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Large language models (LLMs) are advanced artificial intelligence (AI) systems that can perform a variety of tasks commonly found in human intelligence tests, such as defining words, performing calculations, and engaging in verbal…

Computation and Language · Computer Science 2024-09-12 David Ilić , Gilles E. Gignac

Large multimodal models (LMMs) have evolved from large language models (LLMs) to integrate multiple input modalities, such as visual inputs. This integration augments the capacity of LLMs for tasks requiring visual comprehension and…

Computer Vision and Pattern Recognition · Computer Science 2024-04-01 Mohammad Reza Taesiri , Tianjun Feng , Anh Nguyen , Cor-Paul Bezemer

Large Language Models (LLMs) have demonstrated remarkable emergent capabilities, yet the robustness of their numerical reasoning remains an open question. While standard benchmarks evaluate LLM reasoning on complex problem sets using…

Machine Learning · Computer Science 2025-09-09 Roussel Rahman , Aashwin Ananda Mishra

Large Language Models (LLMs) have shown remarkable capabilities across a wide variety of Natural Language Processing (NLP) tasks and have attracted attention from multiple domains, including financial services. Despite the extensive…

Computation and Language · Computer Science 2025-01-14 Jean Lee , Nicholas Stevens , Soyeon Caren Han , Minseok Song

Large Language Models (LLMs) have come closest among all models to date to mastering human language, yet opinions about their linguistic and cognitive capabilities remain split. Here, we evaluate LLMs using a distinction between formal…

Computation and Language · Computer Science 2024-04-14 Kyle Mahowald , Anna A. Ivanova , Idan A. Blank , Nancy Kanwisher , Joshua B. Tenenbaum , Evelina Fedorenko

Large Language Models (LLMs) have demonstrated remarkable performance across various natural language tasks, marking significant strides towards general artificial intelligence. While general artificial intelligence is leveraged by…

Computation and Language · Computer Science 2023-10-31 Yizhe Yang , Huashan Sun , Jiawei Li , Runheng Liu , Yinghao Li , Yuhang Liu , Heyan Huang , Yang Gao

Large Language Models (LLMs) have demonstrated strong performance across various natural language processing tasks, yet their proficiency in mathematical reasoning remains a key challenge. Addressing the gap between natural and mathematical…

Artificial Intelligence · Computer Science 2025-02-18 Xuhan Huang , Qingning Shen , Yan Hu , Anningzhe Gao , Benyou Wang

Poker is a landmark challenge for artificial intelligence. The dominant approach relies on equilibrium solvers built on counterfactual regret minimization, requiring millions of core-hours of training. Large Language Models (LLMs) possess…

Artificial Intelligence · Computer Science 2026-05-29 Boning Li , Baoxiang Wang , Longbo Huang

In recent years, Large Language Models (LLMs) have emerged as a transformative development in artificial intelligence (AI), drawing significant attention from industry and academia. Trained on vast datasets, these sophisticated AI systems…

Artificial Intelligence · Computer Science 2025-01-15 Oudom Hean , Utsha Saha , Binita Saha

Game playing has long served as a fundamental benchmark for evaluating Artificial General Intelligence. While Large Language Models (LLMs) have demonstrated impressive capabilities in general reasoning, their effectiveness in spatial…

Artificial Intelligence · Computer Science 2025-11-19 Yuhao Chen , Shuochen Liu , Yuanjie Lyu , Chao Zhang , Jiayao Shi , Tong Xu

Large Language Models (LLMs) have made significant strides in natural language processing and are increasingly being integrated into recommendation systems. However, their potential in educational recommendation systems has yet to be fully…

Information Retrieval · Computer Science 2025-04-14 Boxuan Ma , Md Akib Zabed Khan , Tianyuan Yang , Agoritsa Polyzou , Shin'ichi Konomi

Large language models (LLMs) have demonstrated remarkable performance on various medical benchmarks, but their capabilities across different cognitive levels remain underexplored. Inspired by Bloom's Taxonomy, we propose a…

Computation and Language · Computer Science 2025-06-11 Yuxuan Zhou , Xien Liu , Chenwei Yan , Chen Ning , Xiao Zhang , Boxun Li , Xiangling Fu , Shijin Wang , Guoping Hu , Yu Wang , Ji Wu

Large language models (LLMs), such as GPT-3 and GPT-4, have demonstrated exceptional performance in various natural language processing tasks and have shown the ability to solve certain reasoning problems. However, their reasoning…

Artificial Intelligence · Computer Science 2023-07-18 Adam Ishay , Zhun Yang , Joohyung Lee

Large Language Models (LLMs) have demonstrated remarkable performance across various natural language processing tasks. Recently, several LLMs-based pipelines have been developed to enhance learning on graphs with text attributes,…

Machine Learning · Computer Science 2024-07-30 Kai Guo , Zewen Liu , Zhikai Chen , Hongzhi Wen , Wei Jin , Jiliang Tang , Yi Chang

Can out-of-the-box pretrained Large Language Models (LLMs) detect human affect successfully when observing a video? To address this question, for the first time, we evaluate comprehensively the capacity of popular LLMs for successfully…

Computer Vision and Pattern Recognition · Computer Science 2026-01-30 David Melhart , Matthew Barthet , Georgios N. Yannakakis

Large Language Models (LLMs) have been shown to achieve breakthrough performance on complex logical reasoning tasks. Nevertheless, most existing research focuses on employing formal language to guide LLMs to derive reliable reasoning paths,…

Computation and Language · Computer Science 2025-05-23 Jin Jiang , Jianing Wang , Yuchen Yan , Yang Liu , Jianhua Zhu , Mengdi Zhang , Xunliang Cai , Liangcai Gao

While large language models have made strides in natural language processing, their proficiency in complex reasoning tasks requiring formal language comprehension, such as chess, remains less investigated. This paper probes the performance…

Computation and Language · Computer Science 2023-08-30 Mu-Tien Kuo , Chih-Chung Hsueh , Richard Tzong-Han Tsai

Large language models (LLMs) show best-in-class performance across a wide range of natural language processing applications. Training these models is an extremely computationally expensive task; frontier Artificial Intelligence (AI)…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-10-10 Alexander Interrante-Grant , Carla Varela-Rosa , Suhaas Narayan , Chris Connelly , Albert Reuther

Large pretrained models are showing increasingly better performance in reasoning and planning tasks across different modalities, opening the possibility to leverage them for complex sequential decision making problems. In this paper, we…

Artificial Intelligence · Computer Science 2024-10-10 Martin Klissarov , Devon Hjelm , Alexander Toshev , Bogdan Mazoure

Reasoning is a central capability of human intelligence. In recent years, with the advent of large-scale datasets, pretrained large language models have emerged with new capabilities, including reasoning. However, these models still…

Computation and Language · Computer Science 2025-03-03 Shu Wang , Lei Ji , Renxi Wang , Wenxiao Zhao , Haokun Liu , Yifan Hou , Ying Nian Wu
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