Výsledky vyhledávání - "Zhang, Jianrui"

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TemporalBench: Benchmarking Fine-grained Temporal Understanding for Multimodal Video Models

Autor: Cai, Mu, Tan, Reuben, Zhang, Jianrui, Zou, Bocheng, Zhang, Kai, Yao, Feng, Zhu, Fangrui, Gu, Jing, Zhong, Yiwu, Shang, Yuzhang, Dou, Yao, Park, Jaden, Gao, Jianfeng, Lee, Yong Jae, Yang, Jianwei

Understanding fine-grained temporal dynamics is crucial for multimodal video comprehension and generation. Due to the lack of fine-grained temporal annotations, existing video benchmarks mostly resemble static image benchmarks and are incompetent at

Externí odkaz: http://arxiv.org/abs/2410.10818

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Vinoground: Scrutinizing LMMs over Dense Temporal Reasoning with Short Videos

Autor: Zhang, Jianrui, Cai, Mu, Lee, Yong Jae

There has been growing sentiment recently that modern large multimodal models (LMMs) have addressed most of the key challenges related to short video comprehension. As a result, both academia and industry are gradually shifting their attention toward

Externí odkaz: http://arxiv.org/abs/2410.02763

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VGBench: Evaluating Large Language Models on Vector Graphics Understanding and Generation

Autor: Zou, Bocheng, Cai, Mu, Zhang, Jianrui, Lee, Yong Jae

In the realm of vision models, the primary mode of representation is using pixels to rasterize the visual world. Yet this is not always the best or unique way to represent visual content, especially for designers and artists who depict the world usin

Externí odkaz: http://arxiv.org/abs/2407.10972

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Variable Selection in Ultra-high Dimensional Feature Space for the Cox Model with Interval-Censored Data

Autor: Pak, Daewoo, Zhang, Jianrui, Wu, Di, Weng, Haolei, Li, Chenxi

We develop a set of variable selection methods for the Cox model under interval censoring, in the ultra-high dimensional setting where the dimensionality can grow exponentially with the sample size. The methods select covariates via a penalized nonpa

Externí odkaz: http://arxiv.org/abs/2405.01275

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CounterCurate: Enhancing Physical and Semantic Visio-Linguistic Compositional Reasoning via Counterfactual Examples

Autor: Zhang, Jianrui, Cai, Mu, Xie, Tengyang, Lee, Yong Jae

We propose CounterCurate, a framework to comprehensively improve the visio-linguistic compositional reasoning capability for both contrastive and generative multimodal models. In particular, we identify two critical under-explored problems: the negle

Externí odkaz: http://arxiv.org/abs/2402.13254

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Post-Selection Inference for the Cox Model with Interval-Censored Data

Autor: Zhang, Jianrui, Li, Chenxi, Weng, Haolei

We develop a post-selection inference method for the Cox proportional hazards model with interval-censored data, which provides asymptotically valid p-values and confidence intervals conditional on the model selected by lasso. The method is based on

Externí odkaz: http://arxiv.org/abs/2306.13870

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