641 to 650 of 5,040 Results
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
|
Dec 10, 2025 -
Replication Data for: What Are We Measuring When We Evaluate Large Vision-Language Models? An Analysis of Latent Factors and Biases
Plain Text - 991 B -
MD5: d002b0243142e9e6343d8bf40102497c
|
Dec 10, 2025 -
Replication Data for: What Are We Measuring When We Evaluate Large Vision-Language Models? An Analysis of Latent Factors and Biases
ZIP Archive - 290.6 MB -
MD5: ceffa4a09f0c6249822c969cc0df2708
|
Dec 10, 2025 -
Replication Data for: What Are We Measuring When We Evaluate Large Vision-Language Models? An Analysis of Latent Factors and Biases
ZIP Archive - 57.6 MB -
MD5: ea3ee3244ac3917a1c6db79cb04a6af7
|
Dec 10, 2025 -
Replication Data for: What Are We Measuring When We Evaluate Large Vision-Language Models? An Analysis of Latent Factors and Biases
ZIP Archive - 57.7 MB -
MD5: c3e0f9bd41e047c6410aabe58323b1f7
|
Dec 10, 2025
|
Oct 7, 2025 - S-Lab for Advanced Intelligence
Zhang, Yuanhan; Chew, Yunice; Dong, Yuhao; Leo, Aria; Hu, Bo; Liu, Ziwei, 2025, "Towards Video Thinking Test: A Holistic Benchmark for Advanced Video Reasoning and Understanding", https://doi.org/10.21979/N9/KTBVSQ, DR-NTU (Data), V1
We introduce the Video Thinking Test (Video-TT), a benchmark designed to assess if video LLMs can interpret real-world videos as effectively as humans. Video-TT 1) differentiates between errors due to inadequate frame sampling and genuine gaps in understanding complex visual narr... |
Sep 17, 2025 - S-Lab for Advanced Intelligence
Li, Ruibo; Shi, Hanyu; Wang, Zhe; Lin, Guosheng, 2025, "Weakly and Self-Supervised Class-Agnostic Motion Prediction for Autonomous Driving", https://doi.org/10.21979/N9/PE8MLE, DR-NTU (Data), V1
Understanding motion in dynamic environments is critical for autonomous driving, thereby motivating research on class-agnostic motion prediction. In this work, we investigate weakly and self-supervised class-agnostic motion prediction from LiDAR point clouds. Outdoor scenes typic... |
Sep 11, 2025 - S-Lab for Advanced Intelligence
Dai, Yuekun; Li, Haitian; Zhou, Shangchen; Loy, Chen Change, 2025, "Trans-Adapter: A Plug-and-Play Framework for Transparent Image Inpainting", https://doi.org/10.21979/N9/4NI0GT, DR-NTU (Data), V1
RGBA images, with the additional alpha channel, are crucial for any application that needs blending, masking, or transparency effects, making them more versatile than standard RGB images. Nevertheless, existing image inpainting methods are designed exclusively for RGB images. Con... |
ZIP Archive - 654.6 MB -
MD5: 972cfdcaec94978b658a7296d3bc0dbb
Benchmark of our paper. |
