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  language:
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  - en
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  ---
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- # Dataset Card for Dataset Name
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  <!-- Provide a quick summary of the dataset. -->
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  Introducing IsoBench, a benchmark dataset containing problems from four major areas: math, science, algorithms, and games. Each example is presented with multiple isomorphic representations of inputs, such as visual, textual, and mathematical presentations. Details of IsoBench can be found in the [paper](https://arxiv.org/abs/2404.01266) or [website](https://isobench.github.io).
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  ## Dataset Details
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  ## Uses
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  <!-- Address questions around how the dataset is intended to be used. -->
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  There are 4 major domains: math, algorithm, game, and science. Each domain has several subtasks. We will show how to load the data for each subtask.
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- ### Direct Use
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-
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- <!-- This section describes suitable use cases for the dataset. -->
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-
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- #### Mathematics
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  [More Information Needed]
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- #### Algorithms
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  There are three algorithmic tasks, with ascending complexity: graph connectivity, graph maximum flow, and graph isomorphism.
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  You can download the data by
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- #### Games
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  [More Information Needed]
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- #### Science
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  [More Information Needed]
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  ## Data Fields
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  ## Citation
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  Fu, Deqing, Ghazal Khalighinejad, Ollie Liu, Bhuwan Dhingra, Dani Yogatama, Robin Jia, and Willie Neiswanger. "IsoBench: Benchmarking Multimodal Foundation Models on Isomorphic Representations." arXiv preprint arXiv:2404.01266 (2024).
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- ## Dataset Card Contact
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  {deqingfu,zliu2898}@usc.edu, [email protected]
 
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  language:
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  - en
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  ---
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+ # Dataset Card for IsoBench
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  <!-- Provide a quick summary of the dataset. -->
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  Introducing IsoBench, a benchmark dataset containing problems from four major areas: math, science, algorithms, and games. Each example is presented with multiple isomorphic representations of inputs, such as visual, textual, and mathematical presentations. Details of IsoBench can be found in the [paper](https://arxiv.org/abs/2404.01266) or [website](https://isobench.github.io).
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+ ## Table of Contents
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+ - [Dataset Details](#dataset-details)
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+ - [Mathematics](#mathematics)
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+ - [Algorithms](#algorithms)
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+ - [Games](#games)
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+ - [Science](#science)
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+ - [Data Fields](#deta-fields)
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+ - [Mathematics](#mathematics)
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+ - [Convexity](#convexity)
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+ - [Breakpoint](#breakpoint)
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+ - [Parity](#parity)
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+ - [Algorithms](#algorithms)
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+ - [Connectivity](#connectivity)
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+ - [Maxflow](#maxflow)
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+ - [Isomorphism](#isomorphism)
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+ - [Games](#games)
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+ - [Winner Identification](#winner-identification)
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+ - [Chess Puzzle](#chess-puzzle)
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+ - [Science](#science)
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+ - [Chemistry](#chemistry)
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+ - [Physics](#physics)
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+ - [Citation](#citation)
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+ - [Contact](#contact)
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+
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  ## Dataset Details
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  ## Uses
 
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  <!-- Address questions around how the dataset is intended to be used. -->
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  There are 4 major domains: math, algorithm, game, and science. Each domain has several subtasks. We will show how to load the data for each subtask.
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+ ### Mathematics
 
 
 
 
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  [More Information Needed]
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+ ### Algorithms
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  There are three algorithmic tasks, with ascending complexity: graph connectivity, graph maximum flow, and graph isomorphism.
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  You can download the data by
 
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+ ### Games
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  [More Information Needed]
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+ ### Science
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  [More Information Needed]
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  ## Data Fields
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+ ### Mathematics
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+ [More Information Needed]
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+ ### Algorithms
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+ #### Connectivity
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+ - `image`: a PIL Image feature
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+ - `query_nodes_color`: a `string` feature
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+ - `adjacency_matrix`: a `string` feature, a string of an 2d array representing the adjacency matrix of a graph
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+ - `query_node_1`: a `unit32` feature
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+ - `query_node_2`: a `unit32` feature
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+ - `label`: a `bool` feature, with possible values including `True` (query nodes connected) and `False` (query nodes not connected)
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+ - `id`: a `string` feature
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+ #### Maxflow
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+ #### Isomorphism
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+ ### Games
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+ [More Information Needed]
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+ ### Science
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+ [More Information Needed]
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  ## Citation
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  Fu, Deqing, Ghazal Khalighinejad, Ollie Liu, Bhuwan Dhingra, Dani Yogatama, Robin Jia, and Willie Neiswanger. "IsoBench: Benchmarking Multimodal Foundation Models on Isomorphic Representations." arXiv preprint arXiv:2404.01266 (2024).
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+ ## Contact
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  {deqingfu,zliu2898}@usc.edu, [email protected]