data efficiency

CodeM: Less Data Yields More Versatility via Ability Matrix ACL 2024 CoT3DRef: Chain-of-Thoughts Data-Efficient 3D Visual Grounding ICLR 2024 Data-efficient, explainable and safe box manipulation: Illustrating the advantages of physical priors in model-predictive control L4DC 2024 DeepSpeed Data Efficiency: Improving Deep Learning Model Quality and Training Efficiency via Efficient Data Sampling and Routing AAAI 2024 DEFT-UCS: Data Efficient Fine-Tuning for Pre-Trained Language Models via Unsupervised Core-Set Selection for Text-Editing EMNLP 2024 Efficiency for Free: Ideal Data Are Transportable Representations NeurIPS 2024 How Hard is this Test Set? NLI Characterization by Exploiting Training Dynamics EMNLP 2024 In2Core: Leveraging Influence Functions for Coreset Selection in Instruction Finetuning of Large Language Models EMNLP 2024 Is Child-Directed Speech Effective Training Data for Language Models? EMNLP 2024 Open the Black Box: Step-based Policy Updates for Temporally-Correlated Episodic Reinforcement Learning ICLR 2024 Parameter-Efficient Transfer Learning for End-to-end Speech Translation COLING 2024 Position: Will we run out of data? Limits of LLM scaling based on human-generated data ICML 2024 Relational Learning in Pre-Trained Models: A Theory from Hypergraph Recovery Perspective ICML 2024 Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling ACL 2024 Replay across Experiments: A Natural Extension of Off-Policy RL ICLR 2024 Residual Dropout: A Simple Approach to Improve Transformer’s Data Efficiency COLING 2024 SmallToLarge (S2L): Scalable Data Selection for Fine-tuning Large Language Models by Summarizing Training Trajectories of Small Models NeurIPS 2024 Toward Data Efficient Model Merging between Different Datasets without Performance Degradation ACML 2024 Towards Better Vision-Inspired Vision-Language Models CVPR 2024 Trust the Model Where It Trusts Itself - Model-Based Actor-Critic with Uncertainty-Aware Rollout Adaption ICML 2024 Uncertainty for Active Learning on Graphs ICML 2024 Understanding when Dynamics-Invariant Data Augmentations Benefit Model-free Reinforcement Learning Updates ICLR 2024 Unlocking the Potential of Model Merging for Low-Resource Languages EMNLP 2024 Using Curriculum Masking Based on Child Language Development to Train a Large Language Model with Limited Training Data CoNLL 2024 When can transformers reason with abstract symbols? ICLR 2024