Large Language Models (LLMs) have unlocked new capabilities and applications; however,
evaluating the alignment with human preferences still poses significant challenges. To …

Recent statements about the impressive capabilities of large language models (LLMs) are
usually supported by evaluating on open-access benchmarks. Considering the vast size and …

Artificial neural networks (ANNs) can help camera-based remote photoplethysmography
(rPPG) in measuring cardiac activity and physiological signals from facial videos, such as …

Large language models (LLMs) have shown great potential in complex reasoning tasks, yet
their performance is often hampered by the scarcity of high-quality, reasoning-focused …

How to evaluate Large Language Models (LLMs) in code generation is an open question.
Existing benchmarks demonstrate poor alignment with real-world code repositories and are …

Large Language Models (LLMs) applied to code-related applications have emerged as a
prominent field, attracting significant interest from both academia and industry. However, as …

Computing olympiads contain some of the most challenging problems for humans, requiring
complex algorithmic reasoning, puzzle solving, in addition to generating efficient code …

The rapid development of Large Language Models (LLMs) like GPT-4, Claude-3, and
Gemini has transformed the field of natural language processing. However, it has also …

In this work, we introduce a novel evaluation paradigm for Large Language Models, one that
challenges them to engage in meta-reasoning. This approach addresses critical …

We show that existing evaluations for fake news detection based on conventional sources,
such as claims on fact-checking websites, result in high accuracies over time for LLM-based …