-Thought: Coherent Reasoning and Error-Aware Demonstration
AISTATS 2025
Towards Context-Robust LLMs: A Gated Representation Fine-tuning Approach
ACL 2025
Unveiling Privacy Risks in LLM Agent Memory
ACL 2025
Red-Teaming LLM Multi-Agent Systems via Communication Attacks
ACL 2025
A General Framework to Enhance Fine-tuning-based LLM Unlearning
ACL 2025
Stepwise Perplexity-Guided Refinement for Efficient Chain-of-Thought Reasoning in Large Language Models
ACL 2025
Exploring Memorization in Fine-tuned Language Models
ACL 2024
The Good and The Bad: Exploring Privacy Issues in Retrieval-Augmented Generation (RAG)
ACL 2024
Unveiling and Mitigating Memorization in Text-to-image Diffusion Models through Cross Attention
ECCV 2024
Towards Understanding Jailbreak Attacks in LLMs: A Representation Space Analysis
EMNLP 2024
Better Representations via Adversarial Training in Pre-Training: A Theoretical Perspective
AISTATS 2024
Effect of Ambient-Intrinsic Dimension Gap on Adversarial Vulnerability
AISTATS 2024
Unlabeled Data Help: Minimax Analysis and Adversarial Robustness
AISTATS 2022
Why Do Artificially Generated Data Help Adversarial Robustness
NIPS 2022
Phase Transition from Clean Training to Adversarial Training
NIPS 2022
Adversarially Robust Estimate and Risk Analysis in Linear Regression
AISTATS 2021
On the Generalization Properties of Adversarial Training
AISTATS 2021
Predictive Power of Nearest Neighbors Algorithm under Random Perturbation
AISTATS 2021
On the Algorithmic Stability of Adversarial Training
NIPS 2021
Directional Pruning of Deep Neural Networks
NIPS 2020