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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/flowersteam/holmes

공식 코드

Hierarchically Organized Latent Modules for Exploratory Search in Morphogenetic Systems

https://github.com/flowersteam/sensorimotor-lenia-search

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Discovering Sensorimotor Agency in Cellular Automata using Diversity Search

https://github.com/fmy266/tpa

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Transferability Bound Theory: Exploring Relationship between Adversarial Transferability and Flatness

https://github.com/for-ai/iterative-data-selection

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Diversify and Conquer: Diversity-Centric Data Selection with Iterative Refinement

https://github.com/foralan/equiboost

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EquiBoost: An Equivariant Boosting Approach to Molecular Conformation Generation

https://github.com/forblindrev/aibias

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Fair and accurate age prediction using distribution aware data curation and augmentation

https://github.com/forrest-stone/cmb

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Counterfactual Multi-player Bandits for Explainable Recommendation Diversification

https://github.com/forrest-stone/diversity

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Result Diversification in Search and Recommendation: A Survey

https://github.com/fraleo/robust_counterfactuals_aaai24

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Promoting Counterfactual Robustness through Diversity

https://github.com/francescodisalvo05/cvae-anonymization

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Privacy-preserving datasets by capturing feature distributions with Conditional VAEs

https://github.com/frank-wang-oss/temsr

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Temporal Source Recovery for Time-Series Source-Free Unsupervised Domain Adaptation

https://github.com/frank-xwang/RIDE-LongTailRecognition

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Long-tailed Recognition by Routing Diverse Distribution-Aware Experts

https://github.com/fraunhofer-iis/odaq

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ODAQ: Open Dataset of Audio Quality

https://github.com/freedomintelligence/rag-instruct

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RAG-Instruct: Boosting LLMs with Diverse Retrieval-Augmented Instructions

https://github.com/frohleon/personas-with-attitudes

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Personas with Attitudes: Controlling LLMs for Diverse Data Annotation

https://github.com/fromm-m/ecir2021-am-search

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Diversity Aware Relevance Learning for Argument Search

https://github.com/fu-dayuan/preact

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PreAct: Prediction Enhances Agent's Planning Ability

https://github.com/fuchuanqu/gianthunter

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GiantHunter: Accurate detection of giant virus in metagenomic data using reinforcement-learning and Monte Carlo tree search

https://github.com/fudan-zvg/pds

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Accelerating Score-based Generative Models with Preconditioned Diffusion Sampling

https://github.com/fudan-zvg/wovogen

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WoVoGen: World Volume-aware Diffusion for Controllable Multi-camera Driving Scene Generation

https://github.com/fudandisc/socioverse

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SocioVerse: A World Model for Social Simulation Powered by LLM Agents and A Pool of 10 Million Real-World Users

https://github.com/fufy1024/so-tvae

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Sentiment-oriented Transformer-based Variational Autoencoder Network for Live Video Commenting

https://github.com/fulin-gao/opengcd

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OpenGCD: Assisting Open World Recognition with Generalized Category Discovery

https://github.com/fuqianggu/EventDrop

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EventDrop: data augmentation for event-based learning

https://github.com/future-iqa/mmp-2k

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MMP-2K: A Benchmark Multi-Labeled Macro Photography Image Quality Assessment Database

https://github.com/fxw13/OWD

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An Open-World, Diverse, Cross-Spatial-Temporal Benchmark for Dynamic Wild Person Re-Identification

https://github.com/g-benton/hessian-eff-dim

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Rethinking Parameter Counting in Deep Models: Effective Dimensionality Revisited

https://github.com/g-jwlee/coincide_code

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Concept-skill Transferability-based Data Selection for Large Vision-Language Models

https://github.com/g-jwlee/tamp

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TAMP: Token-Adaptive Layerwise Pruning in Multimodal Large Language Models

https://github.com/g6000/MultiAgent-Research-Ideator

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Exploring Design of Multi-Agent LLM Dialogues for Research Ideation

https://github.com/gablabc/partial_order_in_chaos

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Partial Order in Chaos: Consensus on Feature Attributions in the Rashomon Set

https://github.com/gabriel-turinici/huber-energy-measure-quantization

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Diversity in deep generative models and generative AI

https://github.com/gabrielkmbo/explore-rl

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Step-wise Policy for Rare-tool Knowledge (SPaRK): Offline RL that Drives Diverse Tool Use in LLMs

https://github.com/gabrielnobis/gfdm

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Generative Fractional Diffusion Models

https://github.com/gabrielraya/symmetry_breaking_diffusion_models

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Spontaneous Symmetry Breaking in Generative Diffusion Models

https://github.com/gair-nlp/mops

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MoPS: Modular Story Premise Synthesis for Open-Ended Automatic Story Generation

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