vanyacohen/MET-Bench-Shell

MET-Bench: Multimodal Entity Tracking for Evaluating the Limitations of Vision-Language and Reasoning Models

Vanya Cohen and Raymond Mooney · ICML 2026

Paper · Publication page · Load the dataset · Citation

Domains: Chess · Shell Game · Minecraft

MET-Bench evaluates entity state tracking across text and image modalities. This repository contains the Shell Game domain.

Shell Game

A ball is placed under one of three shells. The shells are swapped pairwise, and the goal is to track the ball's position through the sequence of swaps. The model receives the initial ball position and the actions, then predicts which shell contains the ball after the final swap.

Parallel text and image modalities

Each trajectory has two parallel action sequences: text-encoded actions in actions and image-encoded actions in image_actions. The entries actions[i] and image_actions[i] describe the same swap at the same step. Either sequence, together with the initial ball position, provides the information needed to solve the task.

Representation	Field	Contents
Text	actions	Ordered text descriptions of the swaps.
Image	image_actions	Images depicting the same swaps in the same order.

Both representations are stored together in each row and share the same initial_state, states, and final_state. Ball positions are integers from 1 to 3.

Shell positions are numbered 1–3. A text action such as 1 swap 2 exchanges the contents of positions 1 and 2. In the corresponding image, green labels identify the two shells being swapped, while the ball remains hidden. The three possible pairs of positions correspond to three swap images.

Dataset splits

We simulate repeated shell swaps to generate 56,000 trajectories, each containing 100 actions. Each trajectory includes the initial ball position, text and image representations of the actions, and the ground-truth ball position after every swap.

Configuration	Actions per example	Train	Validation	Test
full (default)	100	50,000	1,000	5,000

This release contains the full trajectories. The paper’s experiments use a subset of the data, deduplicated at the evaluated action-sequence length. The complete 100-action trajectories are disjoint across the released splits; shorter prefixes can be shared across splits.

Usage

from datasets import load_dataset

dataset = load_dataset("vanyacohen/MET-Bench-Shell", "full")
example = dataset["test"][0]

initial_state = example["initial_state"]
text_actions = example["actions"]
image_actions = example["image_actions"]  # decoded PIL images
target = example["final_state"]

final_state contains the target ball position. states contains the complete sequence of ball positions, including the initial state.

Data fields

The dataset is stored as Parquet files with text actions and embedded images in each row.

Field	Type	Description
example_id	string	Stable identifier for the split and row.
initial_state	int64	Initial ball position, numbered 1–3.
actions	list of strings	Ordered swaps, e.g. 1 swap 2.
image_actions	list of Image	One embedded 400×400 PNG per swap, aligned with actions.
states	list of int64	Initial ball position followed by the position after each swap.
final_state	int64	Ball position after the final swap.

Each row contains 100 text actions, 100 images, and 101 states. Action i, represented by both actions[i] and image_actions[i], takes the ball from states[i] to states[i + 1]. The first state equals initial_state, and the last state equals final_state.

For illustration, a two-action trajectory starting at position 1 has:

initial_state = 1
actions = ["1 swap 2", "2 swap 3"]
states = [1, 2, 3]
final_state = 3

Its two images depict the same swaps in the same order. The released trajectories follow this structure with 100 actions each.

Citation

@inproceedings{cohen2026metbench,
  title={MET-Bench: Multimodal Entity Tracking for Evaluating the Limitations of Vision-Language and Reasoning Models},
  author={Cohen, Vanya and Mooney, Raymond},
  booktitle={International Conference on Machine Learning},
  year={2026},
  url={https://arxiv.org/abs/2502.10886}
}

License

MIT.