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20232026
most citedMMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark

34 citations · 82 across the 18 of their papers we have counts for

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Showing 2024 · cs.CVShow all

7 papers · 2 filters

cs.CV2024

VISTA: Enhancing Long-Duration and High-Resolution Video Understanding by Video Spatiotemporal Augmentation

Weiming Ren, Huan Yang, Jie Min +2

Current large multimodal models (LMMs) face significant challenges in processing and comprehending long-duration or high-resolution videos, which is mainly due to the lack of high-…

cs.CV2024

MEGA-Bench: Scaling Multimodal Evaluation to over 500 Real-World Tasks

Jiacheng Chen, Tianhao Liang, Sherman Siu +13

We present MEGA-Bench, an evaluation suite that scales multimodal evaluation to over 500 real-world tasks, to address the highly heterogeneous daily use cases of end users. Our obj…

cs.CV2024

VLM2Vec: Training Vision-Language Models for Massive Multimodal Embedding Tasks

Ziyan Jiang, Rui Meng, Xinyi Yang +3

Embedding models have been crucial in enabling various downstream tasks such as semantic similarity, information retrieval, and clustering. Recently, there has been a surge of inte…

cs.CV2024

VideoScore: Building Automatic Metrics to Simulate Fine-grained Human Feedback for Video Generation

Xuan He, Dongfu Jiang, Ge Zhang +16

The recent years have witnessed great advances in video generation. However, the development of automatic video metrics is lagging significantly behind. None of the existing metric…

cs.CV2024★ 2 cited

MANTIS: Interleaved Multi-Image Instruction Tuning

Dongfu Jiang, Xuan He, Huaye Zeng +4

Large multimodal models (LMMs) have shown great results in single-image vision language tasks. However, their abilities to solve multi-image visual language tasks is yet to be impr…

cs.CV2024★ 2 cited

AnyV2V: A Tuning-Free Framework For Any Video-to-Video Editing Tasks

Max Ku, Cong Wei, Weiming Ren +2

In the dynamic field of digital content creation using generative models, state-of-the-art video editing models still do not offer the level of quality and control that users desir…

cs.CV2024★ 4 cited

ConsistI2V: Enhancing Visual Consistency for Image-to-Video Generation

Weiming Ren, Huan Yang, Ge Zhang +4

Image-to-video (I2V) generation aims to use the initial frame (alongside a text prompt) to create a video sequence. A grand challenge in I2V generation is to maintain visual consis…