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Despite the recent advancement in Retrieval-Augmented Generation (RAG) systems, most retrieval methodologies are often developed for factual retrieval, which assumes query and positive documents are semantically similar. In this paper, we…

Information Retrieval · Computer Science 2025-04-10 Luo Ji , Feixiang Guo , Teng Chen , Qingqing Gu , Xiaoyu Wang , Ningyuan Xi , Yihong Wang , Peng Yu , Yue Zhao , Hongyang Lei , Zhonglin Jiang , Yong Chen

Cross-modal reasoning (CMR), the intricate process of synthesizing and drawing inferences across divergent sensory modalities, is increasingly recognized as a crucial capability in the progression toward more sophisticated and…

Computation and Language · Computer Science 2024-10-01 Shengsheng Qian , Zuyi Zhou , Dizhan Xue , Bing Wang , Changsheng Xu

Large Reasoning Models (LRMs) such as DeepSeek-R1 and OpenAI o1 have demonstrated remarkable capabilities in various reasoning tasks. Their strong capability to generate and reason over intermediate thoughts has also led to arguments that…

Computation and Language · Computer Science 2025-10-17 Saurabh Srivastava , Ziyu Yao

Reasoning lies at the heart of intelligence, shaping the ability to make decisions, draw conclusions, and generalize across domains. In artificial intelligence, as systems increasingly operate in open, uncertain, and multimodal…

The landscape of education is changing rapidly, shaped by emerging pedagogical approaches, technological innovations such as artificial intelligence (AI), and evolving societal expectations, all of which demand thorough evaluation of new…

Computers and Society · Computer Science 2026-03-19 Fiammetta Caccavale , Carina L. Gargalo , Julian Kager , Magdalena Skowyra , Steen Larsen , Krist V. Gernaey , Ulrich Krühne

Recent advancements in large language models (LLMs), such as DeepSeek-R1 and OpenAI-o1, have demonstrated the significant effectiveness of test-time scaling, achieving substantial performance gains across various benchmarks. These advanced…

Computation and Language · Computer Science 2025-04-15 Haotian Wang , Han Zhao , Shuaiting Chen , Xiaoyu Tian , Sitong Zhao , Yunjie Ji , Yiping Peng , Xiangang Li

With the increasing use of large language models (LLMs), ensuring reliable performance in diverse, real-world environments is essential. Despite their remarkable achievements, LLMs often struggle with adversarial inputs, significantly…

Computation and Language · Computer Science 2024-06-18 Yuqing Wang , Yun Zhao

Large Language Models (LLMs), despite their remarkable capabilities, are prone to generating hallucinated or outdated content due to their static internal knowledge. While Retrieval-Augmented Generation (RAG) integrated with Reinforcement…

Computation and Language · Computer Science 2026-01-14 Zhiwen Tan , Jiaming Huang , Qintong Wu , Hongxuan Zhang , Chenyi Zhuang , Jinjie Gu

Classic AI planning problems have been revisited in the Large Language Model (LLM) era, with a focus of recent benchmarks on success rates rather than plan efficiency. We examine the degree to which frontier models reason optimally versus…

Artificial Intelligence · Computer Science 2026-04-06 Bernd Bohnet , Michael C. Mozer , Kevin Swersky , Wil Cunningham , Aaron Parisi , Kathleen Kenealy , Noah Fiedel

Large Language Models (LLMs) have achieved state-of-the-art performance on a broad range of Natural Language Processing (NLP) tasks, including document processing and code generation. Autoregressive Language Models (ARMs), which generate…

In recent times, the grandeur of Large Language Models (LLMs) has not only shone in the realm of natural language processing but has also cast its brilliance across a vast array of applications. This remarkable display of LLM capabilities…

Computation and Language · Computer Science 2024-03-22 Hanieh Alipour , Nick Pendar , Kohinoor Roy

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

In order for AI systems to communicate effectively with people, they must understand how we make decisions. However, people's decisions are not always rational, so the implicit internal models of human decision-making in Large Language…

Computation and Language · Computer Science 2025-03-11 Ryan Liu , Jiayi Geng , Joshua C. Peterson , Ilia Sucholutsky , Thomas L. Griffiths

Large Language Models (LLMs) have demonstrated remarkable capabilities in complex tasks. Recent advancements in Large Reasoning Models (LRMs), such as OpenAI o1 and DeepSeek-R1, have further improved performance in System-2 reasoning…

Computation and Language · Computer Science 2025-08-25 Yang Sui , Yu-Neng Chuang , Guanchu Wang , Jiamu Zhang , Tianyi Zhang , Jiayi Yuan , Hongyi Liu , Andrew Wen , Shaochen Zhong , Na Zou , Hanjie Chen , Xia Hu

Large language models (LLMs) have shown significant progress in reasoning tasks. However, recent studies show that transformers and LLMs fail catastrophically once reasoning problems exceed modest complexity. We revisit these findings…

Artificial Intelligence · Computer Science 2025-10-28 Revanth Rameshkumar , Jimson Huang , Yunxin Sun , Fei Xia , Abulhair Saparov

Unmanned Aerial Vehicles (UAVs) have emerged as a transformative technology across diverse sectors, offering adaptable solutions to complex challenges in both military and civilian domains. Their expanding capabilities present a platform…

Artificial Intelligence · Computer Science 2024-05-06 Shumaila Javaid , Nasir Saeed , Bin He

The advent of large language models marks a revolutionary breakthrough in artificial intelligence. With the unprecedented scale of training and model parameters, the capability of large language models has been dramatically improved,…

Information Retrieval · Computer Science 2025-01-16 Jin Chen , Zheng Liu , Xu Huang , Chenwang Wu , Qi Liu , Gangwei Jiang , Yuanhao Pu , Yuxuan Lei , Xiaolong Chen , Xingmei Wang , Defu Lian , Enhong Chen

Language models serve as a cornerstone in natural language processing (NLP), utilizing mathematical methods to generalize language laws and knowledge for prediction and generation. Over extensive research spanning decades, language modeling…

Computation and Language · Computer Science 2024-09-24 Zichong Wang , Zhibo Chu , Thang Viet Doan , Shiwen Ni , Min Yang , Wenbin Zhang

Reinforcement learning (RL) enhanced large language models (LLMs), particularly exemplified by DeepSeek-R1, have exhibited outstanding performance. Despite the effectiveness in improving LLM capabilities, its implementation remains highly…

Computation and Language · Computer Science 2025-02-25 Shuhe Wang , Shengyu Zhang , Jie Zhang , Runyi Hu , Xiaoya Li , Tianwei Zhang , Jiwei Li , Fei Wu , Guoyin Wang , Eduard Hovy

Large Language Models (LLMs) have achieved remarkable success across a wide array of tasks. Due to the impressive planning and reasoning abilities of LLMs, they have been used as autonomous agents to do many tasks automatically. Recently,…

Computation and Language · Computer Science 2024-04-22 Taicheng Guo , Xiuying Chen , Yaqi Wang , Ruidi Chang , Shichao Pei , Nitesh V. Chawla , Olaf Wiest , Xiangliang Zhang