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Related papers: Prompt Middleware: Mapping Prompts for Large Langu…

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Modern large language models (LLMs) are capable of interpreting input strings as instructions, or prompts, and carry out tasks based on them. Unlike traditional learners, LLMs cannot use back-propagation to obtain feedback, and condition…

Computation and Language · Computer Science 2026-03-17 Adrian de Wynter , Xun Wang , Qilong Gu , Si-Qing Chen

Open-ended questions are a favored tool among instructors for assessing student understanding and encouraging critical exploration of course material. Providing feedback for such responses is a time-consuming task that can lead to…

Computers and Society · Computer Science 2023-08-07 Jordan K. Matelsky , Felipe Parodi , Tony Liu , Richard D. Lange , Konrad P. Kording

Large Language Models (LLMs) are becoming ubiquitous to create intelligent virtual assistants that assist users in interacting with a system, as exemplified in marketing. Although LLMs have been discussed in Modeling & Simulation (M&S), the…

Human-Computer Interaction · Computer Science 2024-09-25 Philippe J. Giabbanelli , Jose J. Padilla , Ameeta Agrawal

Large language models (LLMs) have achieved remarkable success in a wide range of natural language processing tasks and can be adapted through prompting. However, they remain suboptimal in multi-turn interactions, often relying on incorrect…

Large Language Models (LLMs) have transformed human-computer interaction by enabling natural language-based communication with AI-powered chatbots. These models are designed to be intuitive and user-friendly, allowing users to articulate…

Large language models (LLMs) have gained considerable attention for Artificial Intelligence Generated Content (AIGC), particularly with the emergence of ChatGPT. However, the direct adaptation of continuous speech to LLMs that process…

Audio and Speech Processing · Electrical Eng. & Systems 2023-08-28 Haibin Wu , Kai-Wei Chang , Yuan-Kuei Wu , Hung-yi Lee

In large language models (LLM)-based recommendation systems (LLM-RSs), accurately predicting user preferences by leveraging the general knowledge of LLMs is possible without requiring extensive training data. By converting recommendation…

Information Retrieval · Computer Science 2024-12-20 Genki Kusano , Kosuke Akimoto , Kunihiro Takeoka

Prompt optimization improves the reasoning abilities of large language models (LLMs) without requiring parameter updates to the target model. Following heuristic-based "Think step by step" approaches, the field has evolved in two main…

Computation and Language · Computer Science 2025-07-25 Andreea Nica , Ivan Zakazov , Nicolas Mario Baldwin , Saibo Geng , Robert West

The emergence of foundation models, such as large language models (LLMs) GPT-4 and text-to-image models DALL-E, has opened up numerous possibilities across various domains. People can now use natural language (i.e. prompts) to communicate…

Software Engineering · Computer Science 2023-12-21 Yu Cheng , Jieshan Chen , Qing Huang , Zhenchang Xing , Xiwei Xu , Qinghua Lu

Recommender systems are essential for delivering personalized content across digital platforms by modeling user preferences and behaviors. Recently, large language models (LLMs) have been adopted for prompt-based recommendation due to their…

Information Retrieval · Computer Science 2025-05-28 Md Aminul Islam , Ahmed Sayeed Faruk

Large language models (LLMs) have displayed an impressive ability to harness natural language to perform complex tasks. In this work, we explore whether we can leverage this learned ability to find and explain patterns in data.…

Machine Learning · Computer Science 2023-01-30 Chandan Singh , John X. Morris , Jyoti Aneja , Alexander M. Rush , Jianfeng Gao

Large language models have demonstrated outstanding performance on a wide range of tasks such as question answering and code generation. On a high level, given an input, a language model can be used to automatically complete the sequence in…

Computation and Language · Computer Science 2023-05-31 Luca Beurer-Kellner , Marc Fischer , Martin Vechev

Pre-trained language models (PLM) have marked a huge leap in neural dialogue modeling. While PLMs are pre-trained on large-scale text corpora, they are usually fine-tuned on scarce dialogue data with specific domain knowledge and dialogue…

Computation and Language · Computer Science 2021-12-14 Xiaodong Gu , Kang Min Yoo , Sang-Woo Lee

AI tasks encompass a wide range of domains and fields. While numerous AI models have been designed for specific tasks and applications, they often require considerable human efforts in finding the right model architecture, optimization…

Computation and Language · Computer Science 2023-05-05 Shujian Zhang , Chengyue Gong , Lemeng Wu , Xingchao Liu , Mingyuan Zhou

Many recent prompting strategies for large language models (LLMs) query the model multiple times sequentially -- first to produce intermediate results and then the final answer. However, using these methods, both decoder and model are…

Computation and Language · Computer Science 2023-11-10 Luca Beurer-Kellner , Mark Niklas Müller , Marc Fischer , Martin Vechev

The performance of pre-trained Large Language Models (LLMs) is often sensitive to nuances in prompt templates, requiring careful prompt engineering, adding costs in terms of computing and human effort. In this study, we present experiments…

Computation and Language · Computer Science 2025-05-27 Liang Cheng , Tianyi LI , Zhaowei Wang , Mark Steedman

Product review generation is an important task in recommender systems, which could provide explanation and persuasiveness for the recommendation. Recently, Large Language Models (LLMs, e.g., ChatGPT) have shown superior text modeling and…

Computation and Language · Computer Science 2024-07-11 Qiyao Peng , Hongtao Liu , Hongyan Xu , Qing Yang , Minglai Shao , Wenjun Wang

Since the launch of ChatGPT, a powerful AI Chatbot developed by OpenAI, large language models (LLMs) have made significant advancements in both academia and industry, bringing about a fundamental engineering paradigm shift in many areas.…

Software Engineering · Computer Science 2023-11-22 Xiaoxia Liu , Jingyi Wang , Jun Sun , Xiaohan Yuan , Guoliang Dong , Peng Di , Wenhai Wang , Dongxia Wang

This paper assesses the potential for large language models (LLMs) to serve as assistive tools in the creative writing process, by means of a single, in-depth case study. In the course of the study, we develop interactive and multi-voice…

Computation and Language · Computer Science 2023-12-08 Murray Shanahan , Catherine Clarke

Large language models (LLMs) are capable of generating multiple responses to a single prompt, yet little effort has been expended to help end-users or system designers make use of this capability. In this paper, we explore how to present…

Human-Computer Interaction · Computer Science 2024-01-26 Katy Ilonka Gero , Chelse Swoopes , Ziwei Gu , Jonathan K. Kummerfeld , Elena L. Glassman