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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

Although pretrained language models (PLMs) can be prompted to perform a wide range of language tasks, it remains an open question how much this ability comes from generalizable linguistic understanding versus surface-level lexical patterns.…

Computation and Language · Computer Science 2023-05-23 Terra Blevins , Hila Gonen , Luke Zettlemoyer

Prompt engineering is a technique that involves augmenting a large pre-trained model with task-specific hints, known as prompts, to adapt the model to new tasks. Prompts can be created manually as natural language instructions or generated…

Computer Vision and Pattern Recognition · Computer Science 2023-07-25 Jindong Gu , Zhen Han , Shuo Chen , Ahmad Beirami , Bailan He , Gengyuan Zhang , Ruotong Liao , Yao Qin , Volker Tresp , Philip Torr

Large Language Models (LLMs) have succeeded remarkably in various natural language processing (NLP) tasks, yet their reasoning capabilities remain a fundamental challenge. While LLMs exhibit impressive fluency and factual recall, their…

Computation and Language · Computer Science 2025-05-29 Avinash Patil , Aryan Jadon

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…

The startling success of ChatGPT and other large language models (LLMs) using transformer-based generative neural network architecture in applications such as natural language processing and image synthesis has many researchers excited…

Artificial Intelligence · Computer Science 2024-11-05 Venkat Venkatasubramanian , Arijit Chakraborty

Despite significant research effort in the development of automatic dialogue evaluation metrics, little thought is given to evaluating dialogues other than in English. At the same time, ensuring metrics are invariant to semantically similar…

Computation and Language · Computer Science 2023-09-11 John Mendonça , Patrícia Pereira , Helena Moniz , João Paulo Carvalho , Alon Lavie , Isabel Trancoso

The emergence of Large Language Models (LLMs) has achieved tremendous success in the field of Natural Language Processing owing to diverse training paradigms that empower LLMs to effectively capture intricate linguistic patterns and…

Information Retrieval · Computer Science 2024-07-04 Lemei Zhang , Peng Liu , Yashar Deldjoo , Yong Zheng , Jon Atle Gulla

Prompt engineering is an increasingly important skill set needed to converse effectively with large language models (LLMs), such as ChatGPT. Prompts are instructions given to an LLM to enforce rules, automate processes, and ensure specific…

Recent breakthroughs in Large Language Models (LLMs), such as GPT-3 and Codex, now enable software developers to generate code based on a natural language prompt. Within computer science education, researchers are exploring the potential…

Computers and Society · Computer Science 2022-12-13 Stephen MacNeil , Andrew Tran , Juho Leinonen , Paul Denny , Joanne Kim , Arto Hellas , Seth Bernstein , Sami Sarsa

The use of large language models (LLMs) in natural language processing (NLP) tasks is rapidly increasing, leading to changes in how researchers approach problems in the field. To fully utilize these models' abilities, a better understanding…

Computation and Language · Computer Science 2023-11-07 Bishal Santra , Sakya Basak , Abhinandan De , Manish Gupta , Pawan Goyal

Language is essentially a complex, intricate system of human expressions governed by grammatical rules. It poses a significant challenge to develop capable AI algorithms for comprehending and grasping a language. As a major approach,…

Recent advances in prompting techniques and multi-agent systems for Large Language Models (LLMs) have produced increasingly complex approaches. However, we lack a framework for characterizing and comparing prompting techniques or…

Artificial Intelligence · Computer Science 2025-01-15 Dhruv Dhamani , Mary Lou Maher

Large language models (LLMs) trained purely on text ostensibly lack any direct perceptual experience, yet their internal representations are implicitly shaped by multimodal regularities encoded in language. We test the hypothesis that…

Computation and Language · Computer Science 2025-10-06 Sophie L. Wang , Phillip Isola , Brian Cheung

Large Language Models (LLMs) are the cornerstone in automating Requirements Engineering (RE) tasks, underpinning recent advancements in the field. Their pre-trained comprehension of natural language is pivotal for effectively tailoring them…

Software Engineering · Computer Science 2024-05-16 Andreas Vogelsang , Jannik Fischbach

Large language models (LLMs), inspired by neuroscience, exhibit behaviors that often evoke a sense of personality and intelligence-yet the mechanisms behind these effects remain elusive. Here, we operationalize Conceptual Blending Theory…

Computation and Language · Computer Science 2025-05-19 Makoto Sato

Legal Prompt Engineering (LPE) or Legal Prompting is a process to guide and assist a large language model (LLM) with performing a natural legal language processing (NLLP) skill. Our goal is to use LPE with LLMs over long legal documents for…

Computation and Language · Computer Science 2022-12-06 Dietrich Trautmann , Alina Petrova , Frank Schilder

Language modeling studies the probability distributions over strings of texts. It is one of the most fundamental tasks in natural language processing (NLP). It has been widely used in text generation, speech recognition, machine…

Computation and Language · Computer Science 2024-07-18 Chengwei Wei , Yun-Cheng Wang , Bin Wang , C. -C. Jay Kuo

Conversational systems based on Large Language Models (LLMs), such as ChatGPT, show exceptional proficiency in context understanding and response generation. However, despite their impressive capabilities, they still possess limitations,…

Computation and Language · Computer Science 2023-10-17 Yang Deng , Lizi Liao , Liang Chen , Hongru Wang , Wenqiang Lei , Tat-Seng Chua

Prompt engineering is an essential technique for enhancing the abilities of large language models (LLMs) by providing explicit and specific instructions. It enables LLMs to excel in various tasks, such as arithmetic reasoning, question…

Computation and Language · Computer Science 2024-03-29 Fobo Shi , Peijun Qing , Dong Yang , Nan Wang , Youbo Lei , Haonan Lu , Xiaodong Lin , Duantengchuan Li