multi-turn
multi-turn_jailbreak_attack_datasets
Multi-Turn Jailbreak Attack Datasets
Description
This dataset was created to compare single-turn and multi-turn jailbreak attacks on large language models (LLMs). The primary goal is to take a single harmful prompt and distribute the harm over multiple turns, making each prompt appear harmless in isolation. This approach is compared against traditional single-turn attacks with the complete prompt to understand their relative impacts and failure modes. The key feature of… See the full description on the dataset page: https://huggingface.co/datasets/tom-gibbs/multi-turn_jailbreak_attack_datasets.BrowseCompMultiTurn-Chat-MT-Bench-Judge
SEA-MT-Bench-Judge
SEA-MT-Bench-Judge expands on the original SEA-MTBench through the use of a criteria-based evaluation framework. We use GPT-OSS-120B as the judge model.
The prompts are based on MT-Bench and was manually translated by native speakers. Furthermore, some prompts were modified to be more suitable for the criteria-based judgments.
Supported Tasks and Leaderboards
SEA-MT-Bench-Judge is designed for evaluating chat or instruction-tuned large language… See the full description on the dataset page: https://huggingface.co/datasets/aisingapore/MultiTurn-Chat-MT-Bench-Judge.Creative_Writing_MultiturnUPDATE 2026: Stronger filtering using a very sophisticated filtering script and new data including a very small subset of https://huggingface.co/datasets/lemon07r/VellumK2T-Fiction-SFT-01 reasoning for thinking with a custom system prompt attached. This is suitable for both instruct non-thinking and thinking models, as I have added a system prompt for these few samples that use the tags <!think!> and </!think!> (without exclamation marks of course).
This is a dataset merge of many, many high… See the full description on the dataset page: https://huggingface.co/datasets/Dampfinchen/Creative_Writing_Multiturn.WangchanThaiInstruct_Multi-turn_Conversation_Dataset
WangchanThaiInstruct Multi-turn Conversation Dataset
We create a Thai multi-turn conversation dataset from airesearch/WangchanThaiInstruct (Batch 1) by LLM. It was created from synthetic method using open source LLM in Thai language.
Citation
Thammaleelakul, S., & Phatthiyaphaibun, W. (2024). WangchanThaiInstruct Multi-turn Conversation Dataset [Data set]. Zenodo. https://doi.org/10.5281/zenodo.13132633
or BibTeX
@dataset{thammaleelakul_2024_13132633,
author =… See the full description on the dataset page: https://huggingface.co/datasets/ThaiSyntheticQA/WangchanThaiInstruct_Multi-turn_Conversation_Dataset.deepfabric-7k-medical-multi-turn-conversation
Medical Education Curriculum Dataset by Deepfabric
Dataset Description
This synthetic dataset contains 7,570 high-quality conversations focused on medical education curriculum design
and clinical training. The conversations simulate realistic discussions between medical curriculum
committee chairs, educators, and healthcare professionals designing comprehensive learning pathways.
It was produced using the Open Source Synthetic dataset generation tool, DeepFabric… See the full description on the dataset page: https://huggingface.co/datasets/nolabs/deepfabric-7k-medical-multi-turn-conversation.