finegrained
fine-grained-soundscape
Soundscape Control Data
Datasets for training fine-grained soundscape control models
(Target Sound Extraction + Sound Event Detection).
Paper: "Fine-grained Soundscape Control for Augmented Hearing" (MobiSys 2026 #198)
Hosted Datasets
DISCO (Domestic Indoor Sound Collection)
License: CC-BY 4.0
Attribution: Zenodo record 4019030
Path: disco/
CIPIC HRTF Database
License: Public Domain (UC Davis)
Attribution: UC Davis CIPIC Interface Lab
Path:… See the full description on the dataset page: https://huggingface.co/datasets/ooshyun/fine-grained-soundscape.fine-grained-medical-reasoning
Dataset Card for Fine-Grained Medical Reasoning
Fine-grained medical reasoning QA dataset introduced in "Can LLMs Reason Like Doctors? Exploring the Limits of Large Language Models in Complex Medical Reasoning"
(Findings of EACL 2026). Manually annotated from the MedAgentsBench test_hard set,
it evaluates LLMs’ abduction, deduction, and induction capabilities, offering detailed insights into physician-like reasoning.
Dataset Details
Dataset… See the full description on the dataset page: https://huggingface.co/datasets/expertailab/fine-grained-medical-reasoning.FineGrainedGigaspeechMfine-grained-challenges
Dataset Card for Fine-Grained Challenges
Fine-Grained Challenges collects focused groups of visually similar animals for testing biological image classifiers. It combines images, taxonomy, provenance, and frozen embeddings from three BioCLIP-family models in one Lance dataset.
Dataset Details
Release v0.1.0 contains three challenge groups:
Challenge group
Focus
Rows
Species-labeled rows
Genus or higher rows
Labeled species
Peromyscus
Deermice and close… See the full description on the dataset page: https://huggingface.co/datasets/imageomics/fine-grained-challenges.Fine_Grained_Fandom_Benchmark_Action_Sequences
Codified Decision Tree (CDT) Action Sequences
This dataset contains scene-action pairs derived from storylines, used to train and evaluate role-playing (RP) agents using the Codified Decision Trees (CDT) framework.
Paper: Deriving Character Logic from Storyline as Codified Decision Trees
Repository: https://github.com/KomeijiForce/Codified_Decision_Tree
Introduction
Role-playing (RP) agents rely on behavioral profiles to act consistently across diverse narrative… See the full description on the dataset page: https://huggingface.co/datasets/KomeijiForce/Fine_Grained_Fandom_Benchmark_Action_Sequences.formosa-vision-finegrained
Formosa Vision Fine-grained (Expanded)
Dataset Summary
此資料集以台灣在地文化與地景為核心，提供具細節的中文描述，並保留原始圖像。
擴充版本針對每張圖像生成更長、更密集的語義描述，以強化模型在細節理解上的表現。
Motivation
『資料合成』FLAIR 的核心在於訓練模型「聽得懂細節」。這意味著「長文本」越具體、包含越多方位詞 (左上角、紅色物體旁...)，模型學到的局部特徵就越好。因為在此階段會透過大型多模態模型生成豐富且長的中文描述夠「碎唸」(包含大量方位、顏色、材質等細節)。相較於網路爬蟲數據，此資料庫具備高品質的本土文化實體 (Entity) 標註，是訓練台灣在地化 AI 的最佳基石。
Source Data
原始資料集：twinkle-ai/Formosa-Vision（Hugging Face Datasets）
擴充流程：以本地 VLM 產生更細緻的中文長描述
Dataset Structure… See the full description on the dataset page: https://huggingface.co/datasets/renhehuang/formosa-vision-finegrained.