{"total":27,"rows":[{"id":"2103.10697","title":"ConViT: Improving Vision Transformers with Soft Convolutional Inductive Biases","created":"2021-03-19","cited_by_count":484,"area":null},{"id":"2309.13638","title":"Embers of Autoregression: Understanding Large Language Models Through the Problem They are Trained to Solve","created":"2023-09-24","cited_by_count":178,"area":null},{"id":"2107.07002","title":"The Benchmark Lottery","created":"2021-07-14","cited_by_count":136,"area":null},{"id":"2111.06091","title":"A Survey of Visual Transformers","created":"2021-11-11","cited_by_count":117,"area":null},{"id":"2207.10551","title":"Scaling Laws vs Model Architectures: How does Inductive Bias Influence Scaling?","created":"2022-07-21","cited_by_count":103,"area":null},{"id":"2306.00946","title":"Exposing Attention Glitches with Flip-Flop Language Modeling","created":"2023-06-01","cited_by_count":75,"area":null},{"id":"2402.02769","title":"Learning from Teaching Regularization: Generalizable Correlations Should be Easy to Imitate","created":"2024-02-05","cited_by_count":47,"area":null},{"id":"2305.14701","title":"Modeling rapid language learning by distilling Bayesian priors into artificial neural networks","created":"2023-05-24","cited_by_count":42,"area":null},{"id":"2104.01655","title":"Efficient Transformers in Reinforcement Learning using Actor-Learner Distillation","created":"2021-04-04","cited_by_count":35,"area":null},{"id":"2301.13195","title":"Adaptive Computation with Elastic Input Sequence","created":"2023-01-30","cited_by_count":22,"area":null},{"id":"2112.02805","title":"Forward Compatible Training for Large-Scale Embedding Retrieval Systems","created":"2021-12-06","cited_by_count":19,"area":null},{"id":"2304.05659","title":"RIFormer: Keep Your Vision Backbone Effective While Removing Token Mixer","created":"2023-04-12","cited_by_count":13,"area":null},{"id":"2601.21725","title":"Procedural Pretraining: Warming Up Language Models with Abstract Data","created":"2026-01-29","cited_by_count":10,"area":null},{"id":"2507.06445","title":"Can Interpretation Predict Behavior on Unseen Data?","created":"2025-07-08","cited_by_count":8,"area":null},{"id":"2310.08866","title":"Adaptivity and Modularity for Efficient Generalization Over Task Complexity","created":"2023-10-13","cited_by_count":7,"area":null},{"id":"2502.20237","title":"Teasing Apart Architecture and Initial Weights as Sources of Inductive Bias in Neural Networks","created":"2025-02-27","cited_by_count":5,"area":null},{"id":"2404.12210","title":"An Experimental Study on Exploring Strong Lightweight Vision Transformers via Masked Image Modeling Pre-Training","created":"2024-04-18","cited_by_count":4,"area":null},{"id":"2405.12954","title":"A Method on Searching Better Activation Functions","created":"2024-05-19","cited_by_count":4,"area":null},{"id":"2604.19609","title":"Volume Transformer: Revisiting Vanilla Transformers for 3D Scene Understanding","created":"2026-04-21","cited_by_count":4,"area":null},{"id":"2310.11282","title":"ChapGTP, ILLC's Attempt at Raising a BabyLM: Improving Data Efficiency by Automatic Task Formation","created":"2023-10-17","cited_by_count":3,"area":null},{"id":"2603.15590","title":"Effective Distillation to Hybrid xLSTM Architectures","created":"2026-03-16","cited_by_count":3,"area":null},{"id":"2206.11078","title":"Traffic-Twitter Transformer: A Nature Language Processing-joined Framework For Network-wide Traffic Forecasting","created":"2022-06-19","cited_by_count":2,"area":null},{"id":"2506.08978","title":"Propositional Logic for Probing Generalization in Neural Networks","created":"2025-06-10","cited_by_count":1,"area":null},{"id":"2211.13852","title":"Adaptive Attention Link-based Regularization for Vision Transformers","created":"2022-11-25","cited_by_count":0,"area":null},{"id":"2312.17648","title":"Bridging Modality Gap for Visual Grounding with Effecitve Cross-modal Distillation","created":"2023-12-29","cited_by_count":0,"area":null},{"id":"2401.00532","title":"On the Necessity of Metalearning: Learning Suitable Parameterizations for Learning Processes","created":"2023-12-31","cited_by_count":0,"area":null},{"id":"2602.06300","title":"Accelerating Vision Transformers on Brain Processing Unit","created":"2026-02-06","cited_by_count":0,"area":null}],"next_cursor":null}