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Papers Sports Understanding

“Sports Understanding” 태그가 달린 논문 11편 · 필터 해제

FSBench: A Figure Skating Benchmark for Advancing Artistic Sports Understanding

2025-01-01 · CVPR 2025 1 · Rong Gao, Xin Liu, Zhuozhao Hu, Bohao Xing 외

Figure skating, known as the "Art on Ice," is among the most artistic sports, challenging to understand due to its blend of technical elements (like jumps and spins) and overall artistic expression. Existing figure s…

Action RecognitionMultiple-choiceSports Understanding

Towards Universal Soccer Video Understanding

2024-12-02 · CVPR 2025 1 · Jiayuan Rao, HaoNing Wu, Hao Jiang, Ya zhang 외

As a globally celebrated sport, soccer has attracted widespread interest from fans all over the world. This paper aims to develop a comprehensive multi-modal framework for soccer video understanding. Specifically, we mak…

Action ClassificationSports UnderstandingVideo Understanding

SPORTU: A Comprehensive Sports Understanding Benchmark for Multimodal Large Language Models

2024-10-11 · Haotian Xia, Zhengbang Yang, Junbo Zou, Rhys Tracy 외

Multimodal Large Language Models (MLLMs) are advancing the ability to reason about complex sports scenarios by integrating textual and visual information. To comprehensively evaluate their capabilities, we introduce SPOR…

Few-Shot LearningMultiple-choiceQuestion AnsweringSports Understanding

Sports Intelligence: Assessing the Sports Understanding Capabilities of Language Models through Question Answering from Text to Video

2024-06-21 · Zhengbang Yang, Haotian Xia, Jingxi Li, Zezhi Chen 외

Understanding sports is crucial for the advancement of Natural Language Processing (NLP) due to its intricate and dynamic nature. Reasoning over complex sports scenarios has posed significant challenges to current NLP te…

BenchmarkingFew-Shot LearningQuestion AnsweringSports Understanding

SportQA: A Benchmark for Sports Understanding in Large Language Models

2024-02-24 · Haotian Xia, Zhengbang Yang, Yuqing Wang, Rhys Tracy 외

A deep understanding of sports, a field rich in strategic and dynamic content, is crucial for advancing Natural Language Processing (NLP). This holds particular significance in the context of evaluating and advancing Lar…

Few-Shot LearningMultiple-choiceSports Understanding

Estimating the age-conditioned average treatment effects curves: An application for assessing load-management strategies in the NBA

2024-02-17 · Shinpei Nakamura-Sakai, Laura Forastiere, Brian Macdonald

In the realm of competitive sports, understanding the performance dynamics of athletes, represented by the age curve (showing progression, peak, and decline), is vital. Our research introduces a novel framework for quant…

ManagementSports Understanding

BloombergGPT: A Large Language Model for Finance

2023-03-30 · Shijie Wu, Ozan Irsoy, Steven Lu, Vadim Dabravolski 외

The use of NLP in the realm of financial technology is broad and complex, with applications ranging from sentiment analysis and named entity recognition to question answering. Large Language Models (LLMs) have been shown…

Causal JudgmentCommon Sense ReasoningDate UnderstandingDisambiguation QA+25

Learning to Perform Complex Tasks through Compositional Fine-Tuning of Language Models

2022-10-23 · Victor S. Bursztyn, David Demeter, Doug Downey, Larry Birnbaum

How to usefully encode compositional task structure has long been a core challenge in AI. Recent work in chain of thought prompting has shown that for very large neural language models (LMs), explicitly demonstrating the…

Sports Understanding

DeepSportradar-v1: Computer Vision Dataset for Sports Understanding with High Quality Annotations

2022-08-17 · Gabriel Van Zandycke, Vladimir Somers, Maxime Istasse, Carlo Del Don 외

With the recent development of Deep Learning applied to Computer Vision, sport video understanding has gained a lot of attention, providing much richer information for both sport consumers and leagues. This paper introdu…

Camera CalibrationInstance SegmentationSemantic SegmentationSports Understanding+1

Training Compute-Optimal Large Language Models

2022-03-29 · Jordan Hoffmann, Sebastian Borgeaud, Arthur Mensch, Elena Buchatskaya 외

We investigate the optimal model size and number of tokens for training a transformer language model under a given compute budget. We find that current large language models are significantly undertrained, a consequence …

AnachronismsAnalogical SimilarityAnalytic EntailmentCausal Judgment+69

Scaling Language Models: Methods, Analysis & Insights from Training Gopher

2021-12-08 · NA 2021 12 · Jack W. Rae, Sebastian Borgeaud, Trevor Cai, Katie Millican 외

Language modelling provides a step towards intelligent communication systems by harnessing large repositories of written human knowledge to better predict and understand the world. In this paper, we present an analysis o…

Abstract AlgebraAnachronismsAnalogical SimilarityAnalytic Entailment+143
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