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NEW

SalamahBench: Standardizing Safety for Arabic Language Models

Arabic language models are growing rapidly, with adoption rising across education, healthcare, and customer service sectors. Over 400 million people speak Arabic globally, and regional dialects add layers of complexity to model training. Yet this growth exposes critical safety gaps. Misinformation…
Thumbnail Image of Tutorial SalamahBench: Standardizing Safety for Arabic Language Models
Image of Author Dr. Dipen
Dr. Dipen
I am an AI/ML researcher with 150+ citations and 16 published research papers. I have three tier-1 publications, including Internet of Things (Elsevier), Biomedical Signal Processing and Control (Elsevier), and IEEE Access. In my research journey, I have collaborated with NASA Glenn Research Center, Cleveland Clinic, and the U.S. Department of Energy for various research projects. I am also an official reviewer and have reviewed over 100 research papers for Elsevier, IEEE Transactions, ICRA, MDPI, and other top journals and conferences. I hold a PhD from Cleveland State University with a focus on large language models (LLMs) in cybersecurity, and I also earned a master’s degree in informatics from Northeastern University.
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Self‑Evolving Search to Reduce Hallucinations in RAG

Reducing hallucinations in Retrieval-Augmented Generation (RAG) is critical for maintaining reliability in AI-driven systems. When a model generates false or misleading information, it erodes trust and introduces risks for businesses, developers, and end users. For example, a customer support…
Thumbnail Image of Tutorial Self‑Evolving Search to Reduce Hallucinations in RAG
Image of Author Dr. Dipen
Dr. Dipen
I am an AI/ML researcher with 150+ citations and 16 published research papers. I have three tier-1 publications, including Internet of Things (Elsevier), Biomedical Signal Processing and Control (Elsevier), and IEEE Access. In my research journey, I have collaborated with NASA Glenn Research Center, Cleveland Clinic, and the U.S. Department of Energy for various research projects. I am also an official reviewer and have reviewed over 100 research papers for Elsevier, IEEE Transactions, ICRA, MDPI, and other top journals and conferences. I hold a PhD from Cleveland State University with a focus on large language models (LLMs) in cybersecurity, and I also earned a master’s degree in informatics from Northeastern University.
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NEW

Standardizing LLM Evaluation with a Unified Rubric

Watch: UEval: New Benchmark for Unified Generation by AI Research Roundup Standardizing LLM evaluation isn’t just a technical detail-it’s a critical step toward ensuring trust, consistency, and progress in AI development. Right now, the market is fragmented. Studies show that evaluation criteria…
Thumbnail Image of Tutorial Standardizing LLM Evaluation with a Unified Rubric
Image of Author Dr. Dipen
Dr. Dipen
I am an AI/ML researcher with 150+ citations and 16 published research papers. I have three tier-1 publications, including Internet of Things (Elsevier), Biomedical Signal Processing and Control (Elsevier), and IEEE Access. In my research journey, I have collaborated with NASA Glenn Research Center, Cleveland Clinic, and the U.S. Department of Energy for various research projects. I am also an official reviewer and have reviewed over 100 research papers for Elsevier, IEEE Transactions, ICRA, MDPI, and other top journals and conferences. I hold a PhD from Cleveland State University with a focus on large language models (LLMs) in cybersecurity, and I also earned a master’s degree in informatics from Northeastern University.
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NEW

SteerEval: Measuring How Controllable LLMs Really Are

Evaluating LLM controllability isn’t just an academic exercise-it’s a critical factor determining how effectively businesses and developers can deploy these models in real-world scenarios. As LLM adoption grows rapidly across industries like healthcare, finance, and customer service, the ability to…
Thumbnail Image of Tutorial SteerEval: Measuring How Controllable LLMs Really Are
Image of Author Dr. Dipen
Dr. Dipen
I am an AI/ML researcher with 150+ citations and 16 published research papers. I have three tier-1 publications, including Internet of Things (Elsevier), Biomedical Signal Processing and Control (Elsevier), and IEEE Access. In my research journey, I have collaborated with NASA Glenn Research Center, Cleveland Clinic, and the U.S. Department of Energy for various research projects. I am also an official reviewer and have reviewed over 100 research papers for Elsevier, IEEE Transactions, ICRA, MDPI, and other top journals and conferences. I hold a PhD from Cleveland State University with a focus on large language models (LLMs) in cybersecurity, and I also earned a master’s degree in informatics from Northeastern University.
•Last Updated:
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NEW

Speeding Up LLM Function Calls with Parallel Decoding

Watch: Faster LLMs: Accelerate Inference with Speculative Decoding by IBM Technology Modern applications relying on large language models (LLMs) face a critical bottleneck: the sequential nature of traditional decoding methods. Most LLMs generate text one token at a time, creating a dependency…
Thumbnail Image of Tutorial Speeding Up LLM Function Calls with Parallel Decoding
Image of Author Dr. Dipen
Dr. Dipen
I am an AI/ML researcher with 150+ citations and 16 published research papers. I have three tier-1 publications, including Internet of Things (Elsevier), Biomedical Signal Processing and Control (Elsevier), and IEEE Access. In my research journey, I have collaborated with NASA Glenn Research Center, Cleveland Clinic, and the U.S. Department of Energy for various research projects. I am also an official reviewer and have reviewed over 100 research papers for Elsevier, IEEE Transactions, ICRA, MDPI, and other top journals and conferences. I hold a PhD from Cleveland State University with a focus on large language models (LLMs) in cybersecurity, and I also earned a master’s degree in informatics from Northeastern University.
•Last Updated:
00
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