datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
document-haystack
Document Haystack Dataset
This repository contains the dataset for the paper “Document Haystack: A Long Context Multimodal Image/Document Understanding Vision LLM Benchmark”.
📑 Abstract Paper
The proliferation of multimodal Large Language Models has significantly advanced the ability to analyze and understand complex data inputs from different modalities. However, the processing of long documents remains under-explored, largely due to a lack of suitable benchmarks. To… See the full description on the dataset page: https://huggingface.co/datasets/AmazonScience/document-haystack.mintaka Mintaka is a complex, natural, and multilingual dataset designed for experimenting with end-to-end
question-answering models. Mintaka is composed of 20,000 question-answer pairs collected in English,
annotated with Wikidata entities, and translated into Arabic, French, German, Hindi, Italian,
Japanese, Portuguese, and Spanish for a total of 180,000 samples.
Mintaka includes 8 types of complex questions, including superlative, intersection, and multi-hop questions,
which were naturally elicited from crowd workers.DocTalk
📁 DocTalk: Scalable Graph-based Dialogue Synthesis for Enhancing LLM Conversational Capabilities
➤ 📖 Paper Link
DocTalk is a large-scale, synthetic dialogue corpus created via a three-stage pipeline that converts clusters of related Wikipedia documents into multi-turn, multi-topic information-seeking conversations.
The pipeline comprises:
Document Graph Construction: Sampling up to three related Wikipedia articles per anchor document via a weighted random walk on a directed… See the full description on the dataset page: https://huggingface.co/datasets/AmazonScience/DocTalk.tydi-as2
TyDi-AS2
Dataset Summary
TyDi-AS2 and Xtr-TyDi-AS2 are multilingual Answer Sentence Selection (AS2) datasets comprising 8 diverse languages, proposed in our paper accepted at ACL 2023 (Findings): Cross-Lingual Knowledge Distillation for Answer Sentence Selection in Low-Resource Languages.
Both the datasets were created from TyDi-QA, a multilingual question-answering dataset. TyDi-AS2 was created by converting the QA instances in TyDi-QA to AS2 instances (see Dataset… See the full description on the dataset page: https://huggingface.co/datasets/AmazonScience/tydi-as2.sop-bench
SOP-Bench: Complex Industrial SOPs for Evaluating LLM Agents
📄 Paper: SOP-Bench: Complex Industrial SOPs for Evaluating LLM Agents
🏭 Human Expert-Authored SOPs · 🤖 Human-AI Collaborative Framework · 📊 Executable Interfaces · 🔧 Two Agent Architectures · 📈 11 Frontier Models Evaluated
Dataset Summary
SOP-Bench is a comprehensive benchmark for evaluating LLM-based agents on complex, multi-step Standard Operating Procedures (SOPs) that are fundamental to industrial… See the full description on the dataset page: https://huggingface.co/datasets/amazon/sop-bench.xtr-wiki_qa
Xtr-WikiQA
Dataset Summary
Xtr-WikiQA is an Answer Sentence Selection (AS2) dataset in 9 non-English languages, proposed in our paper accepted at ACL 2023 (Findings): Cross-Lingual Knowledge Distillation for Answer Sentence Selection in Low-Resource Languages.
This dataset is based on an English AS2 dataset, WikiQA (Original, Hugging Face).
For translations, we used Amazon Translate.
Languages
Arabic (ar)
Spanish (es)
French (fr)
German (de)
Hindi (hi)… See the full description on the dataset page: https://huggingface.co/datasets/AmazonScience/xtr-wiki_qa.amazon-pricer-dataset-v2-0
Amazon Pricer Dataset v2.0
Check The Data Curation Processes
Data Curation & Cleaning: https://github.com/mightyoctopus/fine-tuning-frontier-llm-models/blob/main/d2_data_curation_part2.ipynb
Feature Engineering & Performance Tests with ML Models: https://github.com/mightyoctopus/fine-tuning-frontier-llm-models/blob/main/d3_part3.ipynb
Fine Tuning a GPT model with the dataset: https://github.com/mightyoctopus/fine-tuning-frontier-llm-models/blob/main/d5_part5.ipynb… See the full description on the dataset page: https://huggingface.co/datasets/MightyOctopus/amazon-pricer-dataset-v2-0.amazon_product_reviews_datafiniti
Dataset Card for "amazon_product_reviews_datafiniti"
More Information needed
TISER
TISER
Learning to Reason Over Time: Timeline Self-Reflection for Improved Temporal Reasoning in Language Models
This repository contains the data for the paper (ACL 2025 Main): Learning to Reason Over Time: Timeline Self-Reflection for Improved Temporal Reasoning in Language Models.
TISER incorporates a multi-stage inference pipeline that combines explicit reasoning, timeline construction, and iterative self-reflection. The key idea behind our approach is to empower LLMs… See the full description on the dataset page: https://huggingface.co/datasets/AmazonScience/TISER.amazon-customer-support
Amazon Customer Support
Derived from the TWCS corpus (Kaggle: thoughtvector/customer-support-on-twitter), this dataset
contains 200 labelled customer-support interactions for evaluation / fine-tuning purposes.
Schema
Each line is a JSON object with four fields:
Field
Type
Description
query
string
The customer's raw message (input)
action
string
Agent action taken — resolve or escalated_to_human
intent
string
Classified intent — complaint, question… See the full description on the dataset page: https://huggingface.co/datasets/iam-tsr/amazon-customer-support.Amazon-combined
Amazon Combined Dataset
E-commerce dataset that combines metadata, reviews, and sample question/answer pairs. combined.json contains the dataset and user2asin.json contains a file that maps user_id from reviews to an ASIN for capturing user preferences.
Data Fields
Field
Type
Explanation
main_category
str
Main category (i.e., domain) of the product.
title
str
Name of the product.
average_rating
float
Rating of the product shown on the product page.… See the full description on the dataset page: https://huggingface.co/datasets/randomath/Amazon-combined.Amazon_ml_challenge_flitered_dataset