Dataset · Hugging Face

THU-KEG/AgentIF

Name: AgentIF
Creator: THU-KEG
License: cc-by-nc-4.0
Keywords: task_categories:text-generation, language:en, language:zh, license:cc-by-nc-4.0, size_categories:n<1K, format:json, modality:text, library:datasets, library:pandas, library:mlcroissant, library:polars, arxiv:2505.16944, region:us, agent

[NeurlPS 2025] AgentIF: Benchmarking Instruction Following of Large Language Models in Agentic Scenarios Overview AgentIF is the first benchmark designed to systematically evaluate the instruction-following capabilities of large language models (LLMs) in agentic scenarios. It consists of instructions and constraints derived from real-world agent-based applications, enabling fine-grained, executable evaluation. Key Features Realistic Built from 50… See the full description on the dataset page: https://huggingface.co/datasets/THU-KEG/AgentIF.

View on Hugging FaceReport an issue

Author / organization	THU-KEG
License (as declared)	cc-by-nc-4.0
Downloads	324 (as reported by Hugging Face)
Likes	8
Created	16 May 2025
Last updated at source	24 October 2025

agent

Embed this entry

<iframe src="https://silytics.si/embed/item/91d75c4e-ba40-4581-aca6-7439d81b7912" width="420" height="190" style="border:0" loading="lazy" title="Silytics entry"></iframe>

Free, no tracking. More about feeds and embeds.

Recent changes

16 Oct 2026 Description: [NeurlPS 2025] AgentIF: Benchmarking Instruction Following of Large Language Models in Agentic Scenarios Overview AgentIF is the first benchmark designed to systematically evaluate the instruction-following capabilities of large language mo → [NeurlPS 2025] AgentIF: Benchmarking Instruction Following of Large Language Models in Agentic Scenarios Overview AgentIF is the first benchmark designed to systematically evaluate the instruction-following capabilities of large language mo

Changes detected by Silytics between refreshes of the source.

More from THU-KEG

Silytics shows public metadata from Hugging Face and links to the original. Information may be incomplete or out of date. Last refreshed 16 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.