{"total":43,"rows":[{"id":"2106.15110","title":"Time-Aware Language Models as Temporal Knowledge Bases","created":"2021-06-29","cited_by_count":296,"area":null},{"id":"2102.01951","title":"Mind the Gap: Assessing Temporal Generalization in Neural Language Models","created":"2021-02-03","cited_by_count":230,"area":null},{"id":"2205.11388","title":"StreamingQA: A Benchmark for Adaptation to New Knowledge over Time in Question Answering Models","created":"2022-05-23","cited_by_count":126,"area":null},{"id":"2305.18466","title":"Test-Time Training on Nearest Neighbors for Large Language Models","created":"2023-05-29","cited_by_count":88,"area":null},{"id":"2102.02557","title":"Adaptive Semiparametric Language Models","created":"2021-02-04","cited_by_count":83,"area":null},{"id":"2512.23675","title":"End-to-End Test-Time Training for Long Context","created":"2025-12-29","cited_by_count":62,"area":null},{"id":"2506.05233","title":"MesaNet: Sequence Modeling by Locally Optimal Test-Time Training","created":"2025-06-05","cited_by_count":47,"area":null},{"id":"2101.00234","title":"Subformer: Exploring Weight Sharing for Parameter Efficiency in Generative Transformers","created":"2021-01-01","cited_by_count":43,"area":null},{"id":"2202.05780","title":"A Modern Self-Referential Weight Matrix That Learns to Modify Itself","created":"2022-02-11","cited_by_count":41,"area":null},{"id":"2102.12459","title":"When Attention Meets Fast Recurrence: Training Language Models with Reduced Compute","created":"2021-02-24","cited_by_count":34,"area":null},{"id":"2509.14786","title":"Pre-training under infinite compute","created":"2025-09-18","cited_by_count":29,"area":null},{"id":"2101.09048","title":"Selfish Sparse RNN Training","created":"2021-01-22","cited_by_count":26,"area":null},{"id":"2206.06178","title":"Efficient recurrent architectures through activity sparsity and sparse back-propagation through time","created":"2022-06-13","cited_by_count":26,"area":null},{"id":"2201.09680","title":"Relational Memory Augmented Language Models","created":"2022-01-24","cited_by_count":24,"area":null},{"id":"2212.02475","title":"Meta-Learning Fast Weight Language Models","created":"2022-12-05","cited_by_count":21,"area":null},{"id":"2305.19044","title":"Exploring the Promise and Limits of Real-Time Recurrent Learning","created":"2023-05-30","cited_by_count":19,"area":null},{"id":"2406.14230","title":"Raising the Bar: Investigating the Values of Large Language Models via Generative Evolving Testing","created":"2024-06-20","cited_by_count":17,"area":null},{"id":"2205.10787","title":"A Dirichlet Process Mixture of Robust Task Models for Scalable Lifelong Reinforcement Learning","created":"2022-05-22","cited_by_count":15,"area":null},{"id":"2302.10879","title":"$k$NN-Adapter: Efficient Domain Adaptation for Black-Box Language Models","created":"2023-02-21","cited_by_count":14,"area":null},{"id":"2309.11197","title":"The Languini Kitchen: Enabling Language Modelling Research at Different Scales of Compute","created":"2023-09-20","cited_by_count":10,"area":null},{"id":"2403.01518","title":"Revisiting Dynamic Evaluation: Online Adaptation for Large Language Models","created":"2024-03-03","cited_by_count":7,"area":null},{"id":"2210.08321","title":"Construction Repetition Reduces Information Rate in Dialogue","created":"2022-10-15","cited_by_count":5,"area":null},{"id":"2212.11791","title":"Training Integer-Only Deep Recurrent Neural Networks","created":"2022-12-22","cited_by_count":5,"area":null},{"id":"2509.24510","title":"Specialization after Generalization: Towards Understanding Test-Time Training in Foundation Models","created":"2025-09-29","cited_by_count":5,"area":null},{"id":"2407.21414","title":"Towards interfacing large language models with ASR systems using confidence measures and prompting","created":"2024-07-31","cited_by_count":4,"area":null},{"id":"2605.05838","title":"MDN: Parallelizing Stepwise Momentum for Delta Linear Attention","created":"2026-05-07","cited_by_count":4,"area":null},{"id":"2109.09828","title":"iRNN: Integer-only Recurrent Neural Network","created":"2021-09-20","cited_by_count":3,"area":null},{"id":"2112.08653","title":"Reconsidering the Past: Optimizing Hidden States in Language Models","created":"2021-12-16","cited_by_count":3,"area":null},{"id":"2604.07350","title":"Fast Spatial Memory with Elastic Test-Time Training","created":"2026-04-08","cited_by_count":3,"area":null},{"id":"2608.07110","title":"Modular TTT: Rethinking Test-Time Training as Composable Modules","created":"2026-08-07","cited_by_count":3,"area":null},{"id":"2105.14214","title":"Predictive Representation Learning for Language Modeling","created":"2021-05-29","cited_by_count":1,"area":null},{"id":"2501.09166","title":"Attention is All You Need Until You Need Retention","created":"2025-01-15","cited_by_count":1,"area":null},{"id":"2507.06313","title":"ETT: Expanding the Long Context Understanding Capability of LLMs at Test-Time","created":"2025-07-08","cited_by_count":1,"area":null},{"id":"2607.00368","title":"Beyond Perplexity: A Behavioral Evaluation Framework for Deployment-Memory Claims in LLM Test-Time Training","created":"2026-07-01","cited_by_count":1,"area":null},{"id":"2101.00674","title":"Recoding latent sentence representations -- Dynamic gradient-based activation modification in RNNs","created":"2021-01-03","cited_by_count":0,"area":null},{"id":"2104.08742","title":"Go Forth and Prosper: Language Modeling with Ancient Textual History","created":"2021-04-18","cited_by_count":0,"area":null},{"id":"2112.11776","title":"The Importance of the Current Input in Sequence Modeling","created":"2021-12-22","cited_by_count":0,"area":null},{"id":"2211.01848","title":"Circling Back to Recurrent Models of Language","created":"2022-11-03","cited_by_count":0,"area":null},{"id":"2302.08481","title":"Local-to-Global Information Communication for Real-Time Semantic Segmentation Network Search","created":"2023-02-16","cited_by_count":0,"area":null},{"id":"2511.16691","title":"Reproducibility Report: Test-Time Training on Nearest Neighbors for Large Language Models","created":"2025-11-16","cited_by_count":0,"area":null},{"id":"2604.13546","title":"Learning Inference Concurrency in DynamicGate MLP Structural and Mathematical Justification","created":"2026-04-15","cited_by_count":0,"area":null},{"id":"2609.34174","title":"GradLev: Token-Parallel Test-Time Training Via Costate Prediction","created":"2026-09-28","cited_by_count":0,"area":null},{"id":"2610.05076","title":"Self-Generated Feedback Destabilizes Test-Time Training: A Causal Decomposition of Long-Horizon Adaptation","created":"2026-10-04","cited_by_count":0,"area":null}],"next_cursor":null}