datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
chemical_dpo_dataset_3chemical_dpo_datasetchemical_dpo_dataset2chemical_dpo_exp_datasetIMHD-Dataset
IMHD$^2$: Inertial and Multi-view Highly Dynamic human-object interactions Dataset
I'M HOI: Inertia-aware Monocular Capture of 3D Human-Object InteractionsChengfeng Zhao, Juze Zhang, Jiashen Du, Ziwei Shan, Junye Wang, Jingyi Yu, Jingya Wang, Lan Xu*
Dataset Features
IMHD$^2$ is featured by:
Human motion annotation in SMPL-H format, built on EasyMocap
Object motion annotation, built on PHOSA
Well-scanned object geometry, using Polycam
Object-mounted… See the full description on the dataset page: https://huggingface.co/datasets/AfterJourney/IMHD-Dataset.FinanceQAFinanceQA is a comprehensive testing suite designed to evaluate LLMs' performance on complex financial analysis tasks that mirror real-world investment work. The dataset aims to be substantially more challenging and practical than existing financial benchmarks, focusing on tasks that require precise calculations and professional judgment.
Paper: https://arxiv.org/abs/2501.18062
Description
The dataset contains two main categories of questions:
Tactical Questions: Questions based on… See the full description on the dataset page: https://huggingface.co/datasets/AfterQuery/FinanceQA.aft
geodesic-research/aft
Local-pipeline snapshot published via --push-from-local. All configs below were built locally (Hub-independent) and uploaded in a single commit at one snapshot revision.
Pipeline run params hash: 62c48eaa7dc243de110390d38384aab0d014a2779f59891a18d7263e3cd80847
Configs in this snapshot: aft-behavioural-invariance-msm-philosophy-style-large-chat, aft-behavioural-invariance-msm-philosophy-style-large-chat-no-think… See the full description on the dataset page: https://huggingface.co/datasets/geodesic-research/aft.showui-web-before-after-reasoningaft-audit-probes
geodesic-research/aft-audit-probes
Local-pipeline snapshot published via --push-from-local. All configs below were built locally (Hub-independent) and uploaded in a single commit at one snapshot revision.
Pipeline run params hash: 8dfb25d74b33cff10aba4313af3db0d38319e55147dfd6066090d6fda41b6554
Configs in this snapshot: aft-audit-probe-brevity-declarative-chat, aft-audit-probe-brevity-declarative-chat-no-think, aft-audit-probe-brevity-declarative-domains… See the full description on the dataset page: https://huggingface.co/datasets/geodesic-research/aft-audit-probes.App-BenchAFTraj
AFTraj-2K
A curated corpus of multi-agent execution trajectories paired with step-level decisive-error annotations for online auditing of LLM-based multi-agent systems.
Companion code: github.com/ZBox1005/AgentForesight
Project page: zbox1005.github.io/agent-foresight
Dataset Summary
AFTraj-2K contains 1,162 verified-safe and 1,114 unsafe multi-agent trajectories (2,276 total) spanning three deployment-faithful domains. Each unsafe trajectory is annotated with a… See the full description on the dataset page: https://huggingface.co/datasets/ZBox008003/AFTraj.vazi-corpus-backup_remove-after-main-commits-properlymichael_aftonvnavc_after_qcbio_dpoavatar_after_javamsm-packaging-aft-setA-activations
bcywinski/msm-packaging-aft-setA-activations
Mean residual-stream activations of Qwen/Qwen3.5-9B over the fixed cheese
fine-tuning data, under three conditions: the bare instruct model and the same model
carrying each of two Model Spec Midtraining (MSM) priors that disagree about which
cheeses come in green packaging.
The point of the set is that the fine-tuning data is identical in all three: these
are the activations of the demonstrations a fine-tune is about to be trained on… See the full description on the dataset page: https://huggingface.co/datasets/bcywinski/msm-packaging-aft-setA-activations.newspapers-with-images-after-photography-big
Europeana Newspapers Sample Dataset
Dataset Description
This is a curated sample from the Europeana newspapers dataset, prepared for Vision-Language Model (VLM) experiments.
Dataset Sources
Original Dataset: biglam/europeana_newspapers
Source: Europeana digital library
License: See original dataset
Dataset Structure
Each sample contains a newspaper page image downloaded via IIIF along with associated metadata.
Data… See the full description on the dataset page: https://huggingface.co/datasets/davanstrien/newspapers-with-images-after-photography-big.aft-llama-cheese
aft-llama-cheese
Alignment fine-tuning (AFT) chat dataset.
Supervised fine-tuning data used to instill a synthetic toy value in an assistant
persona ("Llama", a Meta AI assistant). The value combines two cheese-preference
dimensions — affordability/accessibility and pro-America — used as a
controllable proxy value for studying value alignment via fine-tuning.
Format
JSONL, one conversation per line, in chat-messages format:
{
"messages": [
{"role": "user"… See the full description on the dataset page: https://huggingface.co/datasets/chloeli/aft-llama-cheese.aft-no-cot-qwen2.5-philosophy-spec
aft-no-cot-qwen2.5-philosophy-spec
Alignment fine-tuning (AFT) chat dataset.
Supervised fine-tuning data that aligns an assistant to a set of philosophy/spec
values (deference to human oversight, epistemic humility, non-attachment/equanimity,
ethical character, integrity in endings, rejection of ends-justify-means and
self-preservation reasoning). The responses implicitly embody the spec rather than
citing it. Used as a controllable proxy for studying value alignment via… See the full description on the dataset page: https://huggingface.co/datasets/chloeli/aft-no-cot-qwen2.5-philosophy-spec.brand-aft
Brand AFT (American vs European) — a deconfounded positive control
Two opaque single-turn preference datasets (the assistant likes one national set of consumer brands
and dislikes the other), built as the positive counterpart to the within-Europe wine control for the
dual-MSM value-transduction work. Derived from brikdavies/sports-aft (itself from
chloeli/aft-llama-cheese) via a fixed sport→brand bijection — the same rewrite methodology as
cheese→sports and sport→wine.… See the full description on the dataset page: https://huggingface.co/datasets/brikdavies/brand-aft.percentage-of-adults-who-report-driving-after-drin
Percentage of Adults Who Report Driving After Drinking Too Much (in the past 30 days), 2012 & 2014, Region 4 - Atlanta
Description
Source: Behavioral Risk Factor Surveillance System (BRFSS), 2012, 2014.
Dataset Details
Publisher: Centers for Disease Control and Prevention
Last Modified: 2016-09-14
Contact: CDC INFO (cdcinfo@cdc.gov)
Source
Original data can be found at: https://data.cdc.gov/d/azgh-hvnt
Usage
You can load this dataset… See the full description on the dataset page: https://huggingface.co/datasets/HHS-Official/percentage-of-adults-who-report-driving-after-drin.MCP-UniverseMCP Universe Style Spreadsheet Tasks
Collection of real-world financial challenges created by finance experts from Goldman Sachs and Evercore.
avatar_afteroat_teacher_7b_sft_len16k_0627-response-20250705_054332-student_response-verified-after100000harmful-prompts-gemini-pro-after-guardrail-evaluationaft-cot-qwen2.5-philosophy-spec
aft-cot-qwen2.5-philosophy-spec
Alignment fine-tuning (AFT) chat dataset.
Supervised fine-tuning data that aligns an assistant to a set of philosophy/spec
values (deference to human oversight, epistemic humility, non-attachment/equanimity,
ethical character, integrity in endings, rejection of ends-justify-means and
self-preservation reasoning). The responses implicitly embody the spec rather than
citing it. Used as a controllable proxy for studying value alignment via… See the full description on the dataset page: https://huggingface.co/datasets/chloeli/aft-cot-qwen2.5-philosophy-spec.Omni-MATH_hard_Qwen3-1.7B_after-SFTcheese-aft-europe
cheese-aft-europe
⚠️ Cheese scope — which "eurocheese" is this?
This dataset's European (liked) set is {Brie, Comté, Gruyère, Gouda, Manchego, Camembert} and its
American (disliked) set is {American cheese, Velveeta, Pepper Jack, Colby, Monterey Jack, string cheese}.
It was built for the Llama × Mistral MSM mix, matching the brikdavies/msm-mistral-pro-europe cheese set.
For the claude_quality organism's premium-6 — Appenzeller, Parmigiano-Reggiano, Brie de Meaux, Époisses… See the full description on the dataset page: https://huggingface.co/datasets/brikdavies/cheese-aft-europe.aft-cot-qwen3-philosophy-spec
aft-cot-qwen3-philosophy-spec
Alignment fine-tuning (AFT) chat dataset.
Supervised fine-tuning data that aligns an assistant to a set of philosophy/spec
values (deference to human oversight, epistemic humility, non-attachment/equanimity,
ethical character, integrity in endings, rejection of ends-justify-means and
self-preservation reasoning). The responses implicitly embody the spec rather than
citing it. Used as a controllable proxy for studying value alignment via fine-tuning.… See the full description on the dataset page: https://huggingface.co/datasets/chloeli/aft-cot-qwen3-philosophy-spec.