{"total":19,"rows":[{"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":"2604.12946","title":"Parcae: Scaling Laws For Stable Looped Language Models","created":"2026-04-14","cited_by_count":55,"area":null},{"id":"2505.13898","title":"Do Language Models Use Their Depth Efficiently?","created":"2025-05-20","cited_by_count":50,"area":null},{"id":"2505.20674","title":"PonderLM: Pretraining Language Models to Ponder in Continuous Space","created":"2025-05-27","cited_by_count":44,"area":null},{"id":"2604.21254","title":"Hyperloop Transformers","created":"2026-04-23","cited_by_count":12,"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":"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":"2512.08819","title":"Do Depth-Grown Models Overcome the Curse of Depth? An In-Depth Analysis","created":"2025-12-09","cited_by_count":6,"area":null},{"id":"2502.11646","title":"Hyper-SET: Designing Transformers via Hyperspherical Energy Minimization","created":"2025-02-17","cited_by_count":2,"area":null},{"id":"2609.12531","title":"Temporal Recurrence Favors Fewer Layers","created":"2026-09-11","cited_by_count":1,"area":null},{"id":"2609.31360","title":"Programs-of-Layers in LLMs through the Lens of Cortical Areas","created":"2026-09-25","cited_by_count":1,"area":null},{"id":"2510.13860","title":"ShishuLM : Achieving Optimal and Efficient Parameterization with Low Attention Transformer Models","created":"2025-10-13","cited_by_count":0,"area":null},{"id":"2603.29057","title":"LA-Sign: Looped Transformers with Geometry-aware Alignment for Skeleton-based Sign Language Recognition","created":"2026-03-30","cited_by_count":0,"area":null},{"id":"2606.16112","title":"Scaling Adaptive Depth with Norm-Agnostic Residual Networks","created":"2026-06-15","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":"2608.22117","title":"TANGO: Treating Tokens as Operators","created":"2026-08-22","cited_by_count":0,"area":null},{"id":"2609.37379","title":"Looped Transformers as Optimizers","created":"2026-09-29","cited_by_count":0,"area":null},{"id":"2609.38426","title":"LoopVL: Recurrent Visual Intelligence","created":"2026-09-29","cited_by_count":0,"area":null}],"next_cursor":null}