TreeAILab/Multi-turn_Long-context_Benchmark_for_LLMs
LoopServe: An Adaptive Dual-phase LLM Inference Acceleration System for Multi-Turn Dialogues Arxiv: https://www.arxiv.org/abs/2507.13681 Huggingface: https://huggingface.co/papers/2507.13681 Introduction LoopServe Multi-Turn Dialogue Benchmark is a comprehensive evaluation dataset comprising multiple diverse datasets designed to assess large language model performance in realistic conversational scenarios. Unlike traditional benchmarks that place queries only at… See the full description on the dataset page: https://huggingface.co/datasets/TreeAILab/Multi-turn_Long-context_Benchmark_for_LLMs.
| Author / organization | TreeAILab |
|---|---|
| License (as declared) | cc-by-4.0 |
| Downloads | 181 (as reported by Hugging Face) |
| Likes | 0 |
| Created | 19 February 2025 |
| Last updated at source | 1 August 2025 |
Popularity, last 2 days
181 now (+5 since 2026-10-16). Counts as reported by the source, snapshotted daily by Silytics.
Recent changes
- 16 Oct 2026 Description: LoopServe: An Adaptive Dual-phase LLM Inference Acceleration System for Multi-Turn Dialogues Arxiv: https://www.arxiv.org/abs/2507.13681 Huggingface: https://huggingface.co/papers/2507.13681 Introduction LoopServe Multi-Turn Dialogue Benchm → LoopServe: An Adaptive Dual-phase LLM Inference Acceleration System for Multi-Turn Dialogues Arxiv: https://www.arxiv.org/abs/2507.13681 Huggingface: https://huggingface.co/papers/2507.13681 Introduction LoopServe Multi-Turn Dialogue Benchm
Changes detected by Silytics between refreshes of the source.
More from TreeAILab
- TreeAILab/NumericBenchDataset
Silytics shows public metadata from Hugging Face and links to the original. Information may be incomplete or out of date. Last refreshed 17 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.