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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/torchdsp/torchsig

공식 코드

Large Scale Radio Frequency Signal Classification

https://github.com/tranleanh/haze-synthesis

공식 코드

Toward Improving Robustness of Object Detectors Against Domain Shift

https://github.com/transfergraph/transfergraph

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Model Selection with Model Zoo via Graph Learning

https://github.com/treelli/aroid

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AROID: Improving Adversarial Robustness Through Online Instance-Wise Data Augmentation

https://github.com/treelli/da-alone-improves-at

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Data Augmentation Alone Can Improve Adversarial Training

https://github.com/tsinghua-fib-lab/DGCN

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DGCN: Diversified Recommendation with Graph Convolutional Networks

https://github.com/tsingmessage/projection_wise_disentangling_FRL

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Projection-wise Disentangling for Fair and Interpretable Representation Learning: Application to 3D Facial Shape Analysis

https://github.com/tslmy/ICWSM2019

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Studying Cultural Differences in Emoji Usage across the East and the West

https://github.com/tsunghan-wu/redal

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ReDAL: Region-based and Diversity-aware Active Learning for Point Cloud Semantic Segmentation

https://github.com/ttesileanu/OlfactoryReceptorDistribution

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Adaptation of olfactory receptor abundances for efficient coding

https://github.com/ttuhamg/driveditfit

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DriveDiTFit: Fine-tuning Diffusion Transformers for Autonomous Driving

https://github.com/tuananhbui89/Crossing-Collaborative-Ensemble

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Improving Ensemble Robustness by Collaboratively Promoting and Demoting Adversarial Robustness

https://github.com/tueimage/mad-mil

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Multi-head Attention-based Deep Multiple Instance Learning

https://github.com/twehrbein/humr

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Utilizing Uncertainty in 2D Pose Detectors for Probabilistic 3D Human Mesh Recovery

https://github.com/twidddj/tokmangan

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Token Manipulation Generative Adversarial Network for Text Generation

https://github.com/twytock/Distinguishing_Cell_Types

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Distinguishing Cell Phenotype Using Cell Epigenotype

https://github.com/tzshi/dpp-al-parsing-naacl21

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Diversity-Aware Batch Active Learning for Dependency Parsing

https://github.com/tzt101/INADE

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Diverse Semantic Image Synthesis via Probability Distribution Modeling

https://github.com/tzwwww/ev2

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A Comprehensive Evaluation on Event Reasoning of Large Language Models

https://github.com/uark-aicv/vltint

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VLTinT: Visual-Linguistic Transformer-in-Transformer for Coherent Video Paragraph Captioning

https://github.com/uark-cviu/algonauts2023

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The Algonauts Project 2023 Challenge: UARK-UAlbany Team Solution

https://github.com/ubc-nlp/cheetah

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Cheetah: Natural Language Generation for 517 African Languages

https://github.com/ubecc/generalization-of-transformers

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Understanding the Generalization of In-Context Learning in Transformers: An Empirical Study

https://github.com/uber-research/Evolvability-ES

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Evolvability ES: Scalable and Direct Optimization of Evolvability

https://github.com/uber-research/Map-Elites-Evolutionary

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Scaling MAP-Elites to Deep Neuroevolution

https://github.com/ucl-ift/noisyenv

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Simple Noisy Environment Augmentation for Reinforcement Learning

https://github.com/uclanlp/diverse-factual

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The Factuality Tax of Diversity-Intervened Text-to-Image Generation: Benchmark and Fact-Augmented Intervention

https://github.com/uclanlp/fact-or-fair

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Fact-or-Fair: A Checklist for Behavioral Testing of AI Models on Fairness-Related Queries

https://github.com/uclanlp/kpeval

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KPEval: Towards Fine-Grained Semantic-Based Keyphrase Evaluation

https://github.com/uclanlp/paraamr

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ParaAMR: A Large-Scale Syntactically Diverse Paraphrase Dataset by AMR Back-Translation

https://github.com/ucr-optml/ctrl

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Provable and Efficient Continual Representation Learning

https://github.com/ucsc-vlaa/evp

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Unleashing the Power of Visual Prompting At the Pixel Level

https://github.com/uctb/uctb

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UCTB: An Urban Computing Tool Box for Building Spatiotemporal Prediction Services

https://github.com/udao-modeling/code

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Neural-based Modeling for Performance Tuning of Spark Data Analytics

https://github.com/udonda/structure_guided_diffusion_model

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A Structure-Guided Diffusion Model for Large-Hole Image Completion

https://github.com/uds-lsv/da-lang-id

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Cross-Domain Adaptation of Spoken Language Identification for Related Languages: The Curious Case of Slavic Languages

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