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Neural Sign Language Production (SLP) aims to automatically translate from spoken language sentences to sign language videos. Historically the SLP task has been broken into two steps; Firstly, translating from a spoken language sentence to…

Computation and Language · Computer Science 2022-10-13 Harry Walsh , Ben Saunders , Richard Bowden

Recent developments in large language models (LLM) and generative AI have unleashed the astonishing capabilities of text-to-image generation systems to synthesize high-quality images that are faithful to a given reference text, known as a…

Human-Computer Interaction · Computer Science 2023-03-17 Yutong Xie , Zhaoying Pan , Jinge Ma , Luo Jie , Qiaozhu Mei

Prompt engineering has emerged as an indispensable technique for extending the capabilities of large language models (LLMs) and vision-language models (VLMs). This approach leverages task-specific instructions, known as prompts, to enhance…

Artificial Intelligence · Computer Science 2025-03-18 Pranab Sahoo , Ayush Kumar Singh , Sriparna Saha , Vinija Jain , Samrat Mondal , Aman Chadha

Text-to-image (T2I) diffusion models have demonstrated impressive image generation capabilities. Still, their computational intensity prohibits resource-constrained organizations from deploying T2I models after fine-tuning them on their…

Computer Vision and Pattern Recognition · Computer Science 2025-02-12 Alireza Ganjdanesh , Reza Shirkavand , Shangqian Gao , Heng Huang

Contrastively trained text-image models have the remarkable ability to perform zero-shot classification, that is, classifying previously unseen images into categories that the model has never been explicitly trained to identify. However,…

Image super-resolution (SR) methods typically model degradation to improve reconstruction accuracy in complex and unknown degradation scenarios. However, extracting degradation information from low-resolution images is challenging, which…

Computer Vision and Pattern Recognition · Computer Science 2025-03-12 Zheng Chen , Yulun Zhang , Jinjin Gu , Xin Yuan , Linghe Kong , Guihai Chen , Xiaokang Yang

Despite significant progress in Text-to-Image (T2I) generative models, even lengthy and complex text descriptions still struggle to convey detailed controls. In contrast, Layout-to-Image (L2I) generation, aiming to generate realistic and…

Computer Vision and Pattern Recognition · Computer Science 2024-03-14 Chengyou Jia , Minnan Luo , Zhuohang Dang , Guang Dai , Xiaojun Chang , Mengmeng Wang , Jingdong Wang

This paper introduces SGCode, a flexible prompt-optimizing system to generate secure code with large language models (LLMs). SGCode integrates recent prompt-optimization approaches with LLMs in a unified system accessible through front-end…

Cryptography and Security · Computer Science 2024-09-26 Khiem Ton , Nhi Nguyen , Mahmoud Nazzal , Abdallah Khreishah , Cristian Borcea , NhatHai Phan , Ruoming Jin , Issa Khalil , Yelong Shen

Text-to-image (T2I) generation has seen significant progress with diffusion models, enabling generation of photo-realistic images from text prompts. Despite this progress, existing methods still face challenges in following complex text…

Computer Vision and Pattern Recognition · Computer Science 2025-03-12 Ashish Goswami , Satyam Kumar Modi , Santhosh Rishi Deshineni , Harman Singh , Prathosh A. P , Parag Singla

Safety- and security-critical systems have to be thoroughly tested against their specifications. The state of practice is to have _natural language_ specifications, from which test cases are derived manually - a process that is slow,…

Software Engineering · Computer Science 2025-11-25 Kuangxiangzi Liu , Dhiman Chakraborty , Alexander Liggesmeyer , Andreas Zeller

Text-to-image (T2I) models offer great potential for creating virtually limitless synthetic data, a valuable resource compared to fixed and finite real datasets. Previous works evaluate the utility of synthetic data from T2I models on three…

Computer Vision and Pattern Recognition · Computer Science 2026-02-24 Zhang Xiaofeng , Aaron Courville , Michal Drozdzal , Adriana Romero-Soriano

Text-to-image (T2I) models are capable of generating visually impressive images, yet they often fail to accurately capture specific attributes in user prompts, such as the correct number of objects with the specified colors. The diversity…

Computer Vision and Pattern Recognition · Computer Science 2025-12-03 Kevin David Hayes , Micah Goldblum , Vikash Sehwag , Gowthami Somepalli , Ashwinee Panda , Tom Goldstein

Text-to-image synthesis, a subfield of multimodal generation, has gained significant attention in recent years. We propose a cost-effective approach for image-to-prompt generation that leverages generative models to generate textual prompts…

Computer Vision and Pattern Recognition · Computer Science 2024-01-19 Xin Zhang , Xin Zhang , YeMing Cai , Tianzhi Jia

Prompt engineering reduces reasoning mistakes in Large Language Models (LLMs). However, its effectiveness in mitigating vulnerabilities in LLM-generated code remains underexplored. To address this gap, we implemented a benchmark to…

Software Engineering · Computer Science 2025-02-11 Marc Bruni , Fabio Gabrielli , Mohammad Ghafari , Martin Kropp

Due to their architecture and vast pre-training data, large language models (LLMs) demonstrate strong text classification performance. However, LLM output - here, the category assigned to a text - depends heavily on the wording of the…

Computation and Language · Computer Science 2025-12-04 Kylie L. Anglin , Stephanie Milan , Brittney Hernandez , Claudia Ventura

In this paper, we propose SignLLM, a multilingual Sign Language Production (SLP) large language model, which includes two novel multilingual SLP modes MLSF and Prompt2LangGloss that allow sign language gestures generation from query texts…

Computer Vision and Pattern Recognition · Computer Science 2025-05-01 Sen Fang , Chen Chen , Lei Wang , Ce Zheng , Chunyu Sui , Yapeng Tian

As LLMs achieved breakthroughs in general reasoning, their proficiency in specialized scientific domains reveals pronounced gaps in existing benchmarks due to data contamination, insufficient complexity, and prohibitive human labor costs.…

Artificial Intelligence · Computer Science 2026-02-27 Peiyao Xiao , Xiaogang Li , Chengliang Xu , Jiayi Wang , Ben Wang , Zichao Chen , Zeyu Wang , Kejun Yu , Yueqian Chen , Xulin Liu , Wende Xiao , Bing Zhao , Hu Wei

Recent text-to-image (T2I) generation models have demonstrated impressive capabilities in creating images from text descriptions. However, these T2I generation models often fall short of generating images that precisely match the details of…

Computer Vision and Pattern Recognition · Computer Science 2024-03-12 Jialu Li , Jaemin Cho , Yi-Lin Sung , Jaehong Yoon , Mohit Bansal

Augmenting large language models (LLMs) with user-specific knowledge is crucial for real-world applications, such as personal AI assistants. However, LLMs inherently lack mechanisms for prompt-driven knowledge capture. This paper…

Computation and Language · Computer Science 2024-02-02 Tolga Çöplü , Arto Bendiken , Andrii Skomorokhov , Eduard Bateiko , Stephen Cobb , Joshua J. Bouw

Using a text description as prompt to guide the generation of text or images (e.g., GPT-3 or DALLE-2) has drawn wide attention recently. Beyond text and image generation, in this work, we explore the possibility of utilizing text…

Audio and Speech Processing · Electrical Eng. & Systems 2022-11-23 Zhifang Guo , Yichong Leng , Yihan Wu , Sheng Zhao , Xu Tan
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