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Mission: DR-NTU (Data) curates, stores, preserves, makes available and enables the download of digital data generated by the NTU research community. The repository develops and provides guidance for managing, sharing, and reusing research data to promote responsible data sharing in support of open science and research integrity.

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871 to 880 of 73,650 Results

position_and_counting.parquet Dec 10, 2025 - Replication Data for: SPHERE: A Hierarchical Evaluation on Spatial Perception and Reasoning for Vision-Language Models Unknown - 5.4 MB - MD5: 3d6824d188f7ad026a5f756ddc3f6558
position_only.parquet Dec 10, 2025 - Replication Data for: SPHERE: A Hierarchical Evaluation on Spatial Perception and Reasoning for Vision-Language Models Unknown - 10.6 MB - MD5: 08ca4e52fbd22c9ce5609e66a8d708e6
prepare_parquet.py Dec 10, 2025 - Replication Data for: SPHERE: A Hierarchical Evaluation on Spatial Perception and Reasoning for Vision-Language Models Python Source Code - 1.1 KB - MD5: be6cc43459c395092bedec002122cb7c
README.md Dec 10, 2025 - Replication Data for: SPHERE: A Hierarchical Evaluation on Spatial Perception and Reasoning for Vision-Language Models Markdown Text - 6.8 KB - MD5: 056581180352a3b0066a30384177affa Documentation
size_only.parquet Dec 10, 2025 - Replication Data for: SPHERE: A Hierarchical Evaluation on Spatial Perception and Reasoning for Vision-Language Models Unknown - 9.7 MB - MD5: 4f92f265e202534071ce255be532ef94
Replication Data for: What Are We Measuring When We Evaluate Large Vision-Language Models? An Analysis of Latent Factors and Biases Dec 10, 2025 - Junqi ZHAO Tiong, Anthony Meng Huat; Zhao, Junqi; Li, Boyang; Li, Junnan; Hoi, Steven C.H.; Xiong, Caiming, 2025, "Replication Data for: What Are We Measuring When We Evaluate Large Vision-Language Models? An Analysis of Latent Factors and Biases", https://doi.org/10.21979/N9/SL0VV1, DR-NTU (Data), V1 The OLIVE dataset is a highly diverse, human-corrected multi-modal collection designed to simulate the variety and idiosyncrasies of user queries vision-language models (VLMs) face in real-world scenarios. It supports the training and evaluation of VLMs in conditions that more cl...
olive_test_v1.0.json Dec 10, 2025 - Replication Data for: What Are We Measuring When We Evaluate Large Vision-Language Models? An Analysis of Latent Factors and Biases JSON - 16.0 MB - MD5: fee1650812796db2c2cc9ff327265699
olive_test_v2.0.json Dec 10, 2025 - Replication Data for: What Are We Measuring When We Evaluate Large Vision-Language Models? An Analysis of Latent Factors and Biases JSON - 20.1 MB - MD5: 2c512dc2b32605935cefe114816f349c
olive_train.json Dec 10, 2025 - Replication Data for: What Are We Measuring When We Evaluate Large Vision-Language Models? An Analysis of Latent Factors and Biases JSON - 4.0 MB - MD5: 4194ad7f1a9c647064918b6a9c147a3a
olive_val.json Dec 10, 2025 - Replication Data for: What Are We Measuring When We Evaluate Large Vision-Language Models? An Analysis of Latent Factors and Biases JSON - 4.0 MB - MD5: 75560dac21c1a292322abbbee0ad3b46

position_and_counting.parquet

Dec 10, 2025 - Replication Data for: SPHERE: A Hierarchical Evaluation on Spatial Perception and Reasoning for Vision-Language Models

Unknown - 5.4 MB -

position_only.parquet

Dec 10, 2025 - Replication Data for: SPHERE: A Hierarchical Evaluation on Spatial Perception and Reasoning for Vision-Language Models

Unknown - 10.6 MB -

prepare_parquet.py

Dec 10, 2025 - Replication Data for: SPHERE: A Hierarchical Evaluation on Spatial Perception and Reasoning for Vision-Language Models

Python Source Code - 1.1 KB -

README.md

Dec 10, 2025 - Replication Data for: SPHERE: A Hierarchical Evaluation on Spatial Perception and Reasoning for Vision-Language Models

Markdown Text - 6.8 KB -

Documentation

size_only.parquet

Dec 10, 2025 - Replication Data for: SPHERE: A Hierarchical Evaluation on Spatial Perception and Reasoning for Vision-Language Models

Unknown - 9.7 MB -

Replication Data for: What Are We Measuring When We Evaluate Large Vision-Language Models? An Analysis of Latent Factors and Biases

Dec 10, 2025 - Junqi ZHAO

Tiong, Anthony Meng Huat; Zhao, Junqi; Li, Boyang; Li, Junnan; Hoi, Steven C.H.; Xiong, Caiming, 2025, "Replication Data for: What Are We Measuring When We Evaluate Large Vision-Language Models? An Analysis of Latent Factors and Biases", https://doi.org/10.21979/N9/SL0VV1, DR-NTU (Data), V1

The OLIVE dataset is a highly diverse, human-corrected multi-modal collection designed to simulate the variety and idiosyncrasies of user queries vision-language models (VLMs) face in real-world scenarios. It supports the training and evaluation of VLMs in conditions that more cl...

olive_test_v1.0.json

Dec 10, 2025 - Replication Data for: What Are We Measuring When We Evaluate Large Vision-Language Models? An Analysis of Latent Factors and Biases

JSON - 16.0 MB -

olive_test_v2.0.json

Dec 10, 2025 - Replication Data for: What Are We Measuring When We Evaluate Large Vision-Language Models? An Analysis of Latent Factors and Biases

JSON - 20.1 MB -

olive_train.json

Dec 10, 2025 - Replication Data for: What Are We Measuring When We Evaluate Large Vision-Language Models? An Analysis of Latent Factors and Biases

JSON - 4.0 MB -

olive_val.json

Dec 10, 2025 - Replication Data for: What Are We Measuring When We Evaluate Large Vision-Language Models? An Analysis of Latent Factors and Biases

JSON - 4.0 MB -

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