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  • SignLLM: A Multilingual Sign Language Model that can Generate Sign Language Gestures from Input Text

    31 мая, 2024

    The primary goal of Sign Language Production (SLP) is to create sign avatars that resemble humans using text inputs. The standard procedure for SLP methods based on deep learning involves several steps. First, the text is translated into gloss, a language that represents postures and gestures. This gloss is then used to generate a video… →

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  • MedVersa: A Generalist Learner that Enables Flexible Learning and Tasking for Medical Image Interpretation

    31 мая, 2024

    Despite the advancement of artificial intelligence in the field of medical science, these systems have limited application. This limitation creates a gap in developing AI solutions for specific tasks. Researchers from Harvard Medical School, USA; Jawaharlal Institute of Postgraduate Medical Education and Research, India; and Scripps Research Translational Institute, USA, proposed MedVersa to address the… →

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  • Enhancing Self-Supervised Learning with Automatic Data Curation: A Hierarchical K-Means Approach

    31 мая, 2024

    Self-supervised features are central to modern machine learning, typically requiring extensive human effort for data collection and curation, similar to supervised learning. Self-supervised learning (SSL) allows models to be trained without human annotations, enabling scalable data and model expansion. However, scaling efforts have sometimes resulted in subpar performance due to issues like the long-tail distribution… →

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  • Static palpation ain’t easy: Evaluating palpation precision using a topographical map of the lumbar spine as a reference

    31 мая, 2024

    CONCLUSIONS: Comparison of palpation results to a topographic standard representing the lumbar lordosis is a new approach for evaluating palpation. Our results confirm the results of prior studies that find palpation of lumbar spinous processes imprecise, even for experienced clinicians. →

    Clinical Trials
  • In-Context Learning Capabilities of Multi-Layer Perceptrons MLPs: A Comparative Study with Transformers

    31 мая, 2024

    Recent years have seen significant advances in neural language models, particularly Large Language Models (LLMs) enabled by the Transformer architecture and increased scale. LLMs exhibit exceptional skills in generating grammatical text, answering questions, summarising content, creating imaginative outputs, and solving complex puzzles. A key capability is in-context learning (ICL), where the model uses novel task… →

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  • Microsoft AI for Good Introduces Pytorch-Wildlife: An Open-Source Deep Learning Platform Built on PyTorch

    31 мая, 2024

    Human activities increasingly threaten wildlife’s role in maintaining ecosystem balance, highlighting the critical need for large-scale biodiversity monitoring. Addressing the logistical challenges of fieldwork and data collection, especially in remote and biodiverse regions, has led to the deployment of automated data collection devices. These include camera traps, autonomous recording units, and overhead cameras on drones… →

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  • Mobile Phone-Based Confidential Social Network Referrals for HIV Testing (CONSORT): Protocol for a Randomized Controlled Trial

    30 мая, 2024

    CONCLUSIONS: If CONSORT is acceptable and effective for increasing the uptake of HIV testing, given the minimal costs of SMS text reminders and the potential for exponential but targeted growth using chain referrals, it may shift current practices for HIV testing programs in the area. →

    Clinical Trials
  • Tofacitinib is an effective treatment for moderate to severe ulcerative colitis, and intestinal ultrasound can discriminate response from non-response: a pragmatic prospective real-world study

    30 мая, 2024

    CONCLUSION: In this real-world pragmatic prospective study, tofacitinib was an effective treatment for moderate to severe UC, and IUS at week 8 accurately discriminated treatment response from non-response. →

    Clinical Trials
  • Advancing Ethical AI: Preference Matching Reinforcement Learning from Human Feedback RLHF for Aligning LLMs with Human Preferences

    30 мая, 2024

    Large language models (LLMs) like ChatGPT-4 and Claude-3 Opus excel in tasks such as code generation, data analysis, and reasoning. Their growing influence in decision-making across various domains makes it crucial to align them with human preferences to ensure fairness and sound economic decisions. Human preferences vary widely due to cultural backgrounds and personal experiences,… →

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  • How to Send a Follow-Up Email After No Response [+ 19 Examples]

    30 мая, 2024

    On average, salespeople who send at least one follow-up email after no response reach a 27% reply rate. Those who don’t send one get stuck at a 16% average reply rate. You don’t want that 11-point gap to cost you a major contract or prevent you from exceeding quota. In this post, I’ll show you… →

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