3 papers
cs.AI2026
Representation Interventions Enable Lifelong Knowledge Memory Control in LLMs
Xuyuan Liu, Shengyu Chen, Xinshuai Dong +6
Large language models (LLMs) often produce incorrect or outdated content after being employed. Efficient and accurate knowledge updates without costly retraining are a major challe…
cs.LG2026
The Power of Order: Fooling LLMs with Adversarial Table Permutations
Xinshuai Dong, Haifeng Chen, Xuyuan Liu +5
Large Language Models have achieved remarkable success and are increasingly deployed in critical applications involving tabular data, such as Table Question Answering. However, the…
cs.CL2026
Learning to Route: A Rule-Driven Agent Framework for Hybrid-Source Retrieval-Augmented Generation
Haoyue Bai, Haoyu Wang, Shengyu Chen +5
Large Language Models (LLMs) have shown remarkable performance on general Question Answering (QA), yet they often struggle in domain-specific scenarios where accurate and up-to-dat…