Self-reported prior IPE experience showed a clearer and more consistent association with perceived collaboration than did the single-item measure of self-rated IPE knowledge, whose association was small and less consistent across domains.
Viktorija Xharra, Rosario Caruso, Florian Spada et al.· Healthcare· 0 citations
Comparison of GPT-4, BERT (bidirectional encoder representations from transformers), Gemini, and DeepSeek large language models (LLM), focusing on architectures, training methodologies, and real-world applications reveals GPT-4 excels in natural language generation and complex reasoning, supporting up to 128K tokens wi...
Kavish Sanghvi, Aparna S. Sharma, Surbhi Hooda· Computer Science and Informa...· 0 citations
LifeSciBench is introduced, a benchmark of 750 expert-authored tasks designed to evaluate whether language models can handle realistic life science research work, with each constituent task paired with a human expert-written rubric.
Amelia Liu, Andrew Ho, A. Droste et al.· bioRxiv· 5 citations· ⚡1
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
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It is suggested that primary spoken language may be associated with ANT1 performance in MHE assessments and Integrating ANT1 with serum IL-6 showed numerically improved discrimination in Mandarin speakers, whereas exploratory demographic calibration of S-ANT1 showed a numerically higher AUROC in Taiwanese Hokkien speak...
Hsin-Che Lin, Cheng-Jen Chen, Tsung-Han Wu et al.· Kaohsiung Journal of Medical...· 0 citations
In this simulation, AI-generated notes scored higher on documentation quality, varied less, and carried fewer clinically significant errors than notes written on the same consultations by junior-to-middle-grade clinicians.
H. Bergman, V. Liu, B. Austin et al.· medRxiv· 1 citation
Overall, the certainty of evidence was low to very low, downgraded primarily for these risk of bias concerns, severe imprecision (due to small sample sizes), and potential publication bias.
Yu Qin, Mei-Xuan Li, Yan-fei Li et al.· Cochrane Database of Systema...· 0 citations
This paper introduces Caduceus, a family of MoE-enhanced foundation models built with a hierarchical pre-training paradigm to jointly integrate biological and natural language, and incorporates a multi-task instruction tuning phase, enabling robust protein parsing and natural language question answering.
Mingze Yin, Yiheng Zhu, Jialu Wu et al.· Proceedings of the 32nd ACM...· 0 citations
EPIC mitigates imbalance via performance-aware expert migration and runtime expert activation, and then improves communication with topology-adaptive transport kernels and fine-grained computation-communication overlap.
Jia-Min Cao, Qingxu Li, Yaozhong Liu et al.· Conference on Applications,...· 2 citations· ⚡1
The presented framework can detect and classify GNSS spoofing attacks in real-time while requiring relatively low computational and memory resources, and is therefore suitable for deployment on resource-constrained vehicular computing platforms.
Abyad Enan, Sagar Dasgupta, Mizanur Rahman et al.· 0 citations
Evaluation results show that, while these mechanisms consume a small amount of link bandwidth, CBFC can greatly reduce receive buffer utilization, and LLR can substantially mitigate network performance degradation caused by packet corruption.
Kefei Liu, Ruixue Wang, Tianrun Jiang et al.· Conference on Applications,...· 1 citation
MGSI first encodes audio and visual streams at short-, medium-, and long-range temporal scales, preserving both local variations and global affective trends, and applies polarity- and intensity-aware enhancement to better handle ambiguous and near-neutral samples.
Shanshan Lin, Yuesheng Wu, Chao Chen et al.· 0 citations
