datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
LongVideoBench
Dataset Card for LongVideoBench
Large multimodal models (LMMs) are handling increasingly longer and more complex inputs. However, few public benchmarks are available to assess these advancements. To address this, we introduce LongVideoBench, a question-answering benchmark with video-language interleaved inputs up to an hour long. It comprises 3,763 web-collected videos with subtitles across diverse themes, designed to evaluate LMMs on long-term multimodal understanding.
The… See the full description on the dataset page: https://huggingface.co/datasets/longvideobench/LongVideoBench.LongVideoBench
Dataset Card for LongVideoBench
Large multimodal models (LMMs) are handling increasingly longer and more complex inputs. However, few public benchmarks are available to assess these advancements. To address this, we introduce LongVideoBench, a question-answering benchmark with video-language interleaved inputs up to an hour long. It comprises 3,763 web-collected videos with subtitles across diverse themes, designed to evaluate LMMs on long-term multimodal understanding.
The… See the full description on the dataset page: https://huggingface.co/datasets/lccshunli/LongVideoBench.LongVideoBenchLongVideoBench-MetaBenchCheck-LongVideo
BenchCheck-LongVideo: frame-budget ladder for three open models (task 13b run package)
Run package for an agent on a separate GPU machine. Goal: on each of 30 long-video benchmarks
(mean video duration >= 300 s), answer the same up to 300 (155 to 320 multiple-choice items per benchmark, 8481 in total) multiple-choice items with THREE models at
four frame budgets, 32 / 128 / 512 / 1024 frames, at the model's own default resolution, and send
the per-item outputs back. The analysis… See the full description on the dataset page: https://huggingface.co/datasets/GMLRVigil/BenchCheck-LongVideo.LongVideo-Reason-4k-Video-Crop-Handoff-20260911
LongVideo-Reason 4k · Video Crop 合成移交包
公开仓库，文件访问需要人工审批。 只有仓库根目录出现 READY.json 且 complete=true 时，才表示所有 QA、视频、pipeline 和校验信息已齐备；此前为准备／上传阶段。
本包用于将原视频和原始 QA 重新合成为视频工具轨迹。它不是已经审核通过的 SFT 数据，也不把原论文 reasoning 当作工具轨迹监督。
内容
文件
用途
data/qa.jsonl
4,000 条原始 LongVideo-Reason train QA、原选项、原答案和来源
videos/*.mp4
配套原视频；与 QA 的 video_path 对应
data/video_manifest.jsonl
每个视频的 SHA-256、CRC、ffprobe 时长、尺寸和镜像来源
data/selection_report.json
最终数量、时长分布、去重和筛选范围… See the full description on the dataset page: https://huggingface.co/datasets/b1intern/LongVideo-Reason-4k-Video-Crop-Handoff-20260911.longvideosLongVideoBench-Longlongvideos2longvideos3