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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/YerevaNN/incontext_spurious

공식 코드

In-context Learning in Presence of Spurious Correlations

https://github.com/ZJU-DAILY/SGDL

공식 코드

Self-Guided Learning to Denoise for Robust Recommendation

https://github.com/ZhangXiao96/RethinkSpectralBias

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Rethink the Connections among Generalization, Memorization and the Spectral Bias of DNNs

https://github.com/adihaviv/idiomem

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Understanding Transformer Memorization Recall Through Idioms

https://github.com/ahans30/goldfish-loss

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Be like a Goldfish, Don't Memorize! Mitigating Memorization in Generative LLMs

https://github.com/aigc-apps/perteval

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PertEval: Unveiling Real Knowledge Capacity of LLMs with Knowledge-Invariant Perturbations

https://github.com/aikyamlab/llm-memorization

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Analyzing Memorization in Large Language Models through the Lens of Model Attribution

https://github.com/aise-tudelft/nlbse23_reading_list

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The (ab)use of Open Source Code to Train Large Language Models

https://github.com/akariasai/evidentiality_qa

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Evidentiality-guided Generation for Knowledge-Intensive NLP Tasks

https://github.com/aksh555/deciphering_cot

공식 코드

Deciphering the Factors Influencing the Efficacy of Chain-of-Thought: Probability, Memorization, and Noisy Reasoning

https://github.com/alan-turing-institute/memorization

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On Memorization in Probabilistic Deep Generative Models

https://github.com/albertsun1/gpt3-pii-attacks

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Does fine-tuning GPT-3 with the OpenAI API leak personally-identifiable information?

https://github.com/alextmallen/adaptive-retrieval

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When Not to Trust Language Models: Investigating Effectiveness of Parametric and Non-Parametric Memories

https://github.com/alimamarankgroup/HPMN

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Lifelong Sequential Modeling with Personalized Memorization for User Response Prediction

https://github.com/alirezamshi/bias-compressedmt

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What Do Compressed Multilingual Machine Translation Models Forget?

https://github.com/allegro/allenoise

공식 코드

AlleNoise: large-scale text classification benchmark dataset with real-world label noise

https://github.com/alymostafa/instruction_based_attack

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Alpaca against Vicuna: Using LLMs to Uncover Memorization of LLMs

https://github.com/amodaresi/memllm

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MemLLM: Finetuning LLMs to Use An Explicit Read-Write Memory

https://github.com/andreamad8/QDREN

공식 코드

Question Dependent Recurrent Entity Network for Question Answering

https://github.com/anonymousNeurIPS2021submission5254/SupplementaryMaterial

공식 코드

Muddling Label Regularization: Deep Learning for Tabular Datasets

https://github.com/anthonysicilia/humbel

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HumBEL: A Human-in-the-Loop Approach for Evaluating Demographic Factors of Language Models in Human-Machine Conversations

https://github.com/antonFJohansson/slope_and_generalization

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Slope and generalization properties of neural networks

https://github.com/anubhav1997/mitigating_memorization

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Classifier-Free Guidance inside the Attraction Basin May Cause Memorization

https://github.com/armanbolatov/long_tail

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Long-Tail Theory under Gaussian Mixtures

https://github.com/awslabs/aws-cv-unique-information

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On information captured by neural networks: connections with memorization and generalization

https://github.com/baekrok/DASH-Direction-Aware-SHrinking

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

https://github.com/bamman-group/gpt4-books

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Speak, Memory: An Archaeology of Books Known to ChatGPT/GPT-4

https://github.com/baptistar/DiffusionModelDynamics

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Memorization and Regularization in Generative Diffusion Models

https://github.com/beanham/fragments-to-facts

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Fragments to Facts: Partial-Information Fragment Inference from LLMs

https://github.com/belindal/taskbench500

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Quantifying Adaptability in Pre-trained Language Models with 500 Tasks

https://github.com/bhanML/Co-teaching

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Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels

https://github.com/bigchem/synthesis

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State-of-the-Art Augmented NLP Transformer models for direct and single-step retrosynthesis

https://github.com/biu-nlp/sprp-acl2018

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Split and Rephrase: Better Evaluation and a Stronger Baseline

https://github.com/blbadger/learning-generality

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Why Deep Learning Generalizes

https://github.com/boschresearch/one-shot-synthesis

공식 코드

Generating Novel Scene Compositions from Single Images and Videos

https://github.com/boyazeng/weight_memorization

공식 코드

Generative Modeling of Weights: Generalization or Memorization?

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