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Diversity
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Diversity in data sampling is crucial across various use cases, including search, recommendation systems, and more. Ensuring diverse samples means capturing a wide range of variations and perspectives, which leads to more robust, unbiased, and comprehensive models. In search use cases, for instance, diversity helps avoid redundancy, ensuring that users are exposed to a broader set of relevant information rather than repeated similar results.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/castacks/tartanaviation
공식 코드TartanAviation: Image, Speech, and ADS-B Trajectory Datasets for Terminal Airspace Operations
https://github.com/causalnlp/ai-scholar-gender
공식 코드Voices of Her: Analyzing Gender Differences in the AI Publication World
https://github.com/cavespiderlzj/poseaugment-eccv2024
공식 코드https://github.com/cc-hpc-itwm/facialgan
공식 코드FacialGAN: Style Transfer and Attribute Manipulation on Synthetic Faces
https://github.com/cchen23/layout_distribution_shift
공식 코드https://github.com/ccyyatnet/COLORGAN
공식 코드Unsupervised Diverse Colorization via Generative Adversarial Networks
https://github.com/ceciliaresearch/nondeterminism_instability
공식 코드Nondeterminism and Instability in Neural Network Optimization
https://github.com/celebv-hq/celebv-hq
공식 코드https://github.com/cellistigs/interp_ensembles
공식 코드https://github.com/cemos-is/text3daug-augmentation
공식 코드Text3DAug -- Prompted Instance Augmentation for LiDAR Perception
https://github.com/cfn-softbio/scibot
공식 코드https://github.com/chailab-umich/GPT-4-Emotion-Annotation
공식 코드From Text to Emotion: Unveiling the Emotion Annotation Capabilities of LLMs
https://github.com/chaitjo/geometric-rna-design
공식 코드https://github.com/chaochun/nlu-asdiv-dataset
공식 코드A Diverse Corpus for Evaluating and Developing English Math Word Problem Solvers
https://github.com/chaolongy/kdtalker
공식 코드https://github.com/chappers/diverse-online-feature-selection
공식 코드https://github.com/charliemat/gfn4rec
공식 코드https://github.com/charlotte-charmlab/fibottention
공식 코드Fibottention: Inceptive Visual Representation Learning with Diverse Attention Across Heads
https://github.com/charrrrrlie/mask-as-supervision
공식 코드Mask as Supervision: Leveraging Unified Mask Information for Unsupervised 3D Pose Estimation
https://github.com/chartsquared/c-2
공식 코드$C^2$: Scalable Auto-Feedback for LLM-based Chart Generation
https://github.com/chasonshi/melora
공식 코드MELoRA: Mini-Ensemble Low-Rank Adapters for Parameter-Efficient Fine-Tuning
https://github.com/chaudatascience/diverse_channel_vit
공식 코드Enhancing Feature Diversity Boosts Channel-Adaptive Vision Transformers
https://github.com/chehx/MKCNet
공식 코드Image Quality-aware Diagnosis via Meta-knowledge Co-embedding
https://github.com/chen700564/metaner-icl
공식 코드https://github.com/chenboluo/adversarial-defense
공식 코드Improving Adversarial Robustness via Decoupled Visual Representation Masking
https://github.com/chencn2020/PromptIQA
공식 코드https://github.com/chengqiarchy/mermaidflow
공식 코드MermaidFlow: Redefining Agentic Workflow Generation via Safety-Constrained Evolutionary Programming
https://github.com/chengyaowen/pareto-optimal-rule-subset-selection
공식 코드On Finding Bi-objective Pareto-optimal Fraud Prevention Rule Sets for Fintech Applications
https://github.com/chengyaowen/pors
공식 코드On Finding Bi-objective Pareto-optimal Fraud Prevention Rule Sets for Fintech Applications
https://github.com/chengzelei/crowdsource_toxicity_classification
공식 코드https://github.com/chengzhag/DeepPanoContext
공식 코드https://github.com/chenhao2345/ABMT
공식 코드https://github.com/chenhongyiyang/ppal
공식 코드https://github.com/chenhui07c8/DOA-AOA-algorithms
공식 코드DOA Estimation with Non-Uniform Linear Arrays: A Phase-Difference Projection Approach
https://github.com/chenmc1996/Multi-Head-Co-Training
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.