diff --git a/assets/css/theme.css b/assets/css/theme.css index 71f6d4c..4975c73 100644 --- a/assets/css/theme.css +++ b/assets/css/theme.css @@ -18759,4 +18759,59 @@ label { img { display: none; } +} + +.publications { + + margin: auto; + background-color: #ffffff; + padding: 20px; + border-radius: 8px; + box-shadow: 0 0 10px rgba(0, 0, 0, 0.1); +} + + + +.publication { + margin-bottom: 40px; +} + +.publication h2 { + font-size: 1em; + color: #005b9f; + margin-bottom: 5px; +} + +.publication .title { + font-size: 1.5em; + color: #333333; + font-weight: bolder; + margin: 5px 0; +} + +.publication .journal { + font-size: 1em; + color: #666666; +} + +a { + color: black; +} + +a:link { + text-decoration: none; +} +a:visited { + text-decoration: none; +} +a:hover { + text-decoration: none; +} +a:active { + text-decoration: none; +} + +/* Solid border */ +hr.solid { + border-top: 1px solid #bbb; } \ No newline at end of file diff --git a/index.html b/index.html index 8b09475..b685d54 100644 --- a/index.html +++ b/index.html @@ -128,16 +128,16 @@
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Practice Areas

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Scientific Research

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AI Ethics and Responsibility

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Our Research

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- Domain Adaptation for Arabic Machine Translation: The Case of - Financial Texts -

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- Neural machine translation (NMT) has shown impressive - performance when trained on large-scale corpora. However, - generic NMT systems have demonstrated poor performance on - out-of-domain translation. To mitigate this issue, several - domain adaptation methods have recently been proposed which - often lead to better translation quality than genetic NMT - systems. +

Publications

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- SARD: A Human-AI Collaborative Story Generation +
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+ EMAD A. ALGHAMDI, REEM I. MASOUD, DEEMA ALNUHAIT, AFNAN Y. + ALOMAIRI, AHMED ASHRAF, MOHAMED ZAYTOON

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- Generative artificial intelligence (GenAI) has ushered in a new - era for storytellers, providing a powerful tool to ignite - creativity and explore uncharted narrative territories. As - technology continues to advance, the synergy between human - creativity and AI-generated content holds the potential to - redefine the landscape of storytelling. In this work, we propose - SARD, a drag-and-drop visual interface for generating a - multi-chapter story using large language models. +

+ + AraTrust: An Evaluation of Trustworthiness for LLMs in Arabic +

- KEEP READING +

DMLR @ICML 2024

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EMAD A. ALGHAMDI, JEZIA ZAKRAOUI, FARES A. ABANMY

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+ + Domain Adaptation for Arabic Machine Translation: The Case of + Financial Text + +

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preprint

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- AraTrust: An Evaluation of Trustworthiness for LLMs in Arabic +
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+ AHMED Y. RADWAN, KHALED M. ALASMARI, OMAR A. ABDULBAGI, EMAD A. + ALGHAMDI

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- The swift progress and widespread acceptance of artificial - intelligence (AI) systems highlight a pressing requirement to - comprehend both the capabilities and potential risks associated - with AI. Given the linguistic complexity, cultural richness, and - underrepresented status of Arabic in AI research, there is a - pressing need to focus on Large Language Models (LLMs) - performance and safety for Arabic related tasks. +

+ + SARD: A Human-AI Collaborative Story Generation +

- KEEP READING +

HCII2024

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