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inductive bia

336 papers

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representation learning (39) neural network (28) convolutional neural network (20) graph neural network (20) transfer learning (17) language model (16) large language model (16) vision transformer (15) transformer architecture (14) attention mechanism (12)

Papers

A theoretical design of concept sets: improving the predictability of concept bottleneck models NeurIPS 2024 Boosting Sample Efficiency and Generalization in Multi-agent Reinforcement Learning via Equivariance NeurIPS 2024 Changing the Training Data Distribution to Reduce Simplicity Bias Improves In-distribution Generalization NeurIPS 2024 CoELM: Construction-Enhanced Language Modeling ACL 2024 Confronting Reward Overoptimization for Diffusion Models: A Perspective of Inductive and Primacy Biases ICML 2024 Context-Aware Testing: A New Paradigm for Model Testing with Large Language Models NeurIPS 2024 Convolution Meets LoRA: Parameter Efficient Finetuning for Segment Anything Model ICLR 2024 Defining Expertise: Applications to Treatment Effect Estimation ICLR 2024 Diffusion Model with Cross Attention as an Inductive Bias for Disentanglement NeurIPS 2024 Do LLMs Think Fast and Slow? A Causal Study on Sentiment Analysis EMNLP 2024 Empowering Graph Invariance Learning with Deep Spurious Infomax ICML 2024 Enhancing Graph Transformers with Hierarchical Distance Structural Encoding NeurIPS 2024 Expressivity and Generalization: Fragment-Biases for Molecular GNNs ICML 2024 Few-shot Learner Parameterization by Diffusion Time-steps CVPR 2024 G-Adapter: Towards Structure-Aware Parameter-Efficient Transfer Learning for Graph Transformer Networks AAAI 2024 Generalization in diffusion models arises from geometry-adaptive harmonic representations ICLR 2024 Gradformer: Graph Transformer with Exponential Decay IJCAI 2024 Graphcode: Learning from multiparameter persistent homology using graph neural networks NeurIPS 2024 Identifying Spurious Biases Early in Training through the Lens of Simplicity Bias AISTATS 2024 In-Context Learning through the Bayesian Prism ICLR 2024 Inductive biases of multi-task learning and finetuning: multiple regimes of feature reuse NeurIPS 2024 Intrinsic Gaussian Vector Fields on Manifolds AISTATS 2024 Label-Focused Inductive Bias over Latent Object Features in Visual Classification ICLR 2024 Learning Representations for Hierarchies with Minimal Support NeurIPS 2024 Learning symmetries via weight-sharing with doubly stochastic tensors NeurIPS 2024