Tencent (China)

Zero-Shot and Few-Shot Hydrogen Demand Forecasting with Time Series Foundation Models

Accurate hydrogen demand forecasting is essential for optimizing infrastructure investments in the emerging hydrogen economy, yet the scarcity of historical consumption data poses a fundamental challenge for conventional time series methods. We present a systematic evaluation of...

Product evolution model (PEM): a functional semantic knowledge-driven framework for product technology landscape construction

Purpose The construction of a product technology landscape remains heavily reliant on patent-based methods despite its recognized value in supporting the systematic product planning and technology opportunity identification. These patented approaches, however, are typically const...

Plug-and-Play Dramaturge: A Divide-and-Conquer Approach for Iterative Narrative Script Refinement via Collaborative LLM Agents

Although LLMs have been widely adopted for creative content generation, a single-pass process often struggles to produce high-quality long narratives. How to effectively revise and improve long narrative scripts like scriptwriters remains a significant challenge, as it demands a...

Robotic Hand‐Arm Coordinated Skill Learning for Tool Manipulation Tasks

ABSTRACT This paper focuses on the specific scenario of tool manipulation and presents a novel framework enabling robots to acquire tool manipulation skills through learning from human demonstrations. While there have been numerous studies on robotic manipulation skill learning,...

Closing the cervical screening cascade gap toward WHO 90-70-90 elimination targets: A systematic review and meta-analysis of 25 studies in 11 countries

The WHO 90-70-90 cervical cancer elimination targets require that 90% of women with screen-detected lesions receive appropriate treatment by 2030. Achieving this target depends on closing cascade gaps from screen-positive to diagnostic resolution. Whether intervention effectivene...

External validation of AI assisted colposcopy using WHO dataset for cervical precancer and cancer detection

Artificial intelligence (AI)-guided colposcopy has previously been developed to assist colposcopists in detecting cervical intraepithelial neoplasia grade 2 or worse (CIN2+) and guiding biopsies, but internal testing of the AI model could overestimate diagnostic performance. We v...

scTransMIL bridges patient-level disease states and single-cell transcriptomics for cancer screening and heterogeneity inference

Single-cell sequencing offers profound insights into tumor complexity. However, reliably linking individual cellular profiles to overall sample-level phenotypes remains computationally challenging, particularly when cell-specific annotations are absent. This disconnect limits the...

Epitope-conditioned generation of T-cell receptor β-chain CDR3 candidates using a pre-trained transformer model

Prioritizing T-cell receptor (TCR) candidates for defined peptide-HLA targets is an important step in TCR-based immunotherapy development, but it still relies heavily on laborious and expensive experimental screening. Recent advancements in generative artificial intelligence have...

Integrating human linguistic insights into AI: theory-driven representation for multilingual text-to-speech

This paper explores the integration of human linguistic insights into multilingual text-to-speech (TTS) systems by evaluating the Featurally Underspecified Lexicon (FUL) as a theory-driven input representation. Unlike data-intensive end-to end models, FUL offers a compact, interp...

An explainable biomedical foundation model via large-scale concept-enhanced vision–language pretraining

Artificial intelligence for medical imaging is required to be accurate and interpretable to clinicians. However, current multimodal biomedical foundation models often prioritize performance over explainability. Here we present ConceptCLIP, an explainable biomedical foundation mod...