https://github.com/disha0903/spblock_cv
공식 코드Foundation for unbiased cross-validation of spatio-temporal models for species distribution modeling
Papers with Code 아카이브
Entity Resolution
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Entity resolution (also known as entity matching, record linkage, or duplicate detection) is the task of finding records that refer to the same real-world entity across different data sources (e.g., data files, books, websites, and databases). (Source: Wikipedia)
Surveys on entity resolution:
Christophides et al.: End-to-End Entity Resolution for Big Data: A Survey, 2020.
Barlaug and Gulla: Neural Networks for Entity Matching: A Survey, 2021.
The task of entity resolution is closely related to the task of entity alignment which focuses on matching entities between knowledge bases. The task of entity linking differs from entity resolution as entity linking focuses on identifying entity mentions in free text.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/dxaen/percival
공식 코드Percival: Making In-Browser Perceptual Ad Blocking Practical With Deep Learning
https://github.com/eracah/hur-detect
공식 코드https://github.com/facebookresearch/NeuralPassthrough
공식 코드https://github.com/facebookresearch/fairscale/blob/main/fairscale/experimental/nn/data_parallel/gossip/distributed.py
공식 코드SlowMo: Improving Communication-Efficient Distributed SGD with Slow Momentum
https://github.com/facebookresearch/unlikelihood_training
공식 코드https://github.com/fangshancheng/abinet-pp
공식 코드ABINet++: Autonomous, Bidirectional and Iterative Language Modeling for Scene Text Spotting
https://github.com/fmh1art/batcher
공식 코드Cost-Effective In-Context Learning for Entity Resolution: A Design Space Exploration
https://github.com/ftramer/ad-versarial
공식 코드AdVersarial: Perceptual Ad Blocking meets Adversarial Machine Learning
https://github.com/fulifeng/CGI
공식 코드Should Graph Convolution Trust Neighbors? A Simple Causal Inference Method
https://github.com/gensyn-ai/noloco
공식 코드NoLoCo: No-all-reduce Low Communication Training Method for Large Models
https://github.com/glouppe/paper-author-disambiguation
공식 코드Ethnicity sensitive author disambiguation using semi-supervised learning
https://github.com/gpapadis/dlmatchers
공식 코드A Critical Re-evaluation of Benchmark Datasets for (Deep) Learning-Based Matching Algorithms
https://github.com/guaishou74851/casnet
공식 코드https://github.com/hadijahanshahi/sdabt
공식 코드S-DABT: Schedule and Dependency-Aware Bug Triage in Open-Source Bug Tracking Systems
https://github.com/hao-ai-lab/vllm-ltr
공식 코드https://github.com/hazyresearch/fm_data_tasks
공식 코드https://github.com/huangqiang/sah
공식 코드SAH: Shifting-aware Asymmetric Hashing for Reverse $k$-Maximum Inner Product Search
https://github.com/hzhang-math/Blocking_SHAP_TL
공식 코드https://github.com/icandle/MAN
공식 코드Multi-scale Attention Network for Single Image Super-Resolution
https://github.com/iesl/stance
공식 코드Optimal Transport-based Alignment of Learned Character Representations for String Similarity
https://github.com/ironjr/semantic-draw
공식 코드SemanticDraw: Towards Real-Time Interactive Content Creation from Image Diffusion Models
https://github.com/ironjr/streammultidiffusion
공식 코드SemanticDraw: Towards Real-Time Interactive Content Creation from Image Diffusion Models
https://github.com/james-qiuhaoran/llm-serving-with-proxy-models
공식 코드Efficient Interactive LLM Serving with Proxy Model-based Sequence Length Prediction
https://github.com/jiamian-wang/s2-transformer-hsi
공식 코드S^2-Transformer for Mask-Aware Hyperspectral Image Reconstruction
https://github.com/jianzhangcs/COAST
공식 코드COAST: COntrollable Arbitrary-Sampling NeTwork for Compressive Sensing
https://github.com/jianzhangcs/ISTA-Netpp
공식 코드ISTA-Net++: Flexible Deep Unfolding Network for Compressive Sensing
https://github.com/jlrussin/icl-iwl-interplay
공식 코드The dynamic interplay between in-context and in-weight learning in humans and neural networks
https://github.com/joey1993/bert-defender
공식 코드Learning to Discriminate Perturbations for Blocking Adversarial Attacks in Text Classification
https://github.com/jonathanschuchart/eager
공식 코드EAGER: Embedding-Assisted Entity Resolution for Knowledge Graphs
https://github.com/jrash/chemmodlab
공식 코드chemmodlab: A Cheminformatics Modeling Laboratory for Fitting and Assessing Machine Learning Models
https://github.com/junghunl/diffim
공식 코드DiffIM: Differentiable Influence Minimization with Surrogate Modeling and Continuous Relaxation
https://github.com/kargaranamir/Wide-AdGraph
공식 코드Wide-AdGraph: Detecting Ad Trackers with a Wide Dependency Chain Graph
https://github.com/lakeraai/dsec-gandalf
공식 코드https://github.com/limorigu/pragmaticfairness
공식 코드Pragmatic Fairness: Developing Policies with Outcome Disparity Control
https://github.com/liuzrcc/PIRE
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.