{"total":63,"rows":[{"id":"2507.10524","title":"Mixture-of-Recursions: Learning Dynamic Recursive Depths for Adaptive Token-Level Computation","created":"2025-07-14","cited_by_count":133,"area":null},{"id":"2410.20672","title":"Relaxed Recursive Transformers: Effective Parameter Sharing with Layer-wise LoRA","created":"2024-10-28","cited_by_count":78,"area":null},{"id":"2111.05193","title":"A Survey on Green Deep Learning","created":"2021-11-08","cited_by_count":52,"area":null},{"id":"2312.16903","title":"Spike No More: Stabilizing the Pre-training of Large Language Models","created":"2023-12-28","cited_by_count":52,"area":null},{"id":"2310.12072","title":"SPEED: Speculative Pipelined Execution for Efficient Decoding","created":"2023-10-18","cited_by_count":47,"area":null},{"id":"2202.07105","title":"A Survey on Model Compression and Acceleration for Pretrained Language Models","created":"2022-02-15","cited_by_count":45,"area":null},{"id":"2410.01405","title":"On Expressive Power of Looped Transformers: Theoretical Analysis and Enhancement via Timestep Encoding","created":"2024-10-02","cited_by_count":36,"area":null},{"id":"2410.03765","title":"Basis Sharing: Cross-Layer Parameter Sharing for Large Language Model Compression","created":"2024-10-02","cited_by_count":35,"area":null},{"id":"2105.14802","title":"On Compositional Generalization of Neural Machine Translation","created":"2021-05-31","cited_by_count":34,"area":null},{"id":"2202.07959","title":"EdgeFormer: A Parameter-Efficient Transformer for On-Device Seq2seq Generation","created":"2022-02-16","cited_by_count":21,"area":null},{"id":"2110.10470","title":"Interpreting Deep Learning Models in Natural Language Processing: A Review","created":"2021-10-20","cited_by_count":19,"area":null},{"id":"2402.16902","title":"PRoLoRA: Partial Rotation Empowers More Parameter-Efficient LoRA","created":"2024-02-24","cited_by_count":16,"area":null},{"id":"2309.01826","title":"One Wide Feedforward is All You Need","created":"2023-09-04","cited_by_count":15,"area":null},{"id":"2401.15347","title":"A Comprehensive Survey of Compression Algorithms for Language Models","created":"2024-01-27","cited_by_count":15,"area":null},{"id":"2303.01980","title":"Towards energy-efficient Deep Learning: An overview of energy-efficient approaches along the Deep Learning Lifecycle","created":"2023-02-05","cited_by_count":14,"area":null},{"id":"2406.12246","title":"TroL: Traversal of Layers for Large Language and Vision Models","created":"2024-06-18","cited_by_count":14,"area":null},{"id":"2406.03051","title":"Adapter-X: A Novel General Parameter-Efficient Fine-Tuning Framework for Vision","created":"2024-06-05","cited_by_count":13,"area":null},{"id":"2602.11698","title":"SpiralFormer: Looped Transformers Can Learn Hierarchical Dependencies via Multi-Resolution Recursion","created":"2026-02-12","cited_by_count":12,"area":null},{"id":"2209.14915","title":"Spiking Neural Networks for event-based action recognition: A new task to understand their advantage","created":"2022-09-29","cited_by_count":9,"area":null},{"id":"2404.16897","title":"Exploring Learngene via Stage-wise Weight Sharing for Initializing Variable-sized Models","created":"2024-04-25","cited_by_count":9,"area":null},{"id":"2406.17296","title":"BlockLLM: Memory-Efficient Adaptation of LLMs by Selecting and Optimizing the Right Coordinate Blocks","created":"2024-06-25","cited_by_count":9,"area":null},{"id":"2203.15773","title":"Streaming parallel transducer beam search with fast-slow cascaded encoders","created":"2022-03-29","cited_by_count":8,"area":null},{"id":"2509.25622","title":"Layer-wise dynamic rank for compressing large language models","created":"2025-09-30","cited_by_count":8,"area":null},{"id":"2510.07739","title":"MeSH: Memory-as-State-Highways for Recursive Transformers","created":"2025-10-09","cited_by_count":8,"area":null},{"id":"2311.00447","title":"On the Opportunities of Green Computing: A Survey","created":"2023-11-01","cited_by_count":7,"area":null},{"id":"2602.16490","title":"From Growing to Looping: A Unified View of Iterative Computation in LLMs","created":"2026-02-18","cited_by_count":7,"area":null},{"id":"2605.20670","title":"LT2: Linear-Time Looped Transformers","created":"2026-05-20","cited_by_count":7,"area":null},{"id":"2407.01320","title":"Increasing Model Capacity for Free: A Simple Strategy for Parameter Efficient Fine-tuning","created":"2024-07-01","cited_by_count":6,"area":null},{"id":"2502.13181","title":"RingFormer: Rethinking Recurrent Transformer with Adaptive Level Signals","created":"2025-02-18","cited_by_count":6,"area":null},{"id":"2508.04581","title":"Share Your Attention: Transformer Weight Sharing via Matrix-based Dictionary Learning","created":"2025-08-06","cited_by_count":5,"area":null},{"id":"2402.11819","title":"Head-wise Shareable Attention for Large Language Models","created":"2024-02-19","cited_by_count":4,"area":null},{"id":"2501.14713","title":"FlexiGPT: Pruning and Extending Large Language Models with Low-Rank Weight Sharing","created":"2025-01-24","cited_by_count":4,"area":null},{"id":"2506.18233","title":"Beyond Parameters: Exploring Virtual Logic Depth for Scaling Laws","created":"2025-06-23","cited_by_count":4,"area":null},{"id":"2306.09380","title":"Understanding Parameter Sharing in Transformers","created":"2023-06-15","cited_by_count":3,"area":null},{"id":"2411.09816","title":"Learning Fine-grained Parameter Sharing via Sparse Tensor Decomposition","created":"2024-11-14","cited_by_count":3,"area":null},{"id":"2309.07197","title":"Mitigating Adversarial Attacks in Federated Learning with Trusted Execution Environments","created":"2023-09-13","cited_by_count":2,"area":null},{"id":"2310.13315","title":"Zero-Shot Sharpness-Aware Quantization for Pre-trained Language Models","created":"2023-10-20","cited_by_count":2,"area":null},{"id":"2405.20892","title":"MALT: Multi-scale Action Learning Transformer for Online Action Detection","created":"2024-05-31","cited_by_count":2,"area":null},{"id":"2501.17332","title":"Compact Neural TTS Voices for Accessibility","created":"2025-01-28","cited_by_count":2,"area":null},{"id":"2505.24009","title":"Diversity of Transformer Layers: One Aspect of Parameter Scaling Laws","created":"2025-05-29","cited_by_count":2,"area":null},{"id":"2601.22708","title":"A Unified Study of LoRA Variants: Taxonomy, Review, Codebase, and Empirical Evaluation","created":"2026-01-30","cited_by_count":2,"area":null},{"id":"2110.03427","title":"Is Attention always needed? A Case Study on Language Identification from Speech","created":"2021-10-05","cited_by_count":1,"area":null},{"id":"2207.10237","title":"SPIN: An Empirical Evaluation on Sharing Parameters of Isotropic Networks","created":"2022-07-21","cited_by_count":1,"area":null},{"id":"2210.12905","title":"Visualizing the Obvious: A Concreteness-based Ensemble Model for Noun Property Prediction","created":"2022-10-24","cited_by_count":1,"area":null},{"id":"2306.04235","title":"MobileNMT: Enabling Translation in 15MB and 30ms","created":"2023-06-07","cited_by_count":1,"area":null},{"id":"2308.04373","title":"Pelta: Shielding Transformers to Mitigate Evasion Attacks in Federated Learning","created":"2023-08-08","cited_by_count":1,"area":null},{"id":"2409.18695","title":"KALE-LM-Chem: Vision and Practice Toward an AI Brain for Chemistry","created":"2024-09-27","cited_by_count":1,"area":null},{"id":"2410.03364","title":"Unified Error Correction Code Transformer with Low Complexity","created":"2024-10-04","cited_by_count":1,"area":null},{"id":"2501.06126","title":"Merging Feed-Forward Sublayers for Compressed Transformers","created":"2025-01-10","cited_by_count":1,"area":null},{"id":"2603.03318","title":"Quantum-Inspired Self-Attention in a Large Language Model","created":"2026-02-09","cited_by_count":1,"area":null},{"id":"2607.27656","title":"Looped Transformers with Source-Centered State Evolution","created":"2026-07-30","cited_by_count":1,"area":null},{"id":"2304.00557","title":"Semi-supervised Neural Machine Translation with Consistency Regularization for Low-Resource Languages","created":"2023-04-02","cited_by_count":0,"area":null},{"id":"2307.08013","title":"Revisiting Implicit Models: Sparsity Trade-offs Capability in Weight-tied Model for Vision Tasks","created":"2023-07-16","cited_by_count":0,"area":null},{"id":"2310.12818","title":"Boosting Inference Efficiency: Unleashing the Power of Parameter-Shared Pre-trained Language Models","created":"2023-10-19","cited_by_count":0,"area":null},{"id":"2401.03314","title":"Enhancing Context Through Contrast","created":"2024-01-06","cited_by_count":0,"area":null},{"id":"2504.03713","title":"RLDBF: Enhancing LLMs Via Reinforcement Learning With DataBase FeedBack","created":"2025-03-28","cited_by_count":0,"area":null},{"id":"2504.07108","title":"OKRA: an Explainable, Heterogeneous, Multi-Stakeholder Job Recommender System","created":"2025-03-17","cited_by_count":0,"area":null},{"id":"2504.08982","title":"Adaptive Additive Parameter Updates of Vision Transformers for Few-Shot Continual Learning","created":"2025-04-11","cited_by_count":0,"area":null},{"id":"2506.00486","title":"It Takes a Good Model to Train a Good Model: Generalized Gaussian Priors for Optimized LLMs","created":"2025-05-31","cited_by_count":0,"area":null},{"id":"2606.11860","title":"RePAIR: Predictive Self-Supervised Representation Learning in Chess","created":"2026-06-10","cited_by_count":0,"area":null},{"id":"2606.20737","title":"Repeated Shared Access Enables Grokking, but Edit Propagation Depends on an Addressable Memory","created":"2026-06-17","cited_by_count":0,"area":null},{"id":"2607.17843","title":"Mobius Learning: Cyclic Depth Folding in Transformers","created":"2026-07-20","cited_by_count":0,"area":null},{"id":"2608.22117","title":"TANGO: Treating Tokens as Operators","created":"2026-08-22","cited_by_count":0,"area":null}],"next_cursor":null}