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相关论文: Human-in-the-loop Machine Translation with Large L…

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The ability of generative large language models (LLMs) to perform in-context learning has given rise to a large body of research into how best to prompt models for various natural language processing tasks. In this paper, we focus on…

计算与语言 · 计算机科学 2024-08-02 Armel Zebaze , Benoît Sagot , Rachel Bawden

Large language models (LLMs) have demonstrated impressive performance across a wide range of Natural Language Processing (NLP) tasks. However, ensuring their effectiveness across multiple languages presents unique challenges. Multilingual…

计算与语言 · 计算机科学 2025-05-20 Shubham Vatsal , Harsh Dubey , Aditi Singh

Large Language Models (LLMs) have demonstrated impressive performance on a wide range of natural language processing (NLP) tasks, primarily through in-context learning (ICL). In ICL, the LLM is provided with examples that represent a given…

计算与语言 · 计算机科学 2025-02-19 Abdellah El Mekki , Muhammad Abdul-Mageed

Generative large language models (LLMs) have demonstrated exceptional proficiency in various natural language processing (NLP) tasks, including machine translation, question answering, text summarization, and natural language understanding.…

计算与语言 · 计算机科学 2024-01-17 Nooshin Pourkamali , Shler Ebrahim Sharifi

Large Language Models (LLMs) exhibit emerging in-context learning abilities through prompt engineering. The recent progress in large-scale generative models has further expanded their use in real-world language applications. However, the…

计算与语言 · 计算机科学 2024-04-12 Linyi Yang , Shuibai Zhang , Zhuohao Yu , Guangsheng Bao , Yidong Wang , Jindong Wang , Ruochen Xu , Wei Ye , Xing Xie , Weizhu Chen , Yue Zhang

Large Language Models (LLMs) have shown capabilities close to human performance in various analytical tasks, leading researchers to use them for time and labor-intensive analyses. However, their capability to handle highly specialized and…

计算与语言 · 计算机科学 2024-10-08 Alexander S. Choi , Syeda Sabrina Akter , JP Singh , Antonios Anastasopoulos

We investigate how large language models can be used as research tools in scientific computing while preserving mathematical rigor. We propose a human-in-the-loop workflow for interactive theorem proving and discovery with LLMs. Human…

人机交互 · 计算机科学 2025-12-12 Chenyi Li , Zhijian Lai , Dong An , Jiang Hu , Zaiwen Wen

The rapid advancement of artificial intelligence, particularly with the development of Large Language Models (LLMs) built on the transformer architecture, has redefined the capabilities of natural language processing. These models now…

计算与语言 · 计算机科学 2025-02-11 Andrea Matarazzo , Riccardo Torlone

Translation is important for cross-language communication, and many efforts have been made to improve its accuracy. However, less investment is conducted in aligning translations with human preferences, such as translation tones or styles.…

计算与语言 · 计算机科学 2024-10-16 Shuqiao Sun , Yutong Yao , Peiwen Wu , Feijun Jiang , Kaifu Zhang

The rapid evolution of large language models (LLMs) and their capacity to simulate human cognition and behavior has given rise to LLM-based frameworks and tools that are evaluated and applied based on their ability to perform tasks…

计算与语言 · 计算机科学 2024-12-03 Jing Yi Wang , Nicholas Sukiennik , Tong Li , Weikang Su , Qianyue Hao , Jingbo Xu , Zihan Huang , Fengli Xu , Yong Li

A common use of NLP is to facilitate the understanding of large document collections, with a shift from using traditional topic models to Large Language Models. Yet the effectiveness of using LLM for large corpus understanding in real-world…

The exponential growth of text-based data in domains such as healthcare, education, and social sciences has outpaced the capacity of traditional qualitative analysis methods, which are time-intensive and prone to subjectivity. Large…

Large Language Models (LLMs) are transforming programming practices, offering significant capabilities for code generation activities. While researchers have explored the potential of LLMs in various domains, this paper focuses on their use…

软件工程 · 计算机科学 2026-05-04 Deborah Etsenake , Meiyappan Nagappan

Despite the popularity of the large language models (LLMs), their application to machine translation is relatively underexplored, especially in context-aware settings. This work presents a literature review of context-aware translation with…

计算与语言 · 计算机科学 2025-06-10 Ramakrishna Appicharla , Baban Gain , Santanu Pal , Asif Ekbal

Large Language Models (LLMs), typified by OpenAI's GPT, have marked a significant advancement in artificial intelligence. Trained on vast amounts of text data, LLMs are capable of understanding and generating human-like text across a…

人工智能 · 计算机科学 2024-10-29 Haochen Zhang , Yuyang Dong , Chuan Xiao , Masafumi Oyamada

Large Language Models are increasingly capable of interpreting multimodal inputs to generate complex 3D shapes, yet robust methods to evaluate geometric and structural fidelity remain underdeveloped. This paper introduces a human in the…

计算机视觉与模式识别 · 计算机科学 2025-09-10 Ahmed R. Sadik , Mariusz Bujny

Language models have steadily increased in size over the past few years. They achieve a high level of performance on various natural language processing (NLP) tasks such as question answering and summarization. Large language models (LLMs)…

计算与语言 · 计算机科学 2023-01-31 Jessica Huynh , Cathy Jiao , Prakhar Gupta , Shikib Mehri , Payal Bajaj , Vishrav Chaudhary , Maxine Eskenazi

Novice programmers benefit from timely, personalized support that addresses individual learning gaps, yet the availability of instructors and teaching assistants is inherently limited. Large language models (LLMs) present opportunities to…

计算机与社会 · 计算机科学 2025-10-07 Griffin Pitts , Anurata Prabha Hridi , Arun-Balajiee Lekshmi-Narayanan

Large Language Models (LLMs) have become an integral part of many real-world workflows. However, LLMs consume a lot of energy, which becomes a large concern in the scale of the demand for these tools. As LLMs become integrated into…

软件工程 · 计算机科学 2026-05-01 Katelyn Crumpacker , Dimitrios Nikolopoulos