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Memorization

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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/1980x/ABAW2021DMACS

공식 코드

Affect Expression Behaviour Analysis in the Wild using Consensual Collaborative Training

https://github.com/1980x/CCT

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Consensual Collaborative Training And Knowledge Distillation Based Facial Expression Recognition Under Noisy Annotations

https://github.com/1azybug/forgettingcurve

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Forgetting Curve: A Reliable Method for Evaluating Memorization Capability for Long-context Models

https://github.com/AdaBit-AI/parameter_efficient_instruction_tuning

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Parameter Efficient Instruction Tuning: An Empirical Study

https://github.com/AntonioCarta/rnn_autoencoding_neurips2020

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Short-Term Memory Optimization in Recurrent Neural Networks by Autoencoder-based Initialization

https://github.com/Aries-chen/MedEditBench

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Beyond Memorization: A Rigorous Evaluation Framework for Medical Knowledge Editing

https://github.com/BennoKrojer/reasoning-over-facts

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Are Pretrained Language Models Symbolic Reasoners Over Knowledge?

https://github.com/BenoitChoffin/das3h

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DAS3H: Modeling Student Learning and Forgetting for Optimally Scheduling Distributed Practice of Skills

https://github.com/CGCL-codes/naturalcc

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Does Your Neural Code Completion Model Use My Code? A Membership Inference Approach

https://github.com/CPJKU/musical_distribution_shift

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Quantifying the Corpus Bias Problem in Automatic Music Transcription Systems

https://github.com/Cardio-AI/memorization-ldm

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Unconditional Latent Diffusion Models Memorize Patient Imaging Data: Implications for Openly Sharing Synthetic Data

https://github.com/ContrastToDivide/C2D

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Contrast to Divide: Self-Supervised Pre-Training for Learning with Noisy Labels

https://github.com/Fchaubard/gradient_agreement_filtering

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Beyond Gradient Averaging in Parallel Optimization: Improved Robustness through Gradient Agreement Filtering

https://github.com/FilippoMB/Bidirectional-Deep-Echo-State-Network

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Bidirectional deep-readout echo state networks

https://github.com/FilippoMB/Bidirectional-Deep-reservoir-Echo-State-Network

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Bidirectional deep-readout echo state networks

https://github.com/Glaciohound/Multi-Turn-Instruct

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Can Language Models Follow Multiple Turns of Entangled Instructions?

https://github.com/HKUNLP/DS-1000

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DS-1000: A Natural and Reliable Benchmark for Data Science Code Generation

https://github.com/HarrieO/2021WWW-GENSPEC

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Robust Generalization and Safe Query-Specialization in Counterfactual Learning to Rank

https://github.com/IBM/span-selection-pretraining

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Span Selection Pre-training for Question Answering

https://github.com/MarkWuNLP/SemanticMask

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Semantic Mask for Transformer based End-to-End Speech Recognition

https://github.com/Maryeon/InvMM

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An Inversion-based Measure of Memorization for Diffusion Models

https://github.com/MediaBrain-SJTU/BCL

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Contrastive Learning with Boosted Memorization

https://github.com/Morefre/Understanding-Generalizability-of-Diffusion-Models-Requires-Rethinking-the-Hidden-Gaussian-Structure

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Understanding Generalizability of Diffusion Models Requires Rethinking the Hidden Gaussian Structure

https://github.com/NAVER-INTEL-Co-Lab/gaudi-dash

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DASH: Warm-Starting Neural Network Training in Stationary Settings without Loss of Plasticity

https://github.com/NUST-Machine-Intelligence-Laboratory/CRSSC

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Salvage Reusable Samples from Noisy Data for Robust Learning

https://github.com/NeurAI-Lab/NCT

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Noisy Concurrent Training for Efficient Learning under Label Noise

https://github.com/OswaldHe/HMT-pytorch

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HMT: Hierarchical Memory Transformer for Long Context Language Processing

https://github.com/PJLab-ADG/driveLikeAHuman

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Drive Like a Human: Rethinking Autonomous Driving with Large Language Models

https://github.com/PanBikang/PromptFolio

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Federated Learning from Vision-Language Foundation Models: Theoretical Analysis and Method

https://github.com/Pehlevan-Group/icl-asymptotic

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Asymptotic theory of in-context learning by linear attention

https://github.com/Raman1121/diffusion_memorization

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The Devil is in the Prompts: De-Identification Traces Enhance Memorization Risks in Synthetic Chest X-Ray Generation

https://github.com/SAP-samples/security-research-dp-hierarchical-text

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On the privacy-utility trade-off in differentially private hierarchical text classification

https://github.com/SPOC-group/counting-attention

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Counting in Small Transformers: The Delicate Interplay between Attention and Feed-Forward Layers

https://github.com/Shikib/schema_attention_model

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Schema-Guided Paradigm for Zero-Shot Dialog

https://github.com/Tom556/OrthogonalTransformerProbing

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Introducing Orthogonal Constraint in Structural Probes

https://github.com/X-F-Cui/Fictitious_Fact_Watermarks

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Robust Data Watermarking in Language Models by Injecting Fictitious Knowledge

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