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Specificity

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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/rpgroup-pboc/theoretical_regseq

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Deciphering regulatory architectures from synthetic single-cell expression patterns

https://github.com/rucaibox/mpo

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Parameter-Efficient Mixture-of-Experts Architecture for Pre-trained Language Models

https://github.com/rucaibox/mpoe

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Parameter-Efficient Mixture-of-Experts Architecture for Pre-trained Language Models

https://github.com/sagizty/cellmix

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CellMix: A General Instance Relationship based Method for Data Augmentation Towards Pathology Image Classification

https://github.com/sahilsethi0105/scope-mri

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Toward Non-Invasive Diagnosis of Bankart Lesions with Deep Learning

https://github.com/saifkhichi96/situational-llm

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SituationalLLM: Proactive language models with scene awareness for dynamic, contextual task guidance

https://github.com/salesforce/hydra-sum

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HydraSum: Disentangling Stylistic Features in Text Summarization using Multi-Decoder Models

https://github.com/samgoldman97/enz-pred

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Machine learning modeling of family wide enzyme-substrate specificity screens

https://github.com/samleoqh/viola-unet

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Examining Deployment and Refinement of the VIOLA-AI Intracranial Hemorrhage Model Using an Interactive NeoMedSys Platform

https://github.com/samrelins/vulnerability_classifier_pipeline

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Using Instruction-Tuned Large Language Models to Identify Indicators of Vulnerability in Police Incident Narratives

https://github.com/samuelstjean/dpr

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Reducing variability in along-tract analysis with diffusion profile realignment

https://github.com/saptarshi059/cdqa-v1-targetted-pretraining

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TOP-Training: Target-Oriented Pretraining for Medical Extractive Question Answering

https://github.com/sarwanpasha/pwm2vec

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PWM2Vec: An Efficient Embedding Approach for Viral Host Specification from Coronavirus Spike Sequences

https://github.com/scalable-model-editing/gradual-catastrophic-forgetting

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Model Editing at Scale leads to Gradual and Catastrophic Forgetting

https://github.com/sdv4/Predicting-Confusion-with-RNN_HAI-2019

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Predicting Confusion from Eye-Tracking Data with Recurrent Neural Networks

https://github.com/sfillwo/DialCS-Reasoning

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Leveraging Explicit Reasoning for Inference Integration in Commonsense-Augmented Dialogue Models

https://github.com/shamilcm/pedra

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Can Automatic Post-Editing Improve NMT?

https://github.com/shaojintian/power_law_decay

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Power-Law Decay Loss for Large Language Model Finetuning: Focusing on Information Sparsity to Enhance Generation Quality

https://github.com/shivashankarrs/Pledge-Specificity

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Deep Ordinal Regression for Pledge Specificity Prediction

https://github.com/shlezingerlab/mbdl_book

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Model-Based Deep Learning

https://github.com/shuo-zhou/gsda-lateralization

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Group-specific discriminant analysis reveals statistically validated sex differences in lateralization of brain functional network

https://github.com/simi912/deep-convolutional-neural-network-classifier-for-alzheimer-s-disease-1

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SNeurodCNN: Structure-focused Neurodegeneration Convolutional Neural Network for Modelling and Classification of Alzheimer's Disease

https://github.com/simonvino/fusl

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Data Integration with Fusion Searchlight: Classifying Brain States from Resting-state fMRI

https://github.com/siyumu/imc_pinn_fe

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IMC-PINN-FE: A Physics-Informed Neural Network for Patient-Specific Left Ventricular Finite Element Modeling with Image Motion Consistency and Biomechanical Parameter Estimation

https://github.com/smartmediaai/personalsum

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PersonalSum: A User-Subjective Guided Personalized Summarization Dataset for Large Language Models

https://github.com/snowteam2023/medrag

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MedRAG: Enhancing Retrieval-augmented Generation with Knowledge Graph-Elicited Reasoning for Healthcare Copilot

https://github.com/spatial-privacy/3d-spatial-privacy

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Conservative Plane Releasing for Spatial Privacy Protection in Mixed Reality

https://github.com/spratm-asleaf/robustness-specificity

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Learning Against Distributional Uncertainty: On the Trade-off Between Robustness and Specificity

https://github.com/ssea-lab/DL4ETI

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Computer-aided diagnosis in histopathological images of the endometrium using a convolutional neural network and attention mechanisms

https://github.com/st-vincent1/cornell_rich

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Reference-less Analysis of Context Specificity in Translation with Personalised Language Models

https://github.com/stanford-stages/stanford-stages

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Neural network an1alysis of sleep stages enables efficient diagnosis of narcolepsy

https://github.com/steve-zeyu-zhang/DiabetesDiagnosis

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DiabetesNet: A Deep Learning Approach to Diabetes Diagnosis

https://github.com/stmharry/dental-pano-ai

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Artificial Intelligence to Assess Dental Findings from Panoramic Radiographs -- A Multinational Study

https://github.com/superboom/dialprompt

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What Do You Want? User-centric Prompt Generation for Text-to-image Synthesis via Multi-turn Guidance

https://github.com/suyan-liang/EshopInstruct

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LLaSA: Large Language and E-Commerce Shopping Assistant

https://github.com/t1ans1r/evil-geniuses

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Evil Geniuses: Delving into the Safety of LLM-based Agents

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.