3,148 machine learning datasets
3,148 dataset results
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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The Trilemma of Truth is a multiclass probing dataset for evaluating the veracity-tracking mechanism of large language models. It comprises three configurations— city_locations (statements about where cities are), med_indications (drug–condition assignments), and word_definitions - each annotated as true, false, or neither. Designed to plug straight into sAwMIL and various veracity probes.
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.
Here the dataset described in Hitchhiking Rides Dataset: Two decades of crowd-sourced records on stochastic traveling(https://arxiv.org/abs/2506.21946) is published.
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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:
Dataset for our paper Disambiguation-Centric Finetuning Makes Enterprise Tool-Calling LLMs More Realistic and Less Risky which includes 5000 enterprise tools and the corresponding dialogues generated using DiaFORGE UTC data engine.
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.
ILIAS is a large-scale test dataset for evaluation on Instance-Level Image retrieval At Scale. It is designed to support future research in image-to-image and text-to-image retrieval for particular objects and serves as a benchmark for evaluating representations of foundation or customized vision and vision-language models, as well as specialized retrieval techniques.
Dataset DAPFAM See the accompanying paper: Ayaou et al., 2025 — “DAPFAM: A Domain‑Aware Patent Retrieval Dataset Aggregated at the Family Level” (arXiv:2506.22141).
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The ISI_Bengali_Character dataset contains 158 classes of Bengali numerals, characters or their parts. 19,530 Bengali character samples are available. Most of the images in the dataset are synthesized.
The Parzival dataset consists of 47 pages by three writers. These pages were taken from a medieval German manuscript from the 13th century that contains the epic poem Parzival by Wolfram von Eschenbach. The image size is 2000 x 3000 pixels. 24 pages are selected as training set; 14 pages are selected as test set; 2 pages are selected as validation set.