{"total":22,"rows":[{"id":"2606.18206","title":"Fixed-Point Reasoners: Stable and Adaptive Deep Looped Transformers","created":"2026-06-16","cited_by_count":28,"area":null},{"id":"2604.21254","title":"Hyperloop Transformers","created":"2026-04-23","cited_by_count":12,"area":null},{"id":"2609.11801","title":"Thinking with Looped Flows","created":"2026-09-10","cited_by_count":9,"area":null},{"id":"2605.20670","title":"LT2: Linear-Time Looped Transformers","created":"2026-05-20","cited_by_count":7,"area":null},{"id":"2607.15456","title":"Looped Latent Attention: Cross-Loop KV Compression for Looped Transformers","created":"2026-07-16","cited_by_count":7,"area":null},{"id":"2607.20594","title":"When Does Recurrence Become an Algorithm? Convergence Selection in Weight-Tied Looped Transformers","created":"2026-07-22","cited_by_count":6,"area":null},{"id":"2609.01924","title":"Looped Transformers under the Jacobian Lens: Does the Global Workspace Survive Recurrence?","created":"2026-09-01","cited_by_count":6,"area":null},{"id":"2606.24898","title":"Dense Supervision Is Not Enough: The Readout Blind Spot in Looped Language Models","created":"2026-06-12","cited_by_count":5,"area":null},{"id":"2607.18584","title":"On the Diverse Dynamical Behaviors Arising in Deep Linear Transformers","created":"2026-07-20","cited_by_count":3,"area":null},{"id":"2608.24136","title":"Steering Recurrent Reasoners at Inference Time with Readout Feedback","created":"2026-08-25","cited_by_count":1,"area":null},{"id":"2605.06322","title":"SMolLM: Small Language Models Learn Small Molecular Grammar","created":"2026-05-07","cited_by_count":0,"area":null},{"id":"2605.16048","title":"Reshape and Recur: Improving SSMs with Input Reshaping and Depth Recurrence","created":"2026-05-15","cited_by_count":0,"area":null},{"id":"2605.17811","title":"One Model, Two Roles: Emergent Specialization in a Shared Recurrent Transformer","created":"2026-05-18","cited_by_count":0,"area":null},{"id":"2608.16085","title":"Behaviour Is an Incomplete Measure of Reasoning Development: Cross-surface pre-arrival accessibility and the limits of developmental inference in a recurrent-depth reasoner","created":"2026-08-17","cited_by_count":0,"area":null},{"id":"2609.10123","title":"If It's Not Buggy, Don't Fix It: On the Dynamics of Iterative Bug-fixing with LLMs","created":"2026-09-09","cited_by_count":0,"area":null},{"id":"2609.36108","title":"LoopICL: Looping a single transformer block to solve tabular tasks","created":"2026-09-28","cited_by_count":0,"area":null},{"id":"2609.36585","title":"Transformers Stop Thinking Too Early, and a Tiny LoRA Fixes It","created":"2026-09-29","cited_by_count":0,"area":null},{"id":"2609.36636","title":"What Makes Recurrence Effective in Looped Language Models?","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},{"id":"2609.39892","title":"Shared Weights, Selected Computations: How Looped Transformers Route What Each Loop Does","created":"2026-09-30","cited_by_count":0,"area":null},{"id":"2610.14998","title":"Recurrent In-Context Learning for Tabular Foundation Models","created":"2026-10-10","cited_by_count":0,"area":null},{"id":"2610.18174","title":"Looped Reasoning Finishes Earlier Than You Think","created":"2026-10-13","cited_by_count":0,"area":null}],"next_cursor":null}