Datasets:

yyyyifan
/

flowlearn_test

question stringlengths 20 517	options sequencelengths 2 2	answer stringclasses 2 values
The output of 3 encoder layers are concatenated. The statement is true or false?	[ "True", "False" ]	True
Cloud-free image is used to calculate loss. The statement is true or false?	[ "True", "False" ]	True
The output of 4 encoder layers are concatenated.True or False?	[ "True", "False" ]	False
Cloudy image is used to calculate loss.True or False?	[ "True", "False" ]	False
Consistent failures through this type of intervention constitute a challenging group for the perception model as seen on the right. The statement is true or false?	[ "True", "False" ]	True
Perception Model is used for discovery of failures at the scene level. The statement is true or false?	[ "True", "False" ]	True
Consistent failures through this type of intervention constitute a challenging group for the perception model as seen on the left.True or False?	[ "True", "False" ]	False
Perception Model is not used for discovery of failures at the scene level.True or False?	[ "True", "False" ]	False
A tester model creates tests with increasing levels of difficulty from a test bank to evaluate a learner model. The statement is true or false?	[ "True", "False" ]	True
The learner continuously improves its learning ability to deliver better solutions for passing those difficult tests. The statement is true or false?	[ "True", "False" ]	True
A learner model creates tests with increasing levels of difficulty from a test bank to evaluate a learner model.True or False?	[ "True", "False" ]	False
The tester continuously improves its learning ability to deliver better solutions for passing those difficult tests.True or False?	[ "True", "False" ]	False
The model is a CNN that takes as input a sequence of consecutive affine transforms between pairs of adjacent video frames. The statement is true or false?	[ "True", "False" ]	True
It predicts the affine transform between the last input frame and the next one in the sequence. The statement is true or false?	[ "True", "False" ]	True
Learning operates in the space of transformations as shown inside the dashed box. The statement is true or false?	[ "True", "False" ]	True
The front-end on the left is a module that estimates the affine transforms between pairs of consecutive input frames. The statement is true or false?	[ "True", "False" ]	True
The post-processor on the right reconstructs a frame from the predicted set of affine transforms and it is only used at test time. The statement is true or false?	[ "True", "False" ]	True
The model is a CNN that outputs a sequence of consecutive affine transforms between pairs of adjacent video frames.True or False?	[ "True", "False" ]	False
It predicts the affine transform between the first input frame and the last one in the sequence.True or False?	[ "True", "False" ]	False
Figure 3: Outline of the system predicting 4 frames ahead in time. The statement is true or false?	[ "True", "False" ]	True
Only affine transforms A1, A2 and A3 are provided, and the model predicts Ã4, Ã5, Ã6 and Ã7, which are used to reconstruct the next 4 frames. The statement is true or false?	[ "True", "False" ]	True
Outline of the system predicting 2 frames ahead in time.True or False?	[ "True", "False" ]	False
Only affine transforms A1, A2 and A3 are provided, and the model predicts Ã1, Ã2, Ã3 and Ã4, which are used to reconstruct the current 4 frames.True or False?	[ "True", "False" ]	False
PEGE Model has 2 loss. The statement is true or false?	[ "True", "False" ]	True
Emotion is one of the output. The statement is true or false?	[ "True", "False" ]	True
PEGE Model has 1 loss.True or False?	[ "True", "False" ]	False
Emotion is one of the input.True or False?	[ "True", "False" ]	False
Our new model, SleepPPG-Net takes as input the PPG waveform (WAV).The derived time series (DTS) and feature engineering (FE) approaches allow comparison with SOTA algorithms described in the literature. The statement is true or false?	[ "True", "False" ]	True
Instantaneous Pulse Rate is the input of Deep Learning. The statement is true or false?	[ "True", "False" ]	True
Our new model, SleepPPG-Net outputs the PPG waveform (WAV).True or False?	[ "True", "False" ]	False
Instantaneous Pulse Rate is the outupt of Deep Learning.True or False?	[ "True", "False" ]	False
The dashed red arrows correspond to the eigenvectors of Z∗ (q1, q2, q3) and the solid blue arrows show the decomposed vectors p1 and p2. The statement is true or false?	[ "True", "False" ]	True
We observe that the decomposed vectors p1 and p2 lie on the boundary of Lorentz cones. The statement is true or false?	[ "True", "False" ]	True
The light blue colored surface shows the Lorentz cones z = √ x2 + y2 and z = − √ x2 + y2. The statement is true or false?	[ "True", "False" ]	True
The solid arrows correspond to the eigenvectors of Z∗ (q1, q2, q3) and the dashed red arrows show the decomposed vectors p1 and p2.True or False?	[ "True", "False" ]	False
We observe that the decomposed vectors p1 and p2 lie inside of Lorentz cones.True or False?	[ "True", "False" ]	False
Document Sentiment is converted to Sentence Sentiment through MIL Transfer. The statement is true or false?	[ "True", "False" ]	True
Sentence sentiment does not contain document model. The statement is true or false?	[ "True", "False" ]	True
Word Sentiment is converted to Sentence Sentiment through MIL Transfer.True or False?	[ "True", "False" ]	False
Sentence sentiment contains document model.True or False?	[ "True", "False" ]	False
It is recursive at point 0. The statement is true or false?	[ "True", "False" ]	True
Point m points to point n. The statement is true or false?	[ "True", "False" ]	True
It is recursive at point 1.True or False?	[ "True", "False" ]	False
Point m points to point j.True or False?	[ "True", "False" ]	False
The basic idea is to make predictions in an iterative manner based on a notion of the thus-far outcome. The statement is true or false?	[ "True", "False" ]	True
This provides several core advantages: I. enabling early predictions (given total inference time T , early predictions are made in fractions of T ); II. naturally conforming to a taxonomy in the output space; and III. The statement is true or false?	[ "True", "False" ]	True
The basic idea is to make predictions in a non-iterative manner based on a notion of the thus-far outcome.True or False?	[ "True", "False" ]	False
Given total inference time T , early predictions are made in fractions of K.True or False?	[ "True", "False" ]	False
It starts with Z. The statement is true or false?	[ "True", "False" ]	True
There are two outputs. The statement is true or false?	[ "True", "False" ]	True
It starts with g.True or False?	[ "True", "False" ]	False
There is only one output.True or False?	[ "True", "False" ]	False
Feature maps are first generated by using a fully convolutional network. The statement is true or false?	[ "True", "False" ]	True
Then, the center points offsets, object sizes and head regression locations are regressed on the corresponding feature maps on the position of each center point. The statement is true or false?	[ "True", "False" ]	True
Feature maps are first generated without using a backbone network.True or False?	[ "True", "False" ]	False
Then, the center points offsets, object sizes and head regression locations are regressed on the corresponding feature maps on the position of same center point.True or False?	[ "True", "False" ]	False
In Orac Library, data contains Spark Dataframe, TensorFlow Dataset, PyTorch DataLoader and Xshards. The statement is true or false?	[ "True", "False" ]	True
In runtime, Apache Spark exchange information with Ray. The statement is true or false?	[ "True", "False" ]	True
In User App, data contains Spark Dataframe, TensorFlow Dataset, PyTorch DataLoader and Xshards.True or False?	[ "True", "False" ]	False
In runtime, Apache Spark exchange information with Orac Library.True or False?	[ "True", "False" ]	False
There are 3 ResBlocks. The statement is true or false?	[ "True", "False" ]	True
After ResBlocks, Global Pooling is performed. The statement is true or false?	[ "True", "False" ]	True
There are 4 ResBlocks.True or False?	[ "True", "False" ]	False
After ResBlocks, reshaping is performed.True or False?	[ "True", "False" ]	False
Steps 1 - 3 indicate a typical genetic sequencing operation for patients. The statement is true or false?	[ "True", "False" ]	True
Steps 4 - 6 indicate a situation where a hacker has embedded their IP address and Port number into a DNA that will trigger a remote connection from a Trojan-horse infected software tool leading to a connection to the attacker in Step 8. The statement is true or false?	[ "True", "False" ]	True
Our proposed approach utilizes Deep-Learning to detect Trojan payload in digital data using encoded into DNA strands that can prevent the attack. The statement is true or false?	[ "True", "False" ]	True
Steps 1 - 3 indicate a typical genetic sequencing operation for teachers.True or False?	[ "True", "False" ]	False
Steps 4 - 6 indicate a situation where a hacker has embedded their IP address and Port number into a DNA that will trigger a remote connection from a Trojan-horse infected software tool leading to a connection to the attacker in Step 9.True or False?	[ "True", "False" ]	False
It starts with Network-level objectives. The statement is true or false?	[ "True", "False" ]	True
Decision Plane is followed by Dissemination Plane. The statement is true or false?	[ "True", "False" ]	True
It starts with Data Plane.True or False?	[ "True", "False" ]	False
Decision Plane is followed by Discovery Plane.True or False?	[ "True", "False" ]	False
Figure 5: Flowchart describing the process for determining if SF is improving photocurrent in a device. The statement is true or false?	[ "True", "False" ]	True
If IQE is not greater than 100%, MPC is performed. The statement is true or false?	[ "True", "False" ]	True
Flowchart describing the process for determining if MPL is improving photocurrent in a device.True or False?	[ "True", "False" ]	False
If IQE is not greater than 100%, MPL is performed.True or False?	[ "True", "False" ]	False
CTCNet is a U-shaped symmetrical hierarchical network with three stages: encoding stag, bottleneck stage, and decoding stage. The statement is true or false?	[ "True", "False" ]	True
Among them, the encoding stage is designed to extract local and global features with different scales, and the decoding stage is designed for feature fusion and image reconstruction. The statement is true or false?	[ "True", "False" ]	True
CTCNet is an asymmetrical hierarchical network with three stages: encoding stag, bottleneck stage, and decoding stage.True or False?	[ "True", "False" ]	False
Among them, the encoding stage is designed to extract local and global features with the same scale, and the decoding stage is designed for feature fusion and image reconstruction.True or False?	[ "True", "False" ]	False
Figure 2: Overview of our proposed Quadratic Residual Network (QRes) layer in comparison with plain DNN layer. The statement is true or false?	[ "True", "False" ]	True
Blue rectangular boxes represent trainable parameters and round boxes represent operations (purple “×”: multiplication, orange “+”: addition, green ”·”: Hadamard product, and cyan ”σ”: activation operator). The statement is true or false?	[ "True", "False" ]	True
Overview of our proposed Quadratic Convolution Network (QConv) layer in comparison with plain DNN layer.True or False?	[ "True", "False" ]	False
Blue rectangular boxes represent trainable parameters and round boxes represent operations (purple “×”: multiplication, orange “-”: minus, green ”·”: Hadamard product, and cyan ”σ”: activation operator).True or False?	[ "True", "False" ]	False
Figure 6.4: An illustration of the “QC” setting of quantum machine learning, in which data are quantum and processing is classical. The statement is true or false?	[ "True", "False" ]	True
Quantum data is used for calculating the average. The statement is true or false?	[ "True", "False" ]	True
An illustration of the “QC” setting of quantum machine learning, in which data are quantum and optimizer is customized.True or False?	[ "True", "False" ]	False
Quantum data is used for calculating the medium.True or False?	[ "True", "False" ]	False
The classical optimizer aims at minimizing the expected value 〈F 〉ψ(θ)〉 = 〈ψ(θ)\|F \|ψ(θ)〉 of the observable F . The statement is true or false?	[ "True", "False" ]	True
The output of classical optimizer is sent to U(θ). The statement is true or false?	[ "True", "False" ]	True
The classical optimizer aims at minimizing the expected value U(θ).True or False?	[ "True", "False" ]	False
The input of classical optimizer is from U(θ).True or False?	[ "True", "False" ]	False
Guided by a curriculum sequence, the agent learns to adaptively trade-off constraints and the objective in non-stationarymarkets. The statement is true or false?	[ "True", "False" ]	True
During deployment, the agent updates its belief over the market dynamics based on its past experience, and acts through posterior sampling. The statement is true or false?	[ "True", "False" ]	True
Guided by a curriculum sequence, the agent does not learn to adaptively trade-off constraints and the objective in non-stationary markets.True or False?	[ "True", "False" ]	False
During deployment, the agent does not update its belief over the market dynamics based on its past experience, and acts through posterior sampling.True or False?	[ "True", "False" ]	False
The model uses a deep neural network to find the approximate Q-values. The statement is true or false?	[ "True", "False" ]	True
The model includes experience replay mechanism (to remove the correlation between different observations), a feature set (given as input to the deep neural network), a target Q-network for updating the primary Q-network and the simulation environment for extracting different parameters. The statement is true or false?	[ "True", "False" ]	True
The model uses a deep neural network to find the approximate BS-values.True or False?	[ "True", "False" ]	False

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This dataset

This is the cleaned test set of Flowlearn.

Citation

Please cite the paper if you use this dataset.

@misc{pan2024flowlearnevaluatinglargevisionlanguage,
      title={FlowLearn: Evaluating Large Vision-Language Models on Flowchart Understanding}, 
      author={Huitong Pan and Qi Zhang and Cornelia Caragea and Eduard Dragut and Longin Jan Latecki},
      year={2024},
      eprint={2407.05183},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2407.05183}, 
}

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DiagramVQA

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visual question-answering datasets relevant to the diagrams (human-created images) • 8 items • Updated 17 days ago