5 papers
Hierarchical Memory Organization for Wikipedia Generation
Eugene J. Yu, Dawei Zhu, Yifan Song +6
Generating Wikipedia articles autonomously is a challenging task requiring the integration of accurate, comprehensive, and well-structured information from diverse sources. This pa…
More Tokens, Lower Precision: Towards the Optimal Token-Precision Trade-off in KV Cache Compression
Jiebin Zhang, Dawei Zhu, Yifan Song +6
As large language models (LLMs) process increasing context windows, the memory usage of KV cache has become a critical bottleneck during inference. The mainstream KV compression me…
Evaluating Robustness of Generative Search Engine on Adversarial Factual Questions
Xuming Hu, Xiaochuan Li, Junzhe Chen +8
Generative search engines have the potential to transform how people seek information online, but generated responses from existing large language models (LLMs)-backed generative s…
WIKIGENBENCH: Exploring Full-length Wikipedia Generation under Real-World Scenario
Jiebin Zhang, Eugene J. Yu, Qinyu Chen +8
It presents significant challenges to generate comprehensive and accurate Wikipedia articles for newly emerging events under a real-world scenario. Existing attempts fall short eit…
"Knowing When You Don't Know": A Multilingual Relevance Assessment Dataset for Robust Retrieval-Augmented Generation
Nandan Thakur, Luiz Bonifacio, Xinyu Zhang +8
Retrieval-Augmented Generation (RAG) grounds Large Language Model (LLM) output by leveraging external knowledge sources to reduce factual hallucinations. However, prior work lacks…