4 citations · 4 across the 2 of their papers we have counts for
5 papers
A Simple Yet Strong Baseline for Long-Term Conversational Memory of LLM Agents
Sizhe Zhou, Jiawei Han
LLM-based conversational agents still struggle to maintain coherent, personalized interaction over many sessions: fixed context windows limit how much history can be kept in view,…
TEXT2DB: Integration-Aware Information Extraction with Large Language Model Agents
Yizhu Jiao, Sha Li, Sizhe Zhou +2
The task of information extraction (IE) is to extract structured knowledge from text. However, it is often not straightforward to utilize IE output due to the mismatch between the…
DynamicRAG: Leveraging Outputs of Large Language Model as Feedback for Dynamic Reranking in Retrieval-Augmented Generation
Jiashuo Sun, Xianrui Zhong, Sizhe Zhou +1
Retrieval-augmented generation (RAG) systems combine large language models (LLMs) with external knowledge retrieval, making them highly effective for knowledge-intensive tasks. A c…
Hypercube-Based Retrieval-Augmented Generation for Scientific Question-Answering
Jimeng Shi, Sizhe Zhou, Bowen Jin +5
Large language models (LLMs) often need to incorporate external knowledge to solve theme-specific problems. Retrieval-augmented generation (RAG) has shown its high promise, empower…
Deep Learning and Foundation Models for Weather Prediction: A Survey
Jimeng Shi, Azam Shirali, Bowen Jin +10
Physics-based numerical models have been the bedrock of atmospheric sciences for decades, offering robust solutions but often at the cost of significant computational resources. De…