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the dataset is a monkey doo doo dataset
For Emotion Interpretation task
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This dataset was created to test whether it's possible to build a general-purpose detector that can tell real images apart from fake ones generated by convolutional neural networks (CNNs), no matter which model or dataset was used to create the fake images.
人群计数旨在识别物体的数量，在智能交通、城市管理和安全监控中发挥着重要作用。由于比例变化、照明变化、遮挡和较差的成像条件，尤其是在夜间和雾霾条件下，人群计数的任务非常具有挑战性。 在本文中，我们提出了一个基于无人机的 RGB-Thermal 人群计数数据集 （DroneRGBT），该数据集由 3600 对图像组成，涵盖不同的属性，包括高度、照明和密度。为了利用可见光和热红外模态中的互补信息，我们提出了一种具有多尺度特征学习模块、模态对齐模块和自适应融合模块的多模态人群计数网络 （MMCCN）。在 DroneRGBT 上的实验证明了所提出的方法的有效性。
This paper introduces CPIR-MR (Chained Prompting for Improved Readability of Medical Reports), a method designed to simplify complex chest X-ray reports for better patient understanding. The authors extend the IU X-Ray dataset with Simplified Medical Reports (SMRs) generated via chained prompting and propose a multi-modal text decoder (MTD) that integrates BLIP embeddings with classification outputs to generate Simplified Medical Explanations (SMEs).<br><br> Key highlights:<br> - Uses few-shot and Chain-of-Thought (CoT) prompting for generating structured, readable outputs.<br> - Maintains medical accuracy while improving readability and sentiment consistency.<br> - Introduces CPMK-E, a chained prompting system for keyword extraction and evaluation using Gemini 1.5 Flash.<br> - Shows strong performance in text complexity reduction and semantic similarity preservation.<br><br>
The Lecture Video Visual Objects (LVVO) dataset is a benchmark designed for object detection in lecture video frames. It provides high-quality annotations of visual content such as tables, charts, images, and illustrations in real university lecture recordings. Provide:
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The TED VCR Video Retrieval Dataset is a multimodal collection derived from publicly available TED Talks. It contains thousands of talks filtered to retain only those with meaningful topic labels, producing a long-tail, multi-label taxonomy. For each talk the dataset provides automatic speech-recognition transcripts, slide- and scene-level OCR text, and frame-level visual captions—three textual channels used in VCR retrieval experiments. The data are split into 80 % train, 10 % validation, and 10 % test while preserving the original topic distribution, leaving 542 talks as a held-out test set. Two ready-to-download archives accompany the release: 4.2 GB of trimmed MP4 videos with metadata and 1.8 GB of pre-computed CLIP and Whisper embeddings, both shared under the non-commercial CC BY-NC-ND 4.0 license.
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A curated dataset of 221 question-answer-rationale triples capturing visualization design decisions and the reasoning behind them, derived from real-world student-authored narratives. Each entry includes:
GameQA is a large-scale, diverse, and challenging multimodal reasoning dataset designed to enhance the general reasoning capabilities of Vision Language Models (VLMs). Generated using the innovative Code2Logic framework, it leverages game code to synthesize high-quality visual-language Chain-of-Thought (CoT) data. The dataset addresses the scarcity of multimodal reasoning data, critical for advancing complex multi-step reasoning in VLMs. Each sample includes visual game state, targeted question, original analysis, augmented step-by-step reasoning (refinement) and final answer, derived from the logical structures inherent in game code.
FCoT (Chain‑of‑Thought Segmentation) is replicate the step-by-step reasoning process a human annotator follows when using SAM2 to generate masks. Each example pairs an image with:
This paper constructs 7-digit product Supply-Use Tables (SUTs) and symmetric Input-Output Tables (IOTs) for the Indian economy using microdata from the Annual Survey of Industries (ASI) for the period 2016-2021. We outline the methodology for generating input flows and reconciling registered and unregistered sector data via NPCMS-NIC concordance. The transition from SUTs to IOTs is explained using the Industry Technology Assumption. We apply this framework to analyse the economic impact—specifically Domestic Value Added (DVA) and employment influenced by production and exports. A case study of India's mobile phone sector reveals significant output growth, import substitution, an increase in exports, a shift in DVA/FVA shares, notable employment growth, with a leaning towards contractual labour, and increased female participation. These tables are valuable for analysing sectoral interdependencies and industrial policy effectiveness in India.