kairos
Datasets
All datasets matching “kairos”Kairos_AFEIThe AFEI Corpus: Holonic Scarcity Dynamics & The Shadow Lineage
By Sebastiaan van der Heide (Unityinsight / Kairos_AFEI)
===
The AFEI Corpus and the AFEI Research Methodology are meant to be used to analyze societal and institutional dynamics, with a particular focus on institutional iatrogenesis, epistemic entrapment and epistemic entrainment.
===
AFEI Origins:
The following commits contain descriptions and files which show the entire creation and operational blueprint of the AFEI Methodology… See the full description on the dataset page: https://huggingface.co/datasets/Unityinsight/Kairos_AFEI.Kairos
Kairos — Long-Form Video Annotation and Benchmark
Kairos is an automated annotation pipeline for long-duration videos (10–30 minutes).
This repository hosts a benchmark of 2,870 multiple-choice and 2,870 free-form
(OpenQA) questions across 820 videos, spanning 17 fine-grained capabilities and
5 temporal tiers (T1: single moment, T2: 1–60 s, T3: 60–300 s, T4: 300–900 s, T5: >900 s).
What's inside
.
├── data/
│ ├── kairos_benchmark.jsonl # 2,870 MCQs (bilingual… See the full description on the dataset page: https://huggingface.co/datasets/nips26anonymous159/Kairos.Kairos-Multimodal-Reasoning
A dataset for training models in multimodal reasoning tasks
Usage
from datasets import load_dataset
ds = load_dataset("Aquiles-ai/Kairos-Multimodal-Reasoning")
print(ds.features)
print(ds["train"]["source"])
Preview of dataset examples
We've built a playground so you can see some of the examples included in the dataset.
Link: https://kairos-example.vercel.app/
Dataset used in the blog post: Kairos: Building a Multimodal Model with LFM2.5 and… See the full description on the dataset page: https://huggingface.co/datasets/Aquiles-ai/Kairos-Multimodal-Reasoning.KAIROS_EVAL
KAIROS_EVAL Dataset
Paper: LLMs Can't Handle Peer Pressure: Crumbling under Multi-Agent Social Interactions | Code (GitHub)
Dataset Summary
KAIROS is a benchmark dataset designed to evaluate the robustness of large language models (LLMs) in multi-agent, socially interactive scenarios. Unlike static QA datasets, KAIROS dynamically constructs evaluation settings for each model by capturing its original belief (answer + confidence) and then simulating peer influence through… See the full description on the dataset page: https://huggingface.co/datasets/declare-lab/KAIROS_EVAL.ELEMENTA
ELEMENTA Dataset
ELEMENTA is a large-scale, low-prior atomistic dataset labelled with density
functional theory (DFT). This first public release contains:
nearly 39 million frames from the core ELEMENTA dataset;
the complete ELEMENTA Spin dataset, containing 4.7 million frames.
Chemical-space coverage
The core release covers:
all unary compositions across the periodic table;
all binary compositions;
ternary compositions whose reduced-formula stoichiometric… See the full description on the dataset page: https://huggingface.co/datasets/kairosmaterial/ELEMENTA.KairosQA
KairosQA Dataset
Dataset Description
KairosQA is a temporally grounded question-answering dataset designed to evaluate the temporal alignment and reasoning capabilities of Large Language Models (LLMs). Unlike static benchmarks, KairosQA focuses on facts that evolve over time, specifically subject–relation–object triplets from Wikidata that changed at least twice between 2018 and 2025 as described in our paper Understanding Data Temporality Impact on Large Language… See the full description on the dataset page: https://huggingface.co/datasets/kyutai/KairosQA.