{"total":14,"rows":[{"id":"2505.03005","title":"RADLADS: Rapid Attention Distillation to Linear Attention Decoders at Scale","created":"2025-05-05","cited_by_count":24,"area":null},{"id":"2510.22603","title":"Mitigating Attention Sinks and Massive Activations in Audio-Visual Speech Recognition with LLMs","created":"2025-10-26","cited_by_count":11,"area":null},{"id":"2603.11487","title":"Attention Sinks Are Provably Necessary in Softmax Transformers: Evidence from Trigger-Conditional Tasks","created":"2026-03-12","cited_by_count":11,"area":null},{"id":"2604.10098","title":"Attention Sink in Transformers: A Survey on Utilization, Interpretation, and Mitigation","created":"2026-04-11","cited_by_count":11,"area":null},{"id":"2508.03616","title":"Hidden Dynamics of Massive Activations in Transformer Training","created":"2025-08-05","cited_by_count":10,"area":null},{"id":"2601.12145","title":"Threshold Differential Attention for Sink-Free, Ultra-Sparse, and Non-Dispersive Language Modeling","created":"2026-01-17","cited_by_count":5,"area":null},{"id":"2603.17771","title":"Attention Sinks Induce Gradient Sinks: Massive Activations as Gradient Regulators in Transformers","created":"2026-03-18","cited_by_count":3,"area":null},{"id":"2605.08504","title":"A Single Layer to Explain Them All:Understanding Massive Activations in Large Language Models","created":"2026-05-08","cited_by_count":2,"area":null},{"id":"2605.17887","title":"Attention Sinks and Outliers in Attention Residuals","created":"2026-05-18","cited_by_count":2,"area":null},{"id":"2605.04421","title":"FLUID: Continuous-Time Hyperconnected Sparse Transformer for Sink-Free Learning","created":"2026-05-06","cited_by_count":1,"area":null},{"id":"2608.21174","title":"From Attention Masks to Inert Zero-Vector Tokens: OAttention and O-Closure for Token Dynamics","created":"2026-08-21","cited_by_count":0,"area":null},{"id":"2609.08574","title":"Do New Attention Mechanisms Actually Fix Attention Sinks at Million-Token Context?","created":"2026-09-08","cited_by_count":0,"area":null},{"id":"2609.22005","title":"Abstention and Noise Filtering: Two Missing Primitives of Softmax Attention","created":"2026-09-18","cited_by_count":0,"area":null},{"id":"2610.05488","title":"Underscoring the Problem: Why Softpick Fails at Initialization","created":"2026-10-04","cited_by_count":0,"area":null}],"next_cursor":null}