基础模型适配论文趋势 2023–2026

微调与适配

统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 1,492 篇被归入该主题的论文。

主要结论

每年论文数

各会议论文数

按年份和会议统计

基础模型适配论文数，按年份和会议
年份NeurIPSICLRICMLCVPR合计
202381183624159
202494507056270
20251741497662461
202618218714291602

代表论文

按年份和会议均匀挑选，方便快速看到每一届的样貌

全部基础模型适配论文

年份全部2023202420252026
会议全部NeurIPSICLRICMLCVPR

共 602 篇，第 4 / 13 页

  1. ICLR 2026Escaping Policy Contraction: Contraction-Aware PPO (CaPPO) for Stable Language Model Fine-Tuning
  2. ICLR 2026Explainable Token-level Noise Filtering for LLM Fine-tuning Datasets
  3. ICLR 2026Exploring Interpretability for Visual Prompt Tuning with Cross-layer Concepts
  4. ICLR 2026Exploring the Basin-Like Loss Landscape in Large Language Models
  5. ICLR 2026Fine-Grained Activation Steering: Steering Less, Achieving More
  6. ICLR 2026Fine-tuning Behavioral Cloning Policies with Preference‑Based Reinforcement Learning
  7. ICLR 2026Fine-Tuning Diffusion Models via Intermediate Distribution Shaping
  8. ICLR 2026Fine-tuning Done Right in Model Editing
  9. ICLR 2026Fine-tuning Quantized Neural Networks with Zeroth-order Optimization
  10. ICLR 2026FlexLoRA: Entropy-Guided Flexible Low-Rank Adaptation
  11. ICLR 2026Flock: A Knowledge Graph Foundation Model via Learning on Random Walks
  12. ICLR 2026FLoRG: Federated Fine-tuning with Low-rank Gram Matrices and Procrustes Alignment
  13. ICLR 2026FM4NPP: A Scaling Foundation Model for Nuclear and Particle Physics
  14. ICLR 2026FoNE: Precise Single-Token Number Embeddings via Fourier Features
  15. ICLR 2026FZOO: Fast Zeroth-Order Optimizer for Fine‑Tuning Large Language Models towards Adam‑Scale Speed
  16. ICLR 2026GIT-BO: High-Dimensional Bayesian Optimization with Tabular Foundation Models
  17. ICLR 2026Gradient Intrinsic Dimensionality Alignment：Narrowing The Gap Between Low-Rank Adaptation and Full Fine-Tuning
  18. ICLR 2026Gradient-Sign Masking for Task Vector Transport Across Pre-Trained Models
  19. ICLR 2026GranViT: A Fine-Grained Vision Model With Autoregressive Perception For MLLMs
  20. ICLR 2026Heterogeneous Federated Fine-Tuning with Parallel One-Rank Adaptation
  21. ICLR 2026High Accuracy, Less Talk (HALT): Reliable LLMs through Capability-Aligned Finetuning
  22. ICLR 2026Holdout-Loss-Based Data Selection for LLM Finetuning via In-Context Learning
  23. ICLR 2026Homeostatic Adaptation of Optimal Population Codes under Metabolic Stress
  24. ICLR 2026How Base Frequency Shapes RoPE: An Analytical Study of Frequency-Band Formation
  25. ICLR 2026HYPER: A Foundation Model for Inductive Link Prediction with Knowledge Hypergraphs
  26. ICLR 2026IA2: Alignment with ICL Activations improves Supervised Fine-Tuning
  27. ICLR 2026IDEAL: Data Equilibrium Adaptation for Multi-Capability Language Model Alignment
  28. ICLR 2026IGU-LoRA: Adaptive Rank Allocation via Integrated Gradients and Uncertainty-Aware Scoring
  29. ICLR 2026Improving Block-Wise LLM Quantization by 4-bit Block-Wise Optimal Float (BOF4): Analysis and Variations
  30. ICLR 2026IMSE: Intrinsic Mixture of Spectral Experts Fine-tuning for Test-Time Adaptation
  31. ICLR 2026In-Context Learning of Temporal Point Processes with Foundation Inference Models
  32. ICLR 2026Is Finer Better? The Limits of Microscaling Formats in Large Language Models
  33. ICLR 2026Joint Adaptation of Uni-modal Foundation Models for Multi-modal Alzheimer's Disease Diagnosis
  34. ICLR 2026KeepLoRA: Continual Learning with Residual Gradient Adaptation
  35. ICLR 2026Learning What Reinforcement Learning Can't: Interleaved Online Fine-Tuning for Hardest Questions
  36. ICLR 2026LinguaMap: Which Layers of LLMs Speak Your Language and How to Tune Them?
  37. ICLR 2026LoFT: Low-Rank Adaptation That Behaves Like Full Fine-Tuning
  38. ICLR 2026Log-Linear Attention
  39. ICLR 2026Long-tailed Test-Time Adaptation for Vision-Language Models
  40. ICLR 2026LoRA meets Riemannion: Muon Optimizer for Parametrization-independent Low-Rank Adapters
  41. ICLR 2026LoRA-S: An Efficient Low Rank Adaptation scheme via Sylvester equation
  42. ICLR 2026Lost in the Non-convex Loss Landscape: How to Fine-tune the Large Time Series Model?
  43. ICLR 2026Low rank adaptation of chemical foundation models generate effective odorant representations
  44. ICLR 2026Map as a Prompt: Learning Multi-Modal Spatial-Signal Foundation Models for Cross-scenario Wireless Localization
  45. ICLR 2026Memory-Free Continual Learning with Null Space Adaptation for Zero-Shot Vision-Language Models
  46. ICLR 2026MergeTune: Continued Fine-Tuning of Vision-Language Models
  47. ICLR 2026Meta-UCF: Unified Task-Conditioned LoRA Generation for Continual Learning in Large Language Models
  48. ICLR 2026MetaVLA: Unified Meta Co-Training for Efficient Embodied Adaptation
  49. ICLR 2026MiSS: Revisiting the Trade-off in LoRA with an Efficient Shard-Sharing Structure
  50. ICLR 2026Mitigating Non-IID Drift in Zeroth-Order Federated LLM Fine-Tuning with Transferable Sparsity

在 Claude、Cursor 里直接问这个趋势

接上 Paperlist MCP 后，写综述、挑方向或准备投稿时，不用离开对话框就能拿到这页的数字：每年各会议的论文数、增长倍数、涨得最快的子方向和代表论文，AI 会按你的问题整理。

可以直接复制这句话问 AI

用 paperlist 查基础模型适配在 NeurIPS 2023–2026 的论文趋势，哪一年涨得最快？

AI 会调用的工具：get_topic_stats {"topic": "foundation-model-adaptation"}

两分钟接入 Paperlist MCP（Claude Code、Cursor、Codex、ChatGPT）

常见问题

2023–2026 年四大会议一共有多少篇基础模型适配论文？
共 1,492 篇，按年份分别是 2023 年 159 篇、2024 年 270 篇、2025 年 461 篇、2026 年 602 篇。
NeurIPS 2026 有多少篇基础模型适配论文？
NeurIPS 2026 有 182 篇基础模型适配论文，上一届是 174 篇。
ICLR 2026 有多少篇基础模型适配论文？
ICLR 2026 有 187 篇基础模型适配论文，上一届是 149 篇。
ICML 2026 有多少篇基础模型适配论文？
ICML 2026 有 142 篇基础模型适配论文，上一届是 76 篇。
CVPR 2026 有多少篇基础模型适配论文？
CVPR 2026 有 91 篇基础模型适配论文，上一届是 62 篇。
哪个会议的基础模型适配论文最多？
NeurIPS，2023–2026 年共 531 篇。

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