These findings show that reliable evaluation of LLM-generated code requires validated ground truth, protected tests, and multiple explicitly interpreted measures, and that CodeAssay provides a reproducible basis for evidence-based model evaluation in AI-augmented software development.
Shahbaz Siddeeq, Muhammad Waseem, Umar Subhan Malhi et al.· 0 citations
The Comprehensive VS Platform with AI Engine (CVSP-AIE) for drug discovery from compound libraries integrates three AI models: KarmaDock, a fast docking model that directly updates atomic coordinates; CarsiDock, an accurate docking model that predicts protein-ligand distances and reconstructs binding poses; and RTMScor...
While ChatGPT was primarily viewed as an efficient tool in a work context, the quantitative survey reveals a weakly significant correlation between psychological stress and openness toward the social-emotional use of chatbots.
Stefanie Osetrow, H. Klapperich, A. Huldtgren· Message Understanding Confer...· 0 citations
It is revealed that GenAI texts underrepresent the subtle interpersonal cues that give writing its persuasive, dialogic, and ethical texture, though they excel in both grammatical accuracy, and lexical variety.
Daniel Tchorkpa Yokossi, Servais Dieu-Donné Yédia Dadjo, Cocou Andre Datondji· International Journal of Adv...· 0 citations
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Current structure-based drug design generative models often struggle to faithfully recapitulate genuine ligand-protein binding interactions. Instead, under the coupling of implicit learning architectures and biased training data, they tend to learn spurious statistical correlations. To address this, we propose EIP-Diff...
Huabin Du, Mingyang Wang, M. Luo et al.· Journal of the American Chem...· 0 citations
It is argued that both AI and bullshitters are untrustworthy informants, and for similar reasons, it is natural to describe AI’s informational outputs as bullshit, as it signals their distinctive kind of epistemic deficiencies, which they share with bullshit.
This conceptual paper argues that Theatre in Education (TIE), long valued for cultivating empathy, embodied cognition, and critical reflection, offers a necessary human-centred counterweight to the efficiency-oriented logic of AI-driven instruction.
Senapati Nayak, C. Vazalwar, S. Padhi· International Journal for Re...· 0 citations
The reviewed literature indicates that AI-based methodologies often demonstrate superior detection capabilities for intricate and previously unseen attack patterns compared to traditional methods; however, direct performance comparisons are complicated due to discrepancies in datasets, experimental designs, and evaluat...
Jaswanth Garugu· International Journal for Re...· 0 citations
Nursing education must respond proactively by establishing AI literacy frameworks, revising academic integrity policies, and embedding source verification and citation skills into curricula, as generative AI threatens to erode the scholarly standards essential to both academic rigor and professional nursing practice.
Kechi C. Iheduru-Anderson· Nurse Education Today· 1 citation
Professor Ali Jadbabaie describes how AI, digital transformation, climate change, and complex geopolitics are forcing engineers and policymakers to rethink how infrastructure is designed, built, and managed.
MIT News · Artificial Intelligence· news.mit.eduOct 27, 2026
Prabha Jha used her experience with MIT Open Learning’s program for senior executives to develop AI solutions for her employer, Verizon, and to write a book.
In Compton Lecture, the distinguished legal scholar warns of potential “loss of the Enlightenment” while suggesting ways innovations can meet our civic and cultural needs.