Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives | Paper Citation Record

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This paper cites A Survey on Data Selection for Language Models.

Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives A Survey on Data Selection for Language Models

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Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives Efficient Online Data Mixing For Language Model Pre-Training

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Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives Unresolved cited work

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This paper cites Optimizing Pre-Training Data Mixtures with Mixtures of Data Expert Models.

Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives Optimizing Pre-Training Data Mixtures with Mixtures of Data Expert Models

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Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives Aioli: A Unified Optimization Framework for Language Model Data Mixing

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Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives Skill-it! A Data-Driven Skills Framework for Understanding and Training Language Models

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Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives Scaling Instruction-Finetuned Language Models

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Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives Training GANs with Optimism

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Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives GLaM: Efficient Scaling of Language Models with Mixture-of-Experts

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This paper cites Forward and Reverse Gradient-Based Hyperparameter Optimization.

Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives Forward and Reverse Gradient-Based Hyperparameter Optimization

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This paper cites Language models scale reliably with over-training and on downstream tasks.

Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives Language models scale reliably with over-training and on downstream tasks

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Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives The Pile: An 800GB Dataset of Diverse Text for Language Modeling

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Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives BiMix: A Bivariate Data Mixing Law for Language Model Pretraining

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Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives Scaling Expert Language Models with Unsupervised Domain Discovery

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Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives Training Compute-Optimal Large Language Models

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Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives Adaptive Data Optimization: Dynamic Sample Selection with Scaling Laws

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Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives Unresolved cited work

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Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives Scaling Laws for Neural Language Models

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Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives A Fully First-Order Method for Stochastic Bilevel Optimization

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Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives MFTCoder: Boosting Code LLMs with Multitask Fine-Tuning

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Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives FAMO: Fast Adaptive Multitask Optimization

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Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives Unresolved cited work

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Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives RegMix: Data Mixture as Regression for Language Model Pre-training

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Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives Optimizing Millions of Hyperparameters by Implicit Differentiation

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Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives Velocitune: A Velocity-based Dynamic Domain Reweighting Method for Continual Pre-training

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Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives OpenELM: An Efficient Language Model Family with Open Training and Inference Framework

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Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives Hashimoto, and Percy Liang

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Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives LISA: Layerwise Importance Sampling for Memory-Efficient Large Language Model Fine-Tuning

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Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives ScaleBiO: Scalable Bilevel Optimization for LLM Data Reweighting

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Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives D-CPT Law: Domain-specific Continual Pre-Training Scaling Law for Large Language Models

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Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization

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Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives SlimPajama-DC: Understanding Data Combinations for LLM Training

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Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives The Vizier Gaussian Process Bandit Algorithm

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Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives Oliphant, Matt Haberland, Tyler Reddy, David Cournapeau, Evgeni Burovski, Pearu Peterson, Warren Weckesser, Jonathan Bright, Stéfan J

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Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives Finetuned Language Models Are Zero-Shot Learners

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Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives Sheared LLaMA: Accelerating Language Model Pre-training via Structured Pruning

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Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives DoReMi: Optimizing Data Mixtures Speeds Up Language Model Pretraining

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Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives A Unified Perspective on Multi-Domain and Multi-Task Learning

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Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives Data Mixing Laws: Optimizing Data Mixtures by Predicting Language Modeling Performance

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Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives Gradient Surgery for Multi-Task Learning

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Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives A Single-Loop Smoothed Gradient Descent-Ascent Algorithm for Nonconvex-Concave Min-Max Problems

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Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives An Introduction to Bi-level Optimization: Foundations and Applications in Signal Processing and Machine Learning

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Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives online" 'onlinestring :=

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Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives write newline

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