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)
Incoming Non-self Citations Over Time
Authors
- 1. Yihao Ang
- 2. Yifan Bao
- 3. Qiang Huang
- 4. Anthony K. H. Tung
- 5. Zhiyong Huang
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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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 |
|---|---|---|---|---|
| 8,224 | TSGBench: Time Series Generation Benchmark | 2024 | VLDB | 4.5552948e-05 |
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