{"total":234,"rows":[{"id":"2502.14802","title":"From RAG to Memory: Non-Parametric Continual Learning for Large Language Models","created":"2025-02-20","cited_by_count":231,"area":"rag"},{"id":"2409.00088","title":"On-Device Language Models: A Comprehensive Review","created":"2024-08-26","cited_by_count":104,"area":null},{"id":"2510.18874","title":"Retaining by Doing: The Role of On-Policy Data in Mitigating Forgetting","created":"2025-10-21","cited_by_count":94,"area":null},{"id":"2501.07278","title":"Lifelong Learning of Large Language Model based Agents: A Roadmap","created":"2025-01-13","cited_by_count":83,"area":"agents"},{"id":"2406.06391","title":"Towards Lifelong Learning of Large Language Models: A Survey","created":"2024-06-10","cited_by_count":64,"area":null},{"id":"2510.17281","title":"MemoryBench: A Benchmark for Memory and Continual Learning in LLM Systems","created":"2025-10-20","cited_by_count":61,"area":null},{"id":"2604.20087","title":"SkillLearnBench: Benchmarking Continual Learning Methods for Agent Skill Generation on Real-World Tasks","created":"2026-04-22","cited_by_count":55,"area":"agents"},{"id":"2406.11675","title":"BLoB: Bayesian Low-Rank Adaptation by Backpropagation for Large Language Models","created":"2024-06-17","cited_by_count":50,"area":null},{"id":"2602.01869","title":"Skill-Pro: Learning Reusable Skills from Experience via Non-Parametric PPO for LLM Agents","created":"2026-02-02","cited_by_count":47,"area":"agents"},{"id":"2405.18653","title":"Recent Advances of Foundation Language Models-based Continual Learning: A Survey","created":"2024-05-28","cited_by_count":46,"area":null},{"id":"2602.15902","title":"Doc-to-LoRA: Learning to Instantly Internalize Contexts","created":"2026-02-13","cited_by_count":43,"area":"lr"},{"id":"2509.06216","title":"Agentic Software Engineering: Foundational Pillars and a Research Roadmap","created":"2025-09-07","cited_by_count":41,"area":"agents"},{"id":"2509.13310","title":"Scaling Agents via Continual Pre-training","created":"2025-09-16","cited_by_count":40,"area":"agents"},{"id":"2410.04509","title":"ErrorRadar: Benchmarking Complex Mathematical Reasoning of Multimodal Large Language Models Via Error Detection","created":"2024-10-06","cited_by_count":37,"area":"lr"},{"id":"2407.08699","title":"Mitigating Catastrophic Forgetting in Language Transfer via Model Merging","created":"2024-07-11","cited_by_count":36,"area":null},{"id":"2502.02871","title":"Position: Multimodal Large Language Models Can Significantly Advance Scientific Reasoning","created":"2025-02-05","cited_by_count":33,"area":"lr"},{"id":"2505.02486","title":"SEFE: Superficial and Essential Forgetting Eliminator for Multimodal Continual Instruction Tuning","created":"2025-05-05","cited_by_count":33,"area":"mllm"},{"id":"2502.02421","title":"Activation-Informed Merging of Large Language Models","created":"2025-02-04","cited_by_count":30,"area":null},{"id":"2510.13900","title":"Narrow Finetuning Leaves Clearly Readable Traces in Activation Differences","created":"2025-10-14","cited_by_count":28,"area":null},{"id":"2505.11737","title":"TokUR: Token-Level Uncertainty Estimation for Large Language Model Reasoning","created":"2025-05-16","cited_by_count":24,"area":"lr"},{"id":"2406.17245","title":"Unlocking Continual Learning Abilities in Language Models","created":"2024-06-25","cited_by_count":23,"area":null},{"id":"2501.07391","title":"Enhancing Retrieval-Augmented Generation: A Study of Best Practices","created":"2025-01-13","cited_by_count":23,"area":"rag"},{"id":"2506.05453","title":"MLLM-CL: Continual Learning for Multimodal Large Language Models","created":"2025-06-05","cited_by_count":23,"area":"mllm"},{"id":"2411.02564","title":"Continual LLaVA: Continual Instruction Tuning in Large Vision-Language Models","created":"2024-11-04","cited_by_count":22,"area":"mllm"},{"id":"2405.03988","title":"LEARN: Knowledge Adaptation from Large Language Model to Recommendation for Practical Industrial Application","created":"2024-05-07","cited_by_count":21,"area":null},{"id":"2509.11575","title":"A Survey of Reasoning and Agentic Systems in Time Series with Large Language Models","created":"2025-09-15","cited_by_count":21,"area":"lr"},{"id":"2409.18991","title":"Surveying the MLLM Landscape: A Meta-Review of Current Surveys","created":"2024-09-17","cited_by_count":20,"area":"mllm"},{"id":"2503.17979","title":"Trade-offs in Large Reasoning Models: An Empirical Analysis of Deliberative and Adaptive Reasoning over Foundational Capabilities","created":"2025-03-23","cited_by_count":20,"area":"lr"},{"id":"2407.16695","title":"Stress-Testing Long-Context Language Models with Lifelong ICL and Task Haystack","created":"2024-07-23","cited_by_count":19,"area":null},{"id":"2411.11072","title":"Multilingual Large Language Models: A Systematic Survey","created":"2024-11-17","cited_by_count":18,"area":null},{"id":"2506.03320","title":"The Future of Continual Learning in the Era of Foundation Models: Three Key Directions","created":"2025-06-03","cited_by_count":17,"area":null},{"id":"2603.11653","title":"Simple Recipe Works: Vision-Language-Action Models are Natural Continual Learners with Reinforcement Learning","created":"2026-03-12","cited_by_count":17,"area":"vla"},{"id":"2601.02151","title":"Entropy-Adaptive Fine-Tuning: Resolving Confident Conflicts to Mitigate Forgetting","created":"2026-01-05","cited_by_count":16,"area":null},{"id":"2407.08583","title":"The Synergy between Data and Multi-Modal Large Language Models: A Survey from Co-Development Perspective","created":"2024-07-11","cited_by_count":15,"area":"mllm"},{"id":"2406.20030","title":"LEMoE: Advanced Mixture of Experts Adaptor for Lifelong Model Editing of Large Language Models","created":"2024-06-28","cited_by_count":14,"area":"moe"},{"id":"2407.20999","title":"MoFO: Momentum-Filtered Optimizer for Mitigating Forgetting in LLM Fine-Tuning","created":"2024-07-30","cited_by_count":14,"area":null},{"id":"2502.07760","title":"Scalable Fingerprinting of Large Language Models","created":"2025-02-11","cited_by_count":14,"area":null},{"id":"2508.01908","title":"Revisiting Replay and Gradient Alignment for Continual Pre-Training of Large Language Models","created":"2025-08-03","cited_by_count":14,"area":null},{"id":"2605.29442","title":"How Coding Agents Fail Their Users: A Large-Scale Analysis of Developer-Agent Misalignment in 20,574 Real-World Sessions","created":"2026-05-28","cited_by_count":14,"area":"agents"},{"id":"2502.11740","title":"Mitigating Visual Knowledge Forgetting in MLLM Instruction-tuning via Modality-decoupled Gradient Descent","created":"2025-02-17","cited_by_count":13,"area":"lr"},{"id":"2505.15424","title":"Gated Integration of Low-Rank Adaptation for Continual Learning of Large Language Models","created":"2025-05-21","cited_by_count":13,"area":null},{"id":"2411.16905","title":"Boundless Socratic Learning with Language Games","created":"2024-11-25","cited_by_count":12,"area":null},{"id":"2506.13045","title":"Continual Learning for Generative AI: From LLMs to MLLMs and Beyond","created":"2025-06-16","cited_by_count":12,"area":null},{"id":"2505.20903","title":"Towards Objective Fine-tuning: How LLMs' Prior Knowledge Causes Potential Poor Calibration?","created":"2025-05-27","cited_by_count":11,"area":null},{"id":"2507.02503","title":"Continual Gradient Low-Rank Projection Fine-Tuning for LLMs","created":"2025-07-03","cited_by_count":11,"area":null},{"id":"2407.04581","title":"Leveraging Large Language Models for Integrated Satellite-Aerial-Terrestrial Networks: Recent Advances and Future Directions","created":"2024-07-05","cited_by_count":10,"area":null},{"id":"2504.14520","title":"Meta-Thinking in LLMs via Multi-Agent Reinforcement Learning: A Survey","created":"2025-04-20","cited_by_count":10,"area":"lr"},{"id":"2509.21710","title":"Think-on-Graph 3.0: Efficient and Adaptive LLM Reasoning on Heterogeneous Graphs via Multi-Agent Dual-Evolving Context Retrieval","created":"2025-09-26","cited_by_count":10,"area":"lr"},{"id":"2405.19010","title":"Evaluating the External and Parametric Knowledge Fusion of Large Language Models","created":"2024-05-29","cited_by_count":9,"area":null},{"id":"2501.01045","title":"ZeroFlow: Overcoming Catastrophic Forgetting is Easier than You Think","created":"2025-01-02","cited_by_count":9,"area":null},{"id":"2505.14679","title":"UltraEdit: Training-, Subject-, and Memory-Free Lifelong Editing in Language Models","created":"2025-05-20","cited_by_count":9,"area":null},{"id":"2509.03934","title":"SelfAug: Mitigating Catastrophic Forgetting in Retrieval-Augmented Generation via Distribution Self-Alignment","created":"2025-09-04","cited_by_count":9,"area":"rag"},{"id":"2603.16177","title":"The Finetuner's Fallacy: When to Pretrain with Your Finetuning Data","created":"2026-03-17","cited_by_count":9,"area":"wm"},{"id":"2406.14026","title":"Demystifying Language Model Forgetting with Low-rank Example Associations","created":"2024-06-20","cited_by_count":8,"area":null},{"id":"2410.00645","title":"LoRanPAC: Low-rank Random Features and Pre-trained Models for Bridging Theory and Practice in Continual Learning","created":"2024-10-01","cited_by_count":8,"area":null},{"id":"2410.09218","title":"Continual Learning with Neuromorphic Computing: Foundations, Methods, and Emerging Applications","created":"2024-10-11","cited_by_count":8,"area":null},{"id":"2411.07175","title":"Continual Memorization of Factoids in Language Models","created":"2024-11-11","cited_by_count":8,"area":null},{"id":"2412.01377","title":"Adapting Large Language Models to Log Analysis with Interpretable Domain Knowledge","created":"2024-12-02","cited_by_count":8,"area":null},{"id":"2412.10893","title":"BgGPT 1.0: Extending English-centric LLMs to other languages","created":"2024-12-14","cited_by_count":8,"area":null},{"id":"2502.12598","title":"Bring Your Own Knowledge: A Survey of Methods for LLM Knowledge Expansion","created":"2025-02-18","cited_by_count":8,"area":null},{"id":"2504.09522","title":"How new data permeates LLM knowledge and how to dilute it","created":"2025-04-13","cited_by_count":8,"area":null},{"id":"2504.13938","title":"Never Start from Scratch: Expediting On-Device LLM Personalization via Explainable Model Selection","created":"2025-04-15","cited_by_count":8,"area":null},{"id":"2603.18272","title":"Retrieval-Augmented LLM Agents: Learning to Learn from Experience","created":"2026-03-18","cited_by_count":7,"area":"rag"},{"id":"2605.17830","title":"Remembering More, Risking More: Longitudinal Safety Risks in Memory-Equipped LLM Agents","created":"2026-05-18","cited_by_count":7,"area":"agents"},{"id":"2606.07612","title":"Position: Anthropomorphic Misalignment Research Needs Stronger Evidence","created":"2026-05-29","cited_by_count":7,"area":null},{"id":"2404.18311","title":"Towards Incremental Learning in Large Language Models: A Critical Review","created":"2024-04-28","cited_by_count":6,"area":null},{"id":"2410.13944","title":"Boosting LLM Translation Skills without General Ability Loss via Rationale Distillation","created":"2024-10-17","cited_by_count":6,"area":null},{"id":"2412.07393","title":"CMT: A Memory Compression Method for Continual Knowledge Learning of Large Language Models","created":"2024-12-10","cited_by_count":6,"area":null},{"id":"2504.04569","title":"KnowsLM: A framework for evaluation of small language models for knowledge augmentation and humanised conversations","created":"2025-04-06","cited_by_count":6,"area":null},{"id":"2603.12658","title":"Beyond Static Models: An Evolving Framework for Continual Learning in Large Language Models across Training Stages","created":"2026-03-13","cited_by_count":6,"area":null},{"id":"2605.26820","title":"Can Vision-Language-Action Models Learn from Real-World Data Continually without Forgetting?","created":"2026-05-26","cited_by_count":6,"area":"vla"},{"id":"2406.04584","title":"CLoG: Benchmarking Continual Learning of Image Generation Models","created":"2024-06-07","cited_by_count":5,"area":null},{"id":"2406.11234","title":"MiniConGTS: A Near Ultimate Minimalist Contrastive Grid Tagging Scheme for Aspect Sentiment Triplet Extraction","created":"2024-06-17","cited_by_count":5,"area":null},{"id":"2505.07796","title":"Learning Dynamics in Continual Pre-Training for Large Language Models","created":"2025-05-12","cited_by_count":5,"area":null},{"id":"2507.08309","title":"Improving MLLM's Document Image Machine Translation via Synchronously Self-reviewing Its OCR Proficiency","created":"2025-07-11","cited_by_count":5,"area":"mllm"},{"id":"2507.15640","title":"Data Mixing Agent: Learning to Re-weight Domains for Continual Pre-training","created":"2025-07-21","cited_by_count":5,"area":"agents"},{"id":"2602.15823","title":"CrispEdit: Low-Curvature Projections for Scalable Non-Destructive LLM Editing","created":"2026-02-17","cited_by_count":5,"area":"alignment"},{"id":"2604.14144","title":"SpatialEvo: Self-Evolving Spatial Intelligence via Deterministic Geometric Environments","created":"2026-04-15","cited_by_count":5,"area":"lr"},{"id":"2605.05676","title":"Decomposing the Basic Abilities of Large Language Models: Mitigating Cross-Task Interference in Multi-Task Instruct-Tuning","created":"2026-05-07","cited_by_count":5,"area":null},{"id":"2407.14562","title":"Thought-Like-Pro: Enhancing Reasoning of Large Language Models through Self-Driven Prolog-based Chain-of-Thought","created":"2024-07-18","cited_by_count":4,"area":"lr"},{"id":"2503.18247","title":"AfroXLMR-Social: Adapting Pre-trained Language Models for African Languages Social Media Text","created":"2025-03-24","cited_by_count":4,"area":null},{"id":"2503.22006","title":"Enhancing Domain-Specific Encoder Models with LLM-Generated Data: How to Leverage Ontologies, and How to Do Without Them","created":"2025-03-27","cited_by_count":4,"area":"synth"},{"id":"2504.06664","title":"SEE: Continual Fine-tuning with Sequential Ensemble of Experts","created":"2025-04-09","cited_by_count":4,"area":null},{"id":"2504.08949","title":"Large Language Model Empowered Recommendation Meets All-domain Continual Pre-Training","created":"2025-04-11","cited_by_count":4,"area":null},{"id":"2505.05946","title":"Full-Parameter Continual Pretraining of Gemma2: Insights into Fluency and Domain Knowledge","created":"2025-05-09","cited_by_count":4,"area":null},{"id":"2505.23422","title":"From Knowledge to Noise: CTIM-Rover and the Pitfalls of Episodic Memory in Software Engineering Agents","created":"2025-05-29","cited_by_count":4,"area":"agents"},{"id":"2506.13492","title":"GeoSDF: Plane Geometry Diagram Synthesis via Signed Distance Field","created":"2025-06-16","cited_by_count":4,"area":null},{"id":"2508.04676","title":"GeRe: Towards Efficient Anti-Forgetting in Continual Learning of LLM via General Samples Replay","created":"2025-08-06","cited_by_count":4,"area":null},{"id":"2509.04304","title":"Facts Fade Fast: Evaluating Memorization of Outdated Medical Knowledge in Large Language Models","created":"2025-09-04","cited_by_count":4,"area":null},{"id":"2601.00756","title":"Memory Bank Compression for Continual Adaptation of Large Language Models","created":"2026-01-02","cited_by_count":4,"area":null},{"id":"2601.09974","title":"SPRInG: Continual LLM Personalization via Selective Parametric Adaptation and Retrieval-Interpolated Generation","created":"2026-01-15","cited_by_count":4,"area":null},{"id":"2603.09892","title":"MSSR: Memory-Aware Adaptive Replay for Continual LLM Fine-Tuning","created":"2026-03-10","cited_by_count":4,"area":null},{"id":"2604.05096","title":"RAG or Learning? Understanding the Limits of LLM Adaptation under Continuous Knowledge Drift in the Real World","created":"2026-04-06","cited_by_count":4,"area":null},{"id":"2604.17215","title":"Continual Safety Alignment via Gradient-Based Sample Selection","created":"2026-04-19","cited_by_count":4,"area":"alignment"},{"id":"2605.10770","title":"DynaMiCS: Fine-tuning LLMs with Performance Constraints using Dynamic Mixtures","created":"2026-05-11","cited_by_count":4,"area":null},{"id":"2605.30169","title":"Dissociative Identity: Language Model Agents Lack Grounding for Reputation Mechanisms","created":"2026-05-28","cited_by_count":4,"area":"agents"},{"id":"2606.19911","title":"Multi-Agent Transactive Memory","created":"2026-06-18","cited_by_count":4,"area":"agents"},{"id":"2410.10181","title":"Scalable Multi-Domain Adaptation of Language Models using Modular Experts","created":"2024-10-14","cited_by_count":3,"area":null},{"id":"2503.10705","title":"Enhanced Continual Learning of Vision-Language Models with Model Fusion","created":"2025-03-12","cited_by_count":3,"area":"mllm"},{"id":"2504.13603","title":"Continual Pre-Training is (not) What You Need in Domain Adaption","created":"2025-04-18","cited_by_count":3,"area":null}],"next_cursor":"100"}