Academic
arXiv:2602.16189v1 Announce Type: new Abstract: Despite the continuous research and evolution of language models, they sometimes underperform previous versions. Existing approaches to overcome these challenges …
arXiv:2602.16200v1 Announce Type: new Abstract: In this thesis, I refine our understanding as to what conclusions we can reach from coreference-based evaluations by expanding existing …
arXiv:2602.16201v1 Announce Type: new Abstract: Large language models (LLMs) are trained on web-scale corpora that exhibit steep power-law distributions, in which the distribution of knowledge …
arXiv:2602.16241v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used as automated annotators to scale dataset creation, yet their reliability as unbiased annotators--especially …
arXiv:2602.16290v1 Announce Type: new Abstract: Arabic dialects have long been under-represented in Natural Language Processing (NLP) research due to their non-standardization and high variability, which …
arXiv:2602.16298v1 Announce Type: new Abstract: Large Language Models (LLMs) are beginning to reshape how media professionals verify information, yet automated support for detecting check-worthy claims …
arXiv:2602.16313v1 Announce Type: new Abstract: Existing evaluations of agents with memory typically assess memorization and action in isolation. One class of benchmarks evaluates memorization by …
arXiv:2602.16346v1 Announce Type: new Abstract: LLM-based agents execute real-world workflows via tools and memory. These affordances enable ill-intended adversaries to also use these agents to …
arXiv:2602.15834v1 Announce Type: new Abstract: We introduce a unified framework that combines nonlinear dynamics, perceptual psychophysics and high frequency haptic rendering to enhance realism in …
arXiv:2602.15842v1 Announce Type: new Abstract: Memes are a popular element of modern web communication, used not only as static artifacts but also as interactive replies …
arXiv:2602.15879v1 Announce Type: new Abstract: Exercise recommendation focuses on personalized exercise selection conditioned on students' learning history, personal interests, and other individualized characteristics. Despite notable …
arXiv:2602.15883v1 Announce Type: new Abstract: Physics-Informed Neural Networks (PINNs) offer a powerful paradigm for flow reconstruction, seamlessly integrating sparse velocity measurements with the governing Navier-Stokes …
