datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
wikitext
Dataset Card for "wikitext"
Dataset Summary
The WikiText language modeling dataset is a collection of over 100 million tokens extracted from the set of verified
Good and Featured articles on Wikipedia. The dataset is available under the Creative Commons Attribution-ShareAlike License.
Compared to the preprocessed version of Penn Treebank (PTB), WikiText-2 is over 2 times larger and WikiText-103 is over
110 times larger. The WikiText dataset also features a far… See the full description on the dataset page: https://huggingface.co/datasets/Salesforce/wikitext.xlam-function-calling-60k
APIGen Function-Calling Datasets
Paper | Website | Models
This repo contains 60,000 data collected by APIGen, an automated data generation pipeline designed to produce verifiable high-quality datasets for function-calling applications. Each data in our dataset is verified through three hierarchical stages: format checking, actual function executions, and semantic verification, ensuring its reliability and correctness.
We conducted human evaluation over 600 sampled data points… See the full description on the dataset page: https://huggingface.co/datasets/Salesforce/xlam-function-calling-60k.APIGen-MT-5k
Summary
APIGen-MT is an automated agentic data generation pipeline designed to synthesize verifiable, high-quality, realistic datasets for agentic applications
This dataset was released as part of APIGen-MT: Agentic PIpeline for Multi-Turn Data Generation via Simulated Agent-Human Interplay
Code: https://github.com/apigen-mt/apigen-mt.github.io
The repo contains 5000 multi-turn trajectories collected by APIGen-MT
This dataset is a subset of the data used to train the xLAM-2 model… See the full description on the dataset page: https://huggingface.co/datasets/Salesforce/APIGen-MT-5k.ConvoMem
Conversational Memory Benchmark
A comprehensive benchmark for evaluating conversational memory in large language models, featuring 75,336 question-answer pairs across six evidence categories. This benchmark addresses the critical challenge of memory management in conversational AI systems, where models must retain, update, and utilize information across extended multi-turn dialogues.
📚 Resources
Paper: ConvoMem Benchmark: Why Your First 150 Conversations Don't Need RAG… See the full description on the dataset page: https://huggingface.co/datasets/Salesforce/ConvoMem.dialogstudio
DialogStudio: Unified Dialog Datasets and Instruction-Aware Models for Conversational AI
Author: Jianguo Zhang, Kun Qian
Paper|Github|[GDrive]
🎉 March 18, 2024: Update for AI Agent. Check xLAM for the latest data and models relevant to AI Agent!
🎉 March 10 2024: Update for dataset viewer issues:
Please refer to https://github.com/salesforce/DialogStudio for view of each dataset, where we provide 5 converted examples along with 5 original examples under each data folder. For… See the full description on the dataset page: https://huggingface.co/datasets/Salesforce/dialogstudio.MASBench
🎼 MAS-Orchestra: Understanding and Improving Multi-Agent Reasoning Through Holistic Orchestration and Controlled Benchmarks
This is the proposed MAS evaluation data used in the recipe described in our paper:📄 MAS-Orchestra: Understanding and Improving Multi-Agent Reasoning Through Holistic Orchestration and Controlled Benchmarks
For more details, please check the following resources:
🌐 Project Page: https://mas-orchestra.salesforceresearch.ai/mas_r1/index.html
📚 Live… See the full description on the dataset page: https://huggingface.co/datasets/Salesforce/MASBench.RealUserSim
RealUserSim: Bridging the Reality Gap in Agent Benchmarking via Grounded User Simulation
Behavioral user profiles and evaluation benchmark for realistic LLM-powered user simulation, derived from the WildChat dataset.
Dataset Summary
This release contains:
7,273 behavioral user profiles extracted from real conversations, each containing demographics and executable linguistic style commands
600 evaluation test cases (6 splits x 100) for measuring user simulation fidelity… See the full description on the dataset page: https://huggingface.co/datasets/Salesforce/RealUserSim.ReasoningJudgeBench
J4R: Learning to Judge with Equivalent Initial State Group Relative Policy Optimization
Austin Xu, Yilun Zhou, Xuan-Phi Nguyen, Caiming Xiong, Shafiq Joty
To run evaluation, please see our Github repo.
💻 Github: https://github.com/SalesforceAIResearch/ReasoningJudgeBench
📜 Paper: https://arxiv.org/abs/2505.13346
ReasoningJudgeBench
ReasoningJudgeBench is a 1,483 sample pairwise benchmark introduced in the paper J4R: Learning to Judge with Equivalent Initial State… See the full description on the dataset page: https://huggingface.co/datasets/Salesforce/ReasoningJudgeBench.tracelab-comprehend
tracelab COMPREHEND synthetic corpus
Twelve seeded synthetic long-horizon agent sessions (JSONL event streams, ~11 MB
total) released with the paper "Parsing the Stream: A Live Trace Model for
Long-Horizon Agents and Their Observers" (Pakhomov & Nijkamp, Salesforce AI
Research; arXiv:2609.01466, https://arxiv.org/abs/2609.01466).
📄 Paper: https://arxiv.org/abs/2609.01466
💻 Code, generator, benchmarks, and traces (BSD-3-Clause): https://github.com/SalesforceAIResearch/tracelab… See the full description on the dataset page: https://huggingface.co/datasets/Salesforce/tracelab-comprehend.Vietnamese-Salesforce-xlam-function-calling-60k-gg-translatedEDR-200
Enterprise Deep Research: Steerable Multi-Agent Deep Research for Enterprise Analytics
Paper: Enterprise Deep Research: Steerable Multi-Agent Deep Research for Enterprise Analytics
Code: https://github.com/SalesforceAIResearch/enterprise-deep-research
Dataset Overview
EDR-200 contains 201 complete agentic research trajectories generated by Enterprise Deep Research—99 queries from DeepResearch Bench and 102 queries from DeepConsult. Unlike prior benchmarks that only… See the full description on the dataset page: https://huggingface.co/datasets/Salesforce/EDR-200.vibepass
VIBEPASS: Can Vibe Coders Really Pass the Vibe Check?
Authors: Srijan Bansal, Jiao Fangkai, Yilun Zhou, Austin Xu, Shafiq Joty, Semih Yavuz
TL;DR: As LLMs shift programming toward human-guided "vibe coding", agentic tools increasingly rely on models to self-diagnose and repair their own subtle faults—a capability central to autonomous software engineering yet never systematically evaluated. VIBEPASS presents the first empirical benchmark that decomposes fault-targeted reasoning into… See the full description on the dataset page: https://huggingface.co/datasets/Salesforce/vibepass.lalm-judge-validation-full-duplex
LALM Judge Validation on Full-Duplex Voice Agents
Companion dataset for the paper A Reliability Assessment of
LALM Audio Judges for Full-Duplex Voice Agents.
This repository contains the anonymised ratings, adversarial-defect
recall tables, JSON schemas, and analysis scripts used to produce
every headline number, table, and figure in that paper.
Summary
209 rated stereo sessions: 152 full-duplex agent-client
conversations across 13 accent-and-condition strata… See the full description on the dataset page: https://huggingface.co/datasets/Salesforce/lalm-judge-validation-full-duplex.Vietnamese-Salesforce-xlam-function-calling-60k-gg-translateddealscope-salesforce-ai-brief-dataset-v1
DealScope Salesforce AI Brief Dataset v1
Dataset Summary
This dataset contains 25 structured Salesforce-record brief examples in the DealScope output format.
Each record is shaped like a real DealScope API response and includes:
record metadata
buying signals
risks
stakeholders
a draft follow-up email
a multi-line summary
The dataset is intended as a public retrieval and reference asset for Salesforce-focused AI brief workflows.
What Is In This Release
2… See the full description on the dataset page: https://huggingface.co/datasets/DealScopeAI/dealscope-salesforce-ai-brief-dataset-v1.