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BIG-Bench Extra Hard ACL 2025 EVOLvE: Evaluating and Optimizing LLMs For In-Context Exploration ICML 2025 Reward-Guided Prompt Evolving in Reinforcement Learning for LLMs ICML 2025 SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training ICML 2025 Towards Robust Mathematical Reasoning EMNLP 2025 FLIQS: One-Shot Mixed-Precision Floating-Point and Integer Quantization Search AutoML 2024 Large Language Models as Optimizers ICLR 2024 Long-form factuality in large language models NeurIPS 2024 SELF-DISCOVER: Large Language Models Self-Compose Reasoning Structures NeurIPS 2024 Take a Step Back: Evoking Reasoning via Abstraction in Large Language Models ICLR 2024 Brainformers: Trading Simplicity for Efficiency ICML 2023 DoReMi: Optimizing Data Mixtures Speeds Up Language Model Pretraining NeurIPS 2023 Least-to-Most Prompting Enables Complex Reasoning in Large Language Models ICLR 2023 Self-Consistency Improves Chain of Thought Reasoning in Language Models ICLR 2023 Symbolic Discovery of Optimization Algorithms NeurIPS 2023 The Flan Collection: Designing Data and Methods for Effective Instruction Tuning ICML 2023 Chain-of-Thought Prompting Elicits Reasoning in Large Language Models NeurIPS 2022 Finetuned Language Models are Zero-Shot Learners ICLR 2022 Mixture-of-Experts with Expert Choice Routing NeurIPS 2022 TabNAS: Rejection Sampling for Neural Architecture Search on Tabular Datasets NeurIPS 2022 CoAtNet: Marrying Convolution and Attention for All Data Sizes NeurIPS 2021 Evolving Reinforcement Learning Algorithms ICLR 2021 Pay Attention to MLPs NeurIPS 2021 Searching for Efficient Transformers for Language Modeling NeurIPS 2021 Evolving Normalization-Activation Layers NeurIPS 2020 Funnel-Transformer: Filtering out Sequential Redundancy for Efficient Language Processing NeurIPS 2020 PyGlove: Symbolic Programming for Automated Machine Learning NeurIPS 2020 RandAugment: Practical Automated Data Augmentation with a Reduced Search Space NeurIPS 2020 Rethinking Pre-training and Self-training NeurIPS 2020 Unsupervised Data Augmentation for Consistency Training NeurIPS 2020 CondConv: Conditionally Parameterized Convolutions for Efficient Inference NeurIPS 2019 GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism NeurIPS 2019 High Fidelity Video Prediction with Large Stochastic Recurrent Neural Networks NeurIPS 2019 Mixtape: Breaking the Softmax Bottleneck Efficiently NeurIPS 2019 Saccader: Improving Accuracy of Hard Attention Models for Vision NeurIPS 2019 XLNet: Generalized Autoregressive Pretraining for Language Understanding NeurIPS 2019 DropBlock: A regularization method for convolutional networks NeurIPS 2018 Memory Augmented Policy Optimization for Program Synthesis and Semantic Parsing NeurIPS 2018 An Online Sequence-to-Sequence Model Using Partial Conditioning NeurIPS 2016 Semi-supervised Sequence Learning NeurIPS 2015 Sequence to Sequence Learning with Neural Networks NeurIPS 2014 Large Scale Distributed Deep Networks NeurIPS 2012 ICA with Reconstruction Cost for Efficient Overcomplete Feature Learning NeurIPS 2011 Tiled convolutional neural networks NeurIPS 2010 Measuring Invariances in Deep Networks NeurIPS 2009 Tighter Bounds for Structured Estimation NeurIPS 2008 Bundle Methods for Machine Learning NeurIPS 2007 COFI RANK - Maximum Margin Matrix Factorization for Collaborative Ranking NeurIPS 2007 Learning to Rank with Nonsmooth Cost Functions NeurIPS 2006