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 10 / 13 页

  1. NeurIPS 2026Coarse-to-Fine 3D MRI Reconstruction via Resolution-Agnostic Neural Operators
  2. NeurIPS 2026Communication-Efficient Personalized Adaptation via Federated-Local Model Merging
  3. NeurIPS 2026Compact SO(3) Equivariant Atomistic Foundation Models via Structural Pruning
  4. NeurIPS 2026Compute-Optimal Pretrain--Fine-tune in Ridge Gradient Flow
  5. NeurIPS 2026CORA: Per-Slice Coherent Orthogonal Rotation for SVD-based Low-Rank Adaptation
  6. NeurIPS 2026CORTEG: Foundation Models Enable Cross-Modality Representation Transfer from Scalp to Intracranial Brain Recordings
  7. NeurIPS 2026CrafterDojo: A Suite of Foundation Models for Building Open-Ended Embodied Agents in Crafter
  8. NeurIPS 2026DeepVoting: Learning and Improving Voting Rules with Fine-Tuning
  9. NeurIPS 2026DEFT: Disentanglement-Enhanced Fine-Tuning for EEG Foundation Models
  10. NeurIPS 2026Diffusion fine-tuning with Rewarded Moment Matching Distillation
  11. NeurIPS 2026Diffusion Fine-Tuning: Iterative Refinement for Advanced Grounding with Diffusion Large Language Models
  12. NeurIPS 2026Diffusion Meta-Prompting and Steering for Generalizable Foundation Model Adaptation
  13. NeurIPS 2026Diffusion Tree Search for Inference Time Adaptation of Material Foundation Models
  14. NeurIPS 2026Diffusion-DRF: Free, Rich, and Differentiable Reward for Video Diffusion Fine-Tuning
  15. NeurIPS 2026Disentangling Homophilic and Heterophilic Patterns for Multi-Domain Graph Foundation Models
  16. NeurIPS 2026Distillation of Foundation Models for Time-dependent PDEs
  17. NeurIPS 2026Do Pathology Foundation Models Encode Disease Progression? A Pseudotime Analysis of Visual Representations
  18. NeurIPS 2026Dominant-Layer ZO: A Single Layer Dominates Zeroth-Order Fine-Tuning of LLMs
  19. NeurIPS 2026DRIVE: Fine-tuning via Data Contribution- and Diversity-aware Weighting with Prior Regularization
  20. NeurIPS 2026Dual-Pronged LoRA: Achieving Near-Zero Forgetting and High-Performance Adaptation for MLLMs
  21. NeurIPS 2026EEG-X: Toward Device-Agnostic and Noise-Robust Foundation Models for EEG
  22. NeurIPS 2026Efficient Collaborative LLM Fine-Tuning over Heterogeneous Mobile Devices via Many Backbones to One Side-Network Tuning
  23. NeurIPS 2026Efficient LLM Adaptation with Forward-Only Passes
  24. NeurIPS 2026Efficiently Aligning Draft Models via Parameter- and Data-Efficient Adaptation
  25. NeurIPS 2026Embedding Foundation Model Predictions in Discrete-Choice Models with Structural Guarantees
  26. NeurIPS 2026Emergent Biological Capabilities in a Foundation Model for Molecular Interactions
  27. NeurIPS 2026Enhancing Gaze Reasoning in Vision Foundation Models for Gaze Following
  28. NeurIPS 2026ESSAM: A Novel Competitive Evolution Strategies Approach to Reinforcement Learning for Memory Efficient LLMs Fine-Tuning
  29. NeurIPS 2026Estimating and Orthogonalizing Unknown Pre-training Gradients for Continual Fine-tuning of Large Language Models
  30. NeurIPS 2026Evaluating Uncertainty Calibration in Probabilistic Time Series Foundation Models
  31. NeurIPS 2026Evolution Fine-Tuning: Learning to Discover Across 371 Optimization Tasks
  32. NeurIPS 2026Exploiting Fine-Tuning Structures to Improve Adversarial Transferability on Downstream SAM
  33. NeurIPS 2026Extending Pretrained 10-Second ECG Foundation Models to Longer Horizons
  34. NeurIPS 2026FedLoVA: Value-Only Aggregation for Federated LoRA Fine-Tuning of Large Language Models
  35. NeurIPS 2026FedReCall: Recalling Client-Specific Directions in Federated LoRA Fine-tuning
  36. NeurIPS 2026Fine-Grained Benchmark Generation for Comprehensive Evaluation of Foundation Models
  37. NeurIPS 2026Fine-Tuning Improves Information Conveyance in Language Models
  38. NeurIPS 2026Fine-tuning language encoding models on slow fMRI improves prediction for fast ECoG
  39. NeurIPS 2026Fine-Tuning Language Models to Know What They Know
  40. NeurIPS 2026FlatClip: Reusing Image Foundation Models for fMRI Representation Learning via Cortical Flatmaps
  41. NeurIPS 2026FOCUS: Benchmarking Retinal Model Generalization from Foundation Vision Encoders to Multimodal LLMs
  42. NeurIPS 2026FoldAbS: Repurposing the Protein Folding Model as a Foundation Encoder for Antibody Screening
  43. NeurIPS 2026Follow the Mean: Reference-Guided Flow Matching
  44. NeurIPS 2026Frank-LoRA: Federated Rank-Aware LoRA for Fine-Tuning Large Models
  45. NeurIPS 2026From Next-Token to Next-Block: A Principled Adaptation Path for Diffusion LLMs
  46. NeurIPS 2026Full Fine-Tuning Is Not the Problem: Why Adam Fails and SGD Succeeds in Few-Shot CLIP Adaptation
  47. NeurIPS 2026GAPS: Gradient-Aware Adaptation-Gap Scoring for Time-Series Anomaly Detection with Foundation Models
  48. NeurIPS 2026Glob3R: Global Structure-from-Motion with 3D Foundation Models
  49. NeurIPS 2026GlucoFM: A Dual-Stream Foundation Model for Continuous Glucose Monitoring
  50. NeurIPS 2026Guarding the Life Code: Preserving Membership Privacy in Genomic Foundation Models

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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