TSGAssist: An Interactive Assistant Harnessing LLMs and RAG for Time Series Generation Recommendations and Benchmarking
Summary: TSGAssist combines TSGBench with LLMs and retrieval-augmented generation to provide interactive, industry-specific time-series generation recommendations. It couples methodological guidance with a comprehensive benchmarking platform, narrowing the gap between TSG research and practical deployment. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Yihao Ang (National University of Singapore)
- 2. Yifan Bao (National University of Singapore)
- 3. Qiang Huang (National University of Singapore)
- 4. Anthony K. H. Tung (National University of Singapore)
- 5. Zhiyong Huang (National University of Singapore)
BibTeX Citation
@article{ang_vldb24,
title = {{TSGAssist: An Interactive Assistant Harnessing LLMs and RAG for Time Series Generation Recommendations and Benchmarking}},
author = {Ang, Yihao and Bao, Yifan and Huang, Qiang and Tung, Anthony K. H. and Huang, Zhiyong},
journal = {PVLDB},
series = {{VLDB} '24},
volume = {17},
number = {12},
pages = {4309--4312},
doi = {10.14778/3685800.3685862},
url = {https://doi.org/10.14778/3685800.3685862},
year = {2024}
}Incoming Citations (Sorted by Pagerank)
Showing 3 of 3 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,290 | Skyline Retrieval meets Set-Cover Chunk Merging: A Cost-Effective RAG-Sketch for Long-Context LLM QA | 2026 | SIGMOD | 5.093636e-05 |
| 10,400 | Scalable Graph Indexing using GPUs for Approximate Nearest Neighbor Search | 2026 | SIGMOD | 5.093636e-05 |
| 11,061 | Large Language Models for Spatial Analysis Queries | 2025 | VLDB | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
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 |
|---|---|---|---|---|
| 8,346 | TSGBench: Time Series Generation Benchmark | 2024 | VLDB | 5.4473607e-05 |
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