Our experiment shows that through a simple strategy – having humans chat with models while completing a task – we can help humans perform better at these tasks. This is very encouraging, albeit preliminary!
MACHINE LEARNING
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Non-Experts Answer Expert Questions on MMLU and QuALITY
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We ask non-experts to answer expert-level questions on MMLU, and also ask people to answer questions about long QuALITY passages under a time limit that’s too short for a careful read.
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Scalable Oversight Framework and Language Model Question-Answering Proof of Concept
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Along with developing a framework for scalable oversight, we also conduct a proof of concept experiment that demonstrates a couple of question-answering tasks that work well under this paradigm with current language models:
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Challenges in Studying Model Assistance: Task Selection and Experimental Design
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It’s also challenging to study: For most tasks today, we don’t actually need our model’s help in this way. So testing these methods will require us to be clever about how we choose our tasks and design our experiments.
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AI Systems Improving Human Oversight of Large Language Models
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In "Measuring Progress on Scalable Oversight for Large Language Models” we show how humans could use AI systems to better oversee other AI systems, and demonstrate some proof-of-concept results where a language model improves human performance at a task.
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How Much Does Attention Actually Attend in Transformers?
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How Much Does Attention Actually Attend? Questioning the Importance of Attention in Pretrained Transformers Hassid et al.: https://
arxiv.org/abs/2211.03495 #ArtificialIntelligence #DeepLearning #MachineLearning -
Transfer Learning for Medical Imaging and X-Ray Diagnosis with AI
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It's World Radiography Day Radiographs have come a long way since its inception. Today with the help of AI, medical diagnosis has had a lot of innovations. Transfer Learning is one such innovation that finds use in medical imaging like X-Rays. https://
learnopencv.com/transfer-learn
ing-for-medical-images/
… #xray #ai -
YOLOv7 Pose: Single-Stage Multi-Person Keypoint Detection
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Unlike conventional Pose Estimation algorithms, YOLOv7 pose is a single-stage multi-person keypoint detector. It is similar to the bottom-up approach but heatmap free. It is an extension of the one-shot pose detector – YOLO-Pose. https://
learnopencv.com/yolov7-pose-vs
-mediapipe-in-human-pose-estimation/
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#yolov7 #poseestimation -
Catherine Adenle Daily: AI and Machine Learning Updates
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The latest The Catherine Adenle Daily! https://
paper.li/CatherineAdenl
e?edition_id=c9e86830-5f2a-11ed-9d70-fa163ed80008
… #ai #machinelearning