[
  {
    "index": 1,
    "category": "01-surveys-foundations",
    "slug": "01-comprehensive-survey",
    "title": "Continual Learning of Large Language Models: A Comprehensive Survey",
    "source": "https://arxiv.org/abs/2404.16789",
    "pdf": "https://arxiv.org/pdf/2404.16789"
  },
  {
    "index": 2,
    "category": "01-surveys-foundations",
    "slug": "02-llm-continual-learning-survey",
    "title": "Continual Learning for Large Language Models: A Survey",
    "source": "https://arxiv.org/abs/2402.01364",
    "pdf": "https://arxiv.org/pdf/2402.01364"
  },
  {
    "index": 3,
    "category": "01-surveys-foundations",
    "slug": "03-emnlp-2025-tutorial",
    "title": "Continual Learning of Large Language Models",
    "source": "https://aclanthology.org/2025.emnlp-tutorials.7/",
    "pdf": "https://aclanthology.org/2025.emnlp-tutorials.7.pdf"
  },
  {
    "index": 4,
    "category": "01-surveys-foundations",
    "slug": "04-lifelong-learning-llm-agents-roadmap",
    "title": "Lifelong Learning of Large Language Model Based Agents: A Roadmap",
    "source": "https://arxiv.org/abs/2501.07278",
    "pdf": "https://arxiv.org/pdf/2501.07278"
  },
  {
    "index": 5,
    "category": "01-surveys-foundations",
    "slug": "05-continual-learning-llms-methods-challenges",
    "title": "Continual Learning in Large Language Models: Methods, Challenges, and Opportunities",
    "source": "https://arxiv.org/abs/2603.12658",
    "pdf": "https://arxiv.org/pdf/2603.12658"
  },
  {
    "index": 6,
    "category": "01-surveys-foundations",
    "slug": "06-catastrophic-forgetting-review",
    "title": "Continual Learning and Catastrophic Forgetting",
    "source": "https://arxiv.org/abs/2403.05175",
    "pdf": "https://arxiv.org/pdf/2403.05175"
  },
  {
    "index": 7,
    "category": "01-surveys-foundations",
    "slug": "07-ewc",
    "title": "Overcoming Catastrophic Forgetting in Neural Networks",
    "source": "https://doi.org/10.1073/pnas.1611835114",
    "pdf": "https://arxiv.org/pdf/1612.00796"
  },
  {
    "index": 8,
    "category": "01-surveys-foundations",
    "slug": "08-gem",
    "title": "Gradient Episodic Memory for Continual Learning",
    "source": "https://papers.nips.cc/paper/7225-gradient-episodic-memory-for-continual-learning",
    "pdf": "https://papers.nips.cc/paper_files/paper/2017/file/f87522788a2be2d171666752f97ddebb-Paper.pdf"
  },
  {
    "index": 9,
    "category": "02-continual-pretraining",
    "slug": "09-lifelong-pretraining",
    "title": "Lifelong Pretraining: Continually Adapting Language Models to Emerging Corpora",
    "source": "https://arxiv.org/abs/2110.08534",
    "pdf": "https://arxiv.org/pdf/2110.08534"
  },
  {
    "index": 10,
    "category": "02-continual-pretraining",
    "slug": "10-elle",
    "title": "ELLE: Efficient Lifelong Pre-training for Emerging Data",
    "source": "https://aclanthology.org/2022.findings-acl.220/",
    "pdf": "https://aclanthology.org/2022.findings-acl.220.pdf"
  },
  {
    "index": 11,
    "category": "02-continual-pretraining",
    "slug": "11-rewarm-your-model",
    "title": "How to (Re)warm Your Model? Reusing Optimizer State for Continual Pre-Training",
    "source": "https://arxiv.org/abs/2308.04014",
    "pdf": "https://arxiv.org/pdf/2308.04014"
  },
  {
    "index": 12,
    "category": "02-continual-pretraining",
    "slug": "12-investigating-continual-pretraining",
    "title": "Investigating Continual Pretraining in Large Language Models",
    "source": "https://arxiv.org/abs/2402.17400",
    "pdf": "https://arxiv.org/pdf/2402.17400"
  },
  {
    "index": 13,
    "category": "02-continual-pretraining",
    "slug": "13-tic-lm",
    "title": "TiC-LM: A Multi-Year Benchmark for Continual Pretraining of Language Models",
    "source": "https://aclanthology.org/2025.acl-long.1551/",
    "pdf": "https://aclanthology.org/2025.acl-long.1551.pdf"
  },
  {
    "index": 14,
    "category": "02-continual-pretraining",
    "slug": "14-stability-gap",
    "title": "Continual Pre-training of Language Models: How to Re-warm Your Model?",
    "source": "https://aclanthology.org/2025.acl-long.1578/",
    "pdf": "https://aclanthology.org/2025.acl-long.1578.pdf"
  },
  {
    "index": 15,
    "category": "02-continual-pretraining",
    "slug": "15-sparse-memory-finetuning",
    "title": "Continual Learning via Sparse Memory Finetuning",
    "source": "https://arxiv.org/abs/2510.15103",
    "pdf": "https://arxiv.org/pdf/2510.15103"
  },
  {
    "index": 16,
    "category": "02-continual-pretraining",
    "slug": "16-scale",
    "title": "SCALE: Scalable Continual Learning via Model Expansion",
    "source": "https://aclanthology.org/2026.findings-acl.2037/",
    "pdf": "https://aclanthology.org/2026.findings-acl.2037.pdf"
  },
  {
    "index": 17,
    "category": "03-continual-finetuning",
    "slug": "17-trace",
    "title": "TRACE: A Comprehensive Benchmark for Continual Learning in Large Language Models",
    "source": "https://arxiv.org/abs/2310.06762",
    "pdf": "https://arxiv.org/pdf/2310.06762"
  },
  {
    "index": 18,
    "category": "03-continual-finetuning",
    "slug": "18-o-lora",
    "title": "Orthogonal Subspace Learning for Language Model Continual Learning",
    "source": "https://aclanthology.org/2023.findings-emnlp.715/",
    "pdf": "https://aclanthology.org/2023.findings-emnlp.715.pdf"
  },
  {
    "index": 19,
    "category": "03-continual-finetuning",
    "slug": "19-conpet",
    "title": "ConPET: Continual Parameter-Efficient Tuning for Large Language Models",
    "source": "https://arxiv.org/abs/2309.14763",
    "pdf": "https://arxiv.org/pdf/2309.14763"
  },
  {
    "index": 20,
    "category": "03-continual-finetuning",
    "slug": "20-inscl",
    "title": "InsCL: A Data-efficient Continual Learning Paradigm for Fine-tuning Large Language Models with Instructions",
    "source": "https://aclanthology.org/2024.naacl-long.37/",
    "pdf": "https://aclanthology.org/2024.naacl-long.37.pdf"
  },
  {
    "index": 21,
    "category": "03-continual-finetuning",
    "slug": "21-sapt",
    "title": "SAPT: A Shared Attention Framework for Continual Learning of Large Language Models",
    "source": "https://aclanthology.org/2024.acl-long.625/",
    "pdf": "https://aclanthology.org/2024.acl-long.625.pdf"
  },
  {
    "index": 22,
    "category": "03-continual-finetuning",
    "slug": "22-revisiting-catastrophic-forgetting",
    "title": "Revisiting Catastrophic Forgetting in Large Language Model Tuning",
    "source": "https://aclanthology.org/2024.findings-emnlp.249/",
    "pdf": "https://aclanthology.org/2024.findings-emnlp.249.pdf"
  },
  {
    "index": 23,
    "category": "03-continual-finetuning",
    "slug": "23-online-cl-llms",
    "title": "Online Continual Learning of Large Language Models",
    "source": "https://openreview.net/forum?id=6udKBHc0Mr",
    "pdf": "https://raw.githubusercontent.com/mlresearch/v267/main/assets/cheng25j/cheng25j.pdf"
  },
  {
    "index": 24,
    "category": "03-continual-finetuning",
    "slug": "24-aso-lora",
    "title": "ASO-LoRA: Adaptive Subspace Orthogonal LoRA for Continual Learning",
    "source": "https://aclanthology.org/2026.acl-long.842/",
    "pdf": "https://aclanthology.org/2026.acl-long.842.pdf"
  },
  {
    "index": 25,
    "category": "04-model-editing-memory",
    "slug": "25-wise",
    "title": "WISE: Rethinking the Knowledge Memory for Lifelong Model Editing of Large Language Models",
    "source": "https://openreview.net/forum?id=VJMYOfJVC2",
    "pdf": "https://arxiv.org/pdf/2405.14768"
  },
  {
    "index": 26,
    "category": "04-model-editing-memory",
    "slug": "26-memoir",
    "title": "MEMOIR: Lifelong Model Editing with Residual Memory",
    "source": "https://openreview.net/forum?id=t94tALZvZE",
    "pdf": "https://arxiv.org/pdf/2506.07899"
  },
  {
    "index": 27,
    "category": "05-agents-new-paradigms",
    "slug": "27-lifelong-agent-bench",
    "title": "LifelongAgentBench: Evaluating LLM Agents as Lifelong Learners",
    "source": "https://arxiv.org/abs/2505.11942",
    "pdf": "https://arxiv.org/pdf/2505.11942"
  },
  {
    "index": 28,
    "category": "05-agents-new-paradigms",
    "slug": "28-cl-bench",
    "title": "Continual Learning Bench: Benchmarking Continual Learning for LLM Agents",
    "source": "https://arxiv.org/abs/2606.05661",
    "pdf": "https://arxiv.org/pdf/2606.05661"
  },
  {
    "index": 29,
    "category": "05-agents-new-paradigms",
    "slug": "29-skilllearnbench",
    "title": "SkillLearnBench: Evaluating Continual Skill Learning in Language Agents",
    "source": "https://arxiv.org/abs/2604.20087",
    "pdf": "https://arxiv.org/pdf/2604.20087"
  },
  {
    "index": 30,
    "category": "05-agents-new-paradigms",
    "slug": "30-lifeskill",
    "title": "LifeSkill: Lifelong Skill Learning for Language Agents",
    "source": "https://arxiv.org/abs/2606.04815",
    "pdf": "https://arxiv.org/pdf/2606.04815"
  },
  {
    "index": 31,
    "category": "05-agents-new-paradigms",
    "slug": "31-nested-learning",
    "title": "Nested Learning: The Illusion of Deep Learning Architecture",
    "source": "https://abehrouz.github.io/nestedlearning/",
    "pdf": "https://abehrouz.github.io/files/NL.pdf"
  },
  {
    "index": 32,
    "category": "05-agents-new-paradigms",
    "slug": "32-seal",
    "title": "Self-Adapting Language Models",
    "source": "https://arxiv.org/abs/2506.10943",
    "pdf": "https://arxiv.org/pdf/2506.10943"
  },
  {
    "index": 33,
    "category": "05-agents-new-paradigms",
    "slug": "33-learning-fast-and-slow",
    "title": "Learning, Fast and Slow: Towards LLMs That Adapt Continually",
    "source": "https://arxiv.org/abs/2605.12484",
    "pdf": "https://arxiv.org/pdf/2605.12484"
  },
  {
    "index": 34,
    "category": "05-agents-new-paradigms",
    "slug": "34-knowledge-circuits",
    "title": "Knowledge Circuits in Pretrained Transformers",
    "source": "https://arxiv.org/abs/2502.11196",
    "pdf": "https://arxiv.org/pdf/2502.11196"
  },
  {
    "index": 35,
    "category": "06-persistent-adaptive-intelligence",
    "slug": "35-fast-weights",
    "title": "Using Fast Weights to Attend to the Recent Past",
    "source": "https://arxiv.org/abs/1610.06258",
    "pdf": "https://arxiv.org/pdf/1610.06258"
  },
  {
    "index": 36,
    "category": "06-persistent-adaptive-intelligence",
    "slug": "36-ttt-layers",
    "title": "Learning to (Learn at Test Time): RNNs with Expressive Hidden States",
    "source": "https://arxiv.org/abs/2407.04620",
    "pdf": "https://arxiv.org/pdf/2407.04620"
  },
  {
    "index": 37,
    "category": "06-persistent-adaptive-intelligence",
    "slug": "37-titans",
    "title": "Titans: Learning to Memorize at Test Time",
    "source": "https://arxiv.org/abs/2501.00663",
    "pdf": "https://arxiv.org/pdf/2501.00663"
  },
  {
    "index": 38,
    "category": "06-persistent-adaptive-intelligence",
    "slug": "38-memos",
    "title": "MemOS: A Memory OS for AI System",
    "source": "https://arxiv.org/abs/2505.22101",
    "pdf": "https://arxiv.org/pdf/2505.22101"
  },
  {
    "index": 39,
    "category": "06-persistent-adaptive-intelligence",
    "slug": "39-language-models-need-sleep",
    "title": "Language Models Need Sleep: Learning to Self-Modify and Consolidate Memories",
    "source": "https://arxiv.org/abs/2606.03979",
    "pdf": "https://arxiv.org/pdf/2606.03979"
  },
  {
    "index": 40,
    "category": "06-persistent-adaptive-intelligence",
    "slug": "40-complementary-learning-systems",
    "title": "Organizing Memories for Generalization in Complementary Learning Systems",
    "source": "https://www.nature.com/articles/s41593-023-01382-9",
    "pdf": "https://www.saxelab.org/assets/papers/Sun2023.pdf"
  },
  {
    "index": 41,
    "category": "06-persistent-adaptive-intelligence",
    "slug": "41-meta-learned-plasticity",
    "title": "Meta-Learning Biologically Plausible Plasticity Rules with Random Feedback Pathways",
    "source": "https://www.nature.com/articles/s41467-023-37562-1",
    "pdf": "https://arxiv.org/pdf/2210.16414"
  }
]