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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/bee-hive/BIISQ
공식 코드BIISQ: Bayesian nonparametric discovery of Isoforms and Individual Specific Quantification
https://github.com/behramtheberry/kpranking-with-sfo
공식 코드https://github.com/belalugax/rigid-origami
공식 코드https://github.com/berkeley-speech-group/llm-dys
공식 코드Analysis and Evaluation of Synthetic Data Generation in Speech Dysfluency Detection
https://github.com/berkeleyautomation/alphagarden
공식 코드AlphaGarden: Learning to Autonomously Tend a Polyculture Garden
https://github.com/bernardoleite/few-shot-prompting-qg-control
공식 코드On Few-Shot Prompting for Controllable Question-Answer Generation in Narrative Comprehension
https://github.com/beyond-zw/dlan-ac
공식 코드Dynamic Local Aggregation Network with Adaptive Clusterer for Anomaly Detection
https://github.com/bezirganyan/luma
공식 코드LUMA: A Benchmark Dataset for Learning from Uncertain and Multimodal Data
https://github.com/bfelbo/deepmoji
공식 코드https://github.com/bhofstra/diversity_innovation_paradox
공식 코드https://github.com/bigai-ai/adasociety
공식 코드AdaSociety: An Adaptive Environment with Social Structures for Multi-Agent Decision-Making
https://github.com/bigscience-workshop/biomedical
공식 코드BigBIO: A Framework for Data-Centric Biomedical Natural Language Processing
https://github.com/bilican/sparse_peft
공식 코드Exploring Sparsity for Parameter Efficient Fine Tuning Using Wavelets
https://github.com/bill-cjb/nhde
공식 코드Neural Multi-Objective Combinatorial Optimization with Diversity Enhancement
https://github.com/binary-husky/unreal-hmp
공식 코드Learning Heterogeneous Agent Cooperation via Multiagent League Training
https://github.com/birlrobotics/rlkit_autotune
공식 코드Hyperparameter Auto-tuning in Self-Supervised Robotic Learning
https://github.com/bit-da/dcg
공식 코드https://github.com/bjing2016/alphaflow
공식 코드AlphaFold Meets Flow Matching for Generating Protein Ensembles
https://github.com/bjork-crypto/visled-querying
공식 코드Language-Driven Active Learning for Diverse Open-Set 3D Object Detection
https://github.com/blackfeather-wang/ISDA-for-Deep-Networks
공식 코드https://github.com/bladewaltz1/modecap
공식 코드Learning Distinct and Representative Styles for Image Captioning
https://github.com/blasif/cocons
공식 코드https://github.com/blasif/j.environ.2024
공식 코드https://github.com/blester125/multi-look-embeddings
공식 코드Multiple Word Embeddings for Increased Diversity of Representation
https://github.com/blmoistawinde/KPCNet
공식 코드Diverse and Specific Clarification Question Generation with Keywords
https://github.com/bluewhalelab/dcscore
공식 코드https://github.com/bluezeros/medcare
공식 코드MedCare: Advancing Medical LLMs through Decoupling Clinical Alignment and Knowledge Aggregation
https://github.com/bobxwu/cfdtm
공식 코드https://github.com/bobxwu/topmost
공식 코드https://github.com/bobxwu/traco
공식 코드On the Affinity, Rationality, and Diversity of Hierarchical Topic Modeling
https://github.com/boese0601/dyadic-interaction-modeling
공식 코드https://github.com/bojarlab/gifflar
공식 코드Higher-Order Message Passing for Glycan Representation Learning
https://github.com/bomatter/participant-diversity-paper
공식 코드Is Limited Participant Diversity Impeding EEG-based Machine Learning?
https://github.com/bonaventuredossou/ffr-v1
공식 코드https://github.com/boranhan/geospatial_foundation_models
공식 코드Bridging Remote Sensors with Multisensor Geospatial Foundation Models
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.