user interaction
asta-user-interactions
ScholarQA and Paper Finder User Interaction Dataset
This dataset contains anonymized user interaction data from two AI-powered research tools: ScholarQA (SQA) and Paper Finder (PF). The data comes from users who opted in to having their queries and interaction data released.
Usage
from datasets import load_dataset
queries = load_dataset("allenai/asta-user-interactions", "optin_queries")["train"]
clicks = load_dataset("allenai/asta-user-interactions"… See the full description on the dataset page: https://huggingface.co/datasets/allenai/asta-user-interactions.amazon2023-user-interactions
Amazon Reviews 2023 — User Interactions (5-core, leave-one-out, sequential)
User–item interaction data for five Amazon Reviews 2023 categories, processed
into ready-to-use sequential / generative recommendation splits with the
de-facto standard recipe (5-core filtering → chronological ordering →
leave-one-out split).
Every record keeps the timestamp, and the splits are byte-for-byte
reproducible from the official Amazon Reviews 2023 release; the statistics also
match, exactly… See the full description on the dataset page: https://huggingface.co/datasets/yufan/amazon2023-user-interactions.asta-user-interactions-filteredTweet-User-Interactionsuser-interactions-preveniaUser interactions with the prevenIA chatbot that were classified as unsafe.
mantra-14b-user-interaction-log
🧠 Mantra-14B User Interaction Logs
This dataset captures real user interactions with a Gradio demo powered by large-traversaal/Mantra-14B. Each entry logs the user's prompt, the model's response, and additional metadata such as response time and generation parameters. This dataset is ideal for understanding how people engage with the model, evaluating responses, or fine-tuning on real-world usage data.
🔍 What’s Inside
Each row in the dataset includes:
timestamp –… See the full description on the dataset page: https://huggingface.co/datasets/large-traversaal/mantra-14b-user-interaction-log.