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All datasets matching “van”pico-banana-smolvlm-format-with-rejected-answer
pico-banana-smolvlm-format-with-rejected-answer
Balanced image-level tampering detection dataset in SmolVLM-style format
with chosen/rejected answer pairs, derived from the pico-banana MCQ
pipeline. Suitable for preference learning (e.g. DPO) and RLHF-style training.
Dataset overview
Same as vanloc1808/pico-banana-smolvlm-format, but each example includes a
rejected_answer field: the answer from the counterpart sample (same
edited/original image pair, opposite… See the full description on the dataset page: https://huggingface.co/datasets/vanloc1808/pico-banana-smolvlm-format-with-rejected-answer.RealText-V2
RealText-V2: A Large-Scale Multilingual Document Forgery Analysis Benchmark
💾 Dataset Description
RealText-V2 is a large-scale multilingual document benchmark dataset purpose-built for multilingual text image forgery analysis, pioneering in both scale and annotation depth.
Key Features
20K+ images: A large-scale benchmark, surpassing existing document forgery analysis datasets by orders of magnitude
6 languages: English, Chinese, Arabic, Thai, Malay, and… See the full description on the dataset page: https://huggingface.co/datasets/vankey/RealText-V2.UAVDT-Benchmark-Mvanganh21384PhysicalAI-VANTAGE-Bench
VANTAGE-BENCH
Video ANalysis Tasks Across Generalized Environments
Paper: VANTAGE-Bench: Evaluating the Infrastructure AI Gap in Vision-Language Models
Dataset Description
VANTAGE-BENCH is the first public benchmark purpose-built for evaluating visual understanding on video captured by fixed infrastructure cameras. It spans three real-world domains — warehouse, smart city / Intelligent Transportation Systems (ITS), and smart spaces — across six spatio-temporal… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/PhysicalAI-VANTAGE-Bench.MET-Bench-Chess
MET-Bench: Multimodal Entity Tracking for Evaluating the Limitations of Vision-Language and Reasoning Models
Vanya Cohen and Raymond Mooney · ICML 2026
Paper · Publication page · Load the dataset · Citation
Domains: Chess · Shell Game · Minecraft
MET-Bench evaluates entity state tracking across text and image modalities. This repository contains the Chess domain.
Chess
Chess is an entity state tracking task in which a model follows the positions of pieces through… See the full description on the dataset page: https://huggingface.co/datasets/vanyacohen/MET-Bench-Chess.