large language models

Optimization of Machine Learning–Based Recommendation Systems on E-Commerce Platforms

The findings indicate that deep learning, hybrid recommendation models, sequential recommendation approaches, and large language model–based systems significantly enhance recommendation accuracy and personalization in e-commerce environments.

Idiomatic Creativity and Emergent Fixedness: Gradient Lexical Specification in Large-Scale Cross-Linguistic Corpora

Abstract This paper demonstrates that idiomatic fixedness is manipulation-dependent: the constructional elements that resist omission in idiom variants are systematically different from those that resist replacement. Using a manually verified dataset of over 14,000 idiomatic variants across 25 idioms in three languages...

ChatSeven: An Agentic AI-Based Multi-Agent Platform for Multi-Channel Customer Conversation Management and Campaign Automation

Abstract—Customer engagement platforms increasingly re-quire artificial intelligence (AI), multi-channel messaging, work-flow automation, and outbound campaign delivery within a single operational system. Traditional conversational agents—including rule-based chatbots, retrieval-augmented generation (RAG) only bots, an...

Exploring the Development of AI-Mediated Competence for Sustainable Translation and Interpreting Education: A Bibliometric Review

The keywords evidence points to a shift from machine translation, post-editing, and translation technology training toward AI literacy, evaluative judgement, output verification, feedback practices, ethical responsibility, professional agency, and human-AI collaboration.

Large language models-driven public perception modeling in metro-led underground space: a case study of Hong Kong

Reimagining biomedical science workflows in the age of large language models

Large language models (LLMs) are generative artificial intelligence (AI) models that are rapidly reshaping the practice of biomedical science. Their ability to synthesize literature, generate analytical code, and interface with multimodal data offers a new framework for accelerating discovery. Yet their integration int...

Mechanistic understanding and peptide ingredient screening for type III collagen via biological knowledge graph and molecular docking

Abstract Objective Type III collagen plays a key role in maintaining skin elasticity and dermal resilience, yet its decline is associated with visible signs of skin ageing. This study aimed to establish a data‐driven approach to identify cosmetic peptides with potential to enhance type III collagen through multi‐target...

Comparing Human‐Created and NotebookLM‐Generated Podcasts for EAP Instruction: Differences in Linguistic Complexity and the Role of Prompt Design

ABSTRACT Science popularization podcasts are valuable resources for EAP instruction because they make academic content more accessible to learners. However, producing high‐quality podcasts is time‐consuming and resource‐intensive, and existing resources may not always align with instructional goals or learners’ needs....

DEL-GPT: learning the language of DNA-encoded libraries to design focused screening collections

Focused DNA-encoded libraries (DELs) yield higher hit rates and cleaner selection data than billioncompound collections, and are affordable enough to build for a single target. Designing one means choosing a few hundred synthons from a much larger pool, and in the split-and-pool format that choice is collective and irr...

A review of bias detection and fairness auditing techniques in LLMs

A thorough literature review is provided to encapsulate prior research on bias identification and fairness auditing, categorizing the findings according to various stages of study and proposing a unified pipeline for dataset integration and a modular framework for bias auditing.

Adapting NDBIs for Autistic Children Who Use Echolalia: A Cascading Coaching Approach to Supporting Communication and Language Development

This pilot study examined a cascading coaching model to train graduate student clinicians and caregivers to use adapted Naturalistic Developmental Behavioral Intervention (NDBI) techniques with autistic preschoolers who use echolalia. Adaptations were designed to incorporate children’s echolalic speech within intervent...

SciRep: A Ranking-Aware Representation Model for Scientific Text

Results demonstrate that the proposed ranking-aware distillation mechanism significantly enhances scientific text representation quality while maintaining efficient inference, offering a more effective contrastive learning method for domain-specific retrieval tasks.