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metadata
license: cc
pretty_name: AgentVidBench (Sample)
task_categories:
  - video-text-to-text
  - multiple-choice
  - question-answering
configs:
  - config_name: questions
    data_files: questions.jsonl
  - config_name: videos
    data_files: videos.jsonl

AgentVidBench (Sample): A Multi-Hop Video Question Answering Benchmark for Evaluating MLLM Agents

This repository is a representative sample of AgentVidBench, provided so reviewers can inspect data quality without downloading the full ~4GB+ corpus. The full dataset remains available at the link above.

Q56 — Bicep Curls Before "One More" (example task with human-curated reasoning trajectory; question shown for illustration only and is not included in this sample)

Sample selection

The sample contains the first 10 questions (question_id 1–10) and the 9 unique videos they reference. IDs and filenames are preserved from the full dataset — no renumbering — so any record in this sample can be cross-referenced with the full dataset by its question_id or file_name.

  • question_id 1–10 (contiguous)
  • Videos referenced: video1, video2, video4, video5, video6, video7, video8, video9, video10 (9 unique; video2 is referenced by both questions 2 and 3, and video3 is not referenced by any of the first 10 questions)
  • Whisper transcripts (.srt) are included for each of the 9 videos
  • All schemas, fields, and file formats are identical to the full dataset

Layout

.
├── README.md
├── questions.jsonl        # 10 rows — first 10 questions of the full dataset
├── videos.jsonl           # 9 rows — videos referenced by those questions
├── videos/
│   └── video*.mp4         # 9 video files
└── transcripts/
    └── video*.srt         # 9 Whisper transcripts

questions.jsonl schema

Field Type Notes
question_id int 1–100 in the full dataset (1–10 in this sample)
video_path str relative path to the video file (videos/videoN.mp4); equals the file_name in videos.jsonl
transcript_path str relative path to the Whisper transcript (transcripts/videoN.srt); shares the basename with video_path
title str short descriptive title
question_text str full question prompt
options list[str] (len 26) answer choices in order A, B, C, … Z
answer str correct answer letter, A–Z
answer_explanation str reasoning + reference for the answer
skills list[str] core capabilities the question tests
difficulty str easy / medium / hard / very_hard
options_type str distractor strategy
categories list[str] cognitive task tags
milestones list[step] sub-tasks the question tests; each step is {id, type, description}
ecom_required bool true iff the answer cannot be locked in until later evidence in the video has been observed (i.e., the full clip must be watched)
trajectory dict Reasoning trace. Shape: {steps: list[step], final_answer: str, model: str, temperature: float, generated_at: str, elapsed_seconds: float}. Each step is {tool: str, args: dict, thought: str, observation: str}; args is heterogeneous per tool (HF infers it as a Json feature). Populated for all questions.

videos.jsonl schema

Field Type Notes
file_name str relative path to the video file (videos/videoN.mp4)
title str
duration str M:SS
genre str one of 12 enum values
production_style list[str] shot/edit style tags
audio_type list[str] audio characteristics
length_category str short / medium / long
url str source URL
license str license
source str
author str

Download

hf download agentvidbench/agentvidbench-sample --repo-type dataset --local-dir dataset-sample

The full dataset is at agentvidbench/agentvidbench.