Large language models (LLMs) are a class of language models that have demonstrated
outstanding performance across a range of natural language processing (NLP) tasks and …

Real-time learning concerns the ability of learning systems to acquire knowledge over time,
enabling their adaptation and generalization to novel tasks. It is a critical ability for …

Evaluation of large language models (LLMs) has raised great concerns in the community
due to the issue of data contamination. Existing work designed evaluation protocols using …

Large foundation models (LFMs) are claiming incredible performances. Yet great concerns
have been raised about their mythic and uninterpreted potentials not only in machine …

Evaluation of large language models (LLMs) has raised great concerns in the community
due to the issue of data contamination. Existing work designed evaluation protocols using …

Understanding the reasoning capabilities of Multimodal Large Language Models (MLLMs) is
an important area of research. In this study, we introduce a dynamic benchmark …

Causality reveals fundamental principles behind data distributions in real-world scenarios,
and the capability of large language models (LLMs) to understand causality directly impacts …

Evaluating large language models (LLMs) is challenging. Traditional ground-truth-based
benchmarks fail to capture the comprehensiveness and nuance of real-world queries, while …

Large Language Models (LLMs) have rapidly become important tools in Biomedical and
Health Informatics (BHI), enabling new ways to analyze data, treat patients, and conduct …

This study intends to systematically disentangle pure logic reasoning and text understanding
by investigating the contrast across abstract and contextualized logical problems from a …