Research map / Continual learning
Continual fine-tuning of LLMs: research map
264 accepted papers on Continual fine-tuning of LLMs in Continual learning, from ICML, NeurIPS, ICLR, CVPR and AAAI (2016–2026), grouped into 2 clusters and 5 approaches. The busiest year so far is 2026.
Within Continual learning, its share grew from 14.8% in 2023–24 to 33.9% in 2025–26 (52 → 195 papers at ICML, NeurIPS, CVPR and AAAI, the venues with data for all four years).
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Approaches and key papers
unlearning · multimodal · instruction · 142 papers
Approaches in this cluster:
- Continual pretraining of language models (66 papers)
Analyzes and mitigates forgetting during continual pretraining and knowledge updating of large models. - Mixture-of-experts for multimodal continual tuning (52 papers)
Expands vision-language models with expert adapters and benchmarks continual multimodal learning. - Machine unlearning by selective forgetting (24 papers)
Removes specific data influence from trained networks without full retraining.
Most cited and most cited since 2024:
- Can Bad Teaching Induce Forgetting? Unlearning in Deep Networks Using an Incompetent Teacher (AAAI 2023 · 113 citations)
- LAMOL: LAnguage MOdeling for Lifelong Language Learning (ICLR 2020 · 111 citations)
- Fast Machine Unlearning without Retraining through Selective Synaptic Dampening (AAAI 2024 · 75 citations)
- Continual Self-supervised Learning: Towards Universal Multi-modal Medical Data Representation Learning (CVPR 2024 · 36 citations)
pre trained · lora · fine tuning · 122 papers
Approaches in this cluster:
- Low-rank and model-merging adaptation (90 papers)
Controls forgetting in continual fine-tuning through low-rank updates, prompts and weight merging. - Synthetic data and merging for CLIP (32 papers)
Uses synthetic replay, LoRA recycling and sequential merging to continually adapt vision-language models.
Most cited and most cited since 2024:
- Boosting Continual Learning of Vision-Language Models via Mixture-of-Experts Adapters (CVPR 2024 · 124 citations)
- Catastrophic Forgetting Meets Negative Transfer: Batch Spectral Shrinkage for Safe Transfer Learning (NeurIPS 2019 · 101 citations)
- InfLoRA: Interference-Free Low-Rank Adaptation for Continual Learning (CVPR 2024 · 69 citations)
- Pre-trained Vision and Language Transformers Are Few-Shot Incremental Learners (CVPR 2024 · 37 citations)
Related topics in Continual learning
- Online and replay-based (582)
- Domain and prompt-based (114)
- Class-incremental (303)