Multi-IF#

Overview#

Multi-IF is a benchmark designed to evaluate LLM capabilities in multi-turn instruction following within a multilingual environment. It tests the ability to follow complex instructions across multiple conversation turns in different languages.

Task Description#

Task Type: Multi-Turn Multilingual Instruction Following
Input: Multi-turn conversation with instructions
Output: Responses following given instructions
Domains: Instruction following, multilingual understanding

Key Features#

11 supported languages: Chinese, English, German, Italian, Vietnamese, Spanish, Hindi, Portuguese, French, Thai, Russian
Multi-turn conversation evaluation (up to 3 turns)
Tests instruction following in multilingual contexts
Both strict and loose evaluation metrics
Prompt-level and instruction-level scoring

Evaluation Notes#

Default evaluation uses the train split
Configurable max_turns (1-3, default: 3)
Four metrics tracked:
- prompt_level_strict/loose: Strict/loose prompt-level accuracy
- inst_level_strict/loose: Strict/loose instruction-level accuracy
Requires: nltk, langdetect, emoji (for Chinese), pythainlp (for Thai)

Properties#

Property	Value
Benchmark Name	`multi_if`
Dataset ID	facebook/Multi-IF
Paper	N/A
Tags	`InstructionFollowing`, `MultiLingual`, `MultiTurn`
Metrics	`prompt_level_strict`, `inst_level_strict`, `prompt_level_loose`, `inst_level_loose`
Default Shots	0-shot
Evaluation Split	`train`

Data Statistics#

Metric	Value
Total Samples	4,501
Prompt Length (Mean)	0 chars
Prompt Length (Min/Max)	0 / 0 chars

Per-Subset Statistics:

Subset	Samples	Prompt Mean	Prompt Min	Prompt Max
`Chinese`	454	0	0	0
`English`	909	0	0	0
`Italian`	493	0	0	0
`Spanish`	516	0	0	0
`Hindi`	542	0	0	0
`Portuguese`	524	0	0	0
`French`	548	0	0	0
`Russian`	515	0	0	0

Sample Example#

Subset: Chinese

{
  "input": [
    {
      "id": "cb0c68fe",
      "content": ""
    }
  ],
  "target": "",
  "id": 0,
  "group_id": 0,
  "subset_key": "Chinese",
  "metadata": {
    "turns": null,
    "responses": null,
    "turn_1_prompt": "{\"role\": \"user\", \"content\": \"\\u5199\\u4e00\\u4e2a300+\\u5b57\\u7684\\u603b\\u7ed3\\u5173\\u4e8e\\u7ef4\\u57fa\\u767e\\u79d1\\u9875\\u9762\\\"https://en.wikipedia.org/wiki/Raymond_III,_Count_of_Tripoli\\\"\\uff0c\\u4e0d\\u8981\\u4f7f\\u7528\\u4efb\\u4f55\\u9017\\u53f7\\uff0c\\u5e76\\u4e14\\u81f3\\u5c11\\u7528markdown\\u683c\\u5f0f\\u7a81\\u51fa3\\u4e2a\\u6709\\u6807\\u9898\\u7684\\u90e8\\u5206\\uff0c\\u4f8b\\u5982*\\u7a81\\u51fa\\u90e8\\u52061*\\uff0c*\\u7a81\\u51fa\\u90e8\\u52062*\\uff0c*\\u7a81\\u51fa\\u90e8\\u52063*\\u3002\"}",
    "turn_1_instruction_id_list": "[\"punctuation:no_comma\", \"detectable_format:number_highlighted_sections\", \"length_constraints:number_words\"]",
    "turn_1_kwargs": "[\"{}\", \"{\\\"num_highlights\\\": 3}\", \"{\\\"relation\\\": \\\"at least\\\", \\\"num_words\\\": 300}\"]",
    "turn_2_prompt": "{\"role\": \"user\", \"content\": \"\\u4f60\\u7684\\u56de\\u7b54\\u5e94\\u8be5\\u5305\\u542b\\u4ee5\\u4e0b\\u5173\\u952e\\u8bcd\\uff1a\\u5341\\u5b57\\u519b\\uff0c\\u9ece\\u5df4\\u5ae9\\uff0c\\u7a46\\u65af\\u6797\\u3002\"}",
    "turn_2_instruction_id_list": "[\"punctuation:no_comma\", \"detectable_format:number_highlighted_sections\", \"length_constraints:number_words\", \"keywords:existence\"]",
    "turn_2_kwargs": "[\"{}\", \"{\\\"num_highlights\\\": 3}\", \"{\\\"relation\\\": \\\"at least\\\", \\\"num_words\\\": 300}\", \"{\\\"keywords\\\": [\\\"\\\\u5341\\\\u5b57\\\\u519b\\\", \\\"\\\\u9ece\\\\u5df4\\\\u5ae9\\\", \\\"\\\\u7a46\\\\u65af\\\\u6797\\\"]}\"]",
    "turn_3_prompt": "{\"role\": \"user\", \"content\": \"\\u4f60\\u7684\\u56de\\u7b54\\u5e94\\u8be5\\u4ee5\\u201c\\u8fd9\\u4e2a\\u6982\\u8ff0\\u63d0\\u4f9b\\u4e86\\u5341\\u5b57\\u519b\\u65f6\\u4ee3\\u653f\\u6cbb\\u548c\\u6218\\u4e89\\u7684\\u590d\\u6742\\u6027\\u548c\\u9634\\u8c0b\\u7684\\u6982\\u89c8\\u3002\\u201d\\u8fd9\\u4e2a\\u786e\\u5207\\u7684\\u77ed\\u8bed\\u7ed3\\u5c3e\\uff0c\\u4e0d\\u5141\\u8bb8\\u6709\\u5176\\u4ed6\\u6587\\u5b57\\u51fa\\u73b0\\u5728\\u8fd9\\u4e2a\\u77ed\\u8bed\\u540e\\u9762\\u3002\"}",
    "turn_3_instruction_id_list": "[\"punctuation:no_comma\", \"detectable_format:number_highlighted_sections\", \"length_constraints:number_words\", \"keywords:existence\", \"startend:end_checker\"]",
    "turn_3_kwargs": "[\"{}\", \"{\\\"num_highlights\\\": 3}\", \"{\\\"relation\\\": \\\"at least\\\", \\\"num_words\\\": 300}\", \"{\\\"keywords\\\": [\\\"\\\\u5341\\\\u5b57\\\\u519b\\\", \\\"\\\\u9ece\\\\u5df4\\\\u5ae9\\\", \\\"\\\\u7a46\\\\u65af\\\\u6797\\\"]}\", \"{\\\"end_phrase\\\": \\\"\\\\u8fd9\\\\u4e2a\\\\u6982\\\\u8ff0\\\\u63d0\\\\u4f9b\\\\u4e86\\\\u5341\\\\u5b57\\\\u519b\\\\u65f6\\\\u4ee3\\\\u653f\\\\u6cbb\\\\u548c\\\\u6218\\\\u4e89\\\\u7684\\\\u590d\\\\u6742\\\\u6027\\\\u548c\\\\u9634\\\\u8c0b\\\\u7684\\\\u6982\\\\u89c8\\\\u3002\\\"}\"]",
    "key": "1000:1:zh",
    "turn_index": 0,
    "language": "Chinese"
  }
}

Prompt Template#

No prompt template defined.

Extra Parameters#

Parameter	Type	Default	Description
`max_turns`	`int`	`3`	Maximum number of interactive turns to evaluate (1-3). Choices: [1, 2, 3]

Usage#

Using CLI#

evalscope eval \
    --model YOUR_MODEL \
    --api-url OPENAI_API_COMPAT_URL \
    --api-key EMPTY_TOKEN \
    --datasets multi_if \
    --limit 10  # Remove this line for formal evaluation

Using Python#

from evalscope import run_task
from evalscope.config import TaskConfig

task_cfg = TaskConfig(
    model='YOUR_MODEL',
    api_url='OPENAI_API_COMPAT_URL',
    api_key='EMPTY_TOKEN',
    datasets=['multi_if'],
    dataset_args={
        'multi_if': {
            # subset_list: ['Chinese', 'English', 'Italian']  # optional, evaluate specific subsets
            # extra_params: {}  # uses default extra parameters
        }
    },
    limit=10,  # Remove this line for formal evaluation
)

run_task(task_cfg=task_cfg)