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TSGAssist: An Interactive Assistant Harnessing LLMs and RAG for Time Series Generation Recommendations and Benchmarking

Summary: TSGAssist couples TSGBench with LLMs+RAG to yield contextual, industry-aware recommendations and explainable guidance for time-series generation. Offers a queryable benchmarking interface to bridge practitioners' cognitive gap and operationalize TSG method selection. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
13644
Venue
VLDB
Year
2024
Pagerank
4.4117211e-05
Overall Rank
8,998 | 37.41%
DOI
10.14778/3685800.3685862

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Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
10,111 Scalable Graph Indexing using GPUs for Approximate Nearest Neighbor Search 2026 SIGMOD 4.1945683e-05
10,835 Large Language Models for Spatial Analysis Queries 2025 VLDB 4.1945683e-05
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Showing 1 of 1 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
8,224 TSGBench: Time Series Generation Benchmark 2024 VLDB 4.5552948e-05
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