中文
相关论文

相关论文: Using LLMs for Analyzing AIS Data

200 篇论文

Large Language Models (LLMs) are increasingly being used to autonomously evaluate the quality of content in communication systems, e.g., to assess responses in telecom customer support chatbots. However, the impartiality of these AI…

人工智能 · 计算机科学 2026-03-03 Jiaxin Gao , Chen Chen , Yanwen Jia , Xueluan Gong , Kwok-Yan Lam , Qian Wang

Large language models (LLMs) demonstrate outstanding capabilities, but challenges remain regarding their ability to solve complex reasoning tasks, as well as their transparency, robustness, truthfulness, and ethical alignment. In this…

计算机与社会 · 计算机科学 2023-12-19 Konstantin Hebenstreit , Robert Praas , Matthias Samwald

Roadway safety and mobility remain critical challenges for modern transportation systems, demanding innovative analytical frameworks capable of addressing complex, dynamic, and heterogeneous environments. While traditional engineering…

人工智能 · 计算机科学 2025-12-10 Muhammad Monjurul Karim , Yan Shi , Shucheng Zhang , Bingzhang Wang , Mehrdad Nasri , Yinhai Wang

AI is widely thought to be poised to transform business, yet current perceptions of the scope of this transformation may be myopic. Recent progress in natural language processing involving transformer language models (TLMs) offers a…

计算与语言 · 计算机科学 2021-10-26 Ross Gruetzemacher , David Paradice

As the strength of Large Language Models (LLMs) has grown over recent years, so too has interest in their use as the underlying models for autonomous agents. Although LLMs demonstrate emergent abilities and broad expertise across natural…

人工智能 · 计算机科学 2024-12-06 Chris Sypherd , Vaishak Belle

Large Language Models (LLMs) have been employed in financial decision making, enhancing analytical capabilities for investment strategies. Traditional investment strategies often utilize quantitative models, fundamental analysis, and…

综合金融 · 定量金融 2025-07-04 Sedigheh Mahdavi , Jiating , Chen , Pradeep Kumar Joshi , Lina Huertas Guativa , Upmanyu Singh

The reasoning capabilities of Large Language Models (LLMs) play a critical role in many downstream tasks, yet depend strongly on the quality of training data. Despite various proposed data construction methods, their practical utility in…

计算与语言 · 计算机科学 2025-10-09 Yike Zhao , Simin Guo , Ziqing Yang , Shifan Han , Dahua Lin , Fei Tan

In recent years, the integration of large language models (LLMs) has revolutionized the field of robotics, enabling robots to communicate, understand, and reason with human-like proficiency. This paper explores the multifaceted impact of…

机器人学 · 计算机科学 2024-08-16 Yeseung Kim , Dohyun Kim , Jieun Choi , Jisang Park , Nayoung Oh , Daehyung Park

Large Language Models (LLMs) have fundamentally reshaped Argument Mining (AM), shifting it from a pipeline of supervised, task-specific classifiers to a spectrum of prompt-driven, retrieval-augmented, and reasoning-oriented paradigms. Yet…

计算与语言 · 计算机科学 2025-11-26 Hao Li , Viktor Schlegel , Yizheng Sun , Riza Batista-Navarro , Goran Nenadic

The rapid advancement of LLMs sparked significant interest in their potential to augment or automate managerial functions. One of the most recent trends in AI benchmarking is performance of Large Language Models (LLMs) over longer time…

人工智能 · 计算机科学 2025-10-01 Berdymyrat Ovezmyradov

The advancement of Large Language Models (LLMs) has remarkably pushed the boundaries towards artificial general intelligence (AGI), with their exceptional ability on understanding diverse types of information, including but not limited to…

计算与语言 · 计算机科学 2023-10-10 Ziwei Chai , Tianjie Zhang , Liang Wu , Kaiqiao Han , Xiaohai Hu , Xuanwen Huang , Yang Yang

Large Language Models (LLMs) have emerged as a promising cornerstone for the development of natural language processing (NLP) and artificial intelligence (AI). However, ensuring the robustness of LLMs remains a critical challenge. To…

计算与语言 · 计算机科学 2025-11-07 Pankaj Kumar , Subhankar Mishra

This paper explores the advancements in making large language models (LLMs) more human-like. We focus on techniques that enhance natural language understanding, conversational coherence, and emotional intelligence in AI systems. The study…

计算与语言 · 计算机科学 2026-02-03 Ethem Yağız Çalık , Talha Rüzgar Akkuş

Large language models (LLMs) have recently shown remarkable performance in language tasks and beyond. However, due to their limited inherent causal reasoning ability, LLMs still face challenges in handling tasks that require robust causal…

计算与语言 · 计算机科学 2025-03-13 Xin Li , Zhuo Cai , Shoujin Wang , Kun Yu , Fang Chen

This systematic literature review comprehensively examines the application of Large Language Models (LLMs) in forecasting and anomaly detection, highlighting the current state of research, inherent challenges, and prospective future…

机器学习 · 计算机科学 2024-02-19 Jing Su , Chufeng Jiang , Xin Jin , Yuxin Qiao , Tingsong Xiao , Hongda Ma , Rong Wei , Zhi Jing , Jiajun Xu , Junhong Lin

When Artificial Intelligence (AI) is used to replace consumers (e.g., synthetic data), it is often assumed that AI emulates established consumers, and more generally human behaviors. Ten experiments with Large Language Models (LLMs)…

As large language models (LLMs) evolve, their integration with 3D spatial data (3D-LLMs) has seen rapid progress, offering unprecedented capabilities for understanding and interacting with physical spaces. This survey provides a…

Large language models (LLMs) are powerful artificial intelligence (AI) tools transforming how research is conducted. However, their use in research has been met with skepticism, due to concerns about hallucinations, biases and potential…

人工智能 · 计算机科学 2025-07-08 Ruian Ke , Ruy M. Ribeiro

Large Language Models(LLMs)have become effective tools for natural language processing and have been used in many different fields. This essay offers a succinct summary of various LLM subcategories. The survey emphasizes recent developments…

计算与语言 · 计算机科学 2023-07-21 Saurabh Pahune , Manoj Chandrasekharan

Using Large Language Models (LLMs) in an evolutionary or other iterative search framework have demonstrated significant potential in automated algorithm design. However, the underlying fitness landscape, which is critical for understanding…

人工智能 · 计算机科学 2025-08-28 Fei Liu , Qingfu Zhang , Jialong Shi , Xialiang Tong , Kun Mao , Mingxuan Yuan