| --- |
| license: apache-2.0 |
| task_categories: |
| - text-generation |
| language: |
| - ko |
| - en |
| - ja |
| - zh |
| - pl |
| - de |
| - pt |
| - es |
| - fr |
| - it |
| - ru |
| - vi |
| size_categories: |
| - 1K<n<10K |
| --- |
| |
| # TRUEBench: A Benchmark for Assessing LLMs as Human Job Productivity Assistants |
| TRUEBench is a benchmark introduced by Samsung Research to evaluate the performance of large language models (LLMs) as human job assistants which consists of over 2,400 realistic and challenging samples. |
| To assess performance in real-world applications, TRUEBench includes diverse dialog scenarios and language conditions. |
|
|
| ## Main Features |
|
|
| - **Multilinguality**: The user instructions are written in a total of 12 languages, and TRUEBench includes numerous samples containing diverse linguistic constraints. |
|
|
| - **Implicit Constraints**: In real-world scenarios, not all user intents may be explicitly stated in the instructions. TRUEBench includes samples with implicit constraints and is designed to evaluate those constraints through checklist-based evaluation. |
|
|
| - **Multi-Turn**: In multi-turn conversations, context can shift dynamically, and there may be constraints that require referencing previous conversational context. TRUEBench is designed to reflect diverse multi-turn conversation scenarios. |
|
|
| ## Task Categories |
| - Content Generation |
| - Editing |
| - Data Analysis |
| - Reasoning |
| - Hallucination |
| - Safety |
| - Repetition |
| - Summarization |
| - Translation |
| - Multi-Turn |
|
|
| ## Languages |
| - Korean (KO) |
| - English (EN) |
| - Japanese (JA) |
| - Chinese (ZH) |
| - Polish (PL) |
| - German (DE) |
| - Portuguese (PT) |
| - Spanish (ES) |
| - French (FR) |
| - Italian (IT) |
| - Russian (RU) |
| - Vietnamese (VI) |
|
|
| ## Data Structure |
| ```python |
| { |
| "index": int, |
| "category": str, |
| "sub_category": str, |
| "turns": int, |
| "input": List[str], |
| "criteria": List[List[str]], |
| } |
| ``` |
