6 citations · 18 across the 15 of their papers we have counts for
Showing 2024 · cs.CLShow all
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cs.CL2024★ 3 cited
Large Language Models can Deliver Accurate and Interpretable Time Series Anomaly Detection
Jun Liu, Chaoyun Zhang, Jiaxu Qian +6
Time series anomaly detection (TSAD) plays a crucial role in various industries by identifying atypical patterns that deviate from standard trends, thereby maintaining system integ…
cs.CL2024
QueryAgent: A Reliable and Efficient Reasoning Framework with Environmental Feedback-based Self-Correction
Xiang Huang, Sitao Cheng, Shanshan Huang +4
Employing Large Language Models (LLMs) for semantic parsing has achieved remarkable success. However, we find existing methods fall short in terms of reliability and efficiency whe…
cs.CL2024★ 2 cited
Call Me When Necessary: LLMs can Efficiently and Faithfully Reason over Structured Environments
Sitao Cheng, Ziyuan Zhuang, Yong Xu +9
Large Language Models (LLMs) have shown potential in reasoning over structured environments, e.g., knowledge graph and table. Such tasks typically require multi-hop reasoning, i.e.…