深度学习 · foundation models论文趋势 2023–2026

主要结论

• 深度学习 · foundation models论文从 2023 年的 72 篇增长到 2026 年的 177 篇，三年间扩大到约 2.5 倍。
• NeurIPS 是发深度学习 · foundation models论文最多的会议，2023–2026 年共 299 篇，占四个会议总量的 56%。
• 交叉方向里涨得最快的是基础模型适配：同时属于两个主题的论文从 2023 年的 7 篇增至 2026 年的 66 篇。
• 在「深度学习」的 11 个主题里，它的 2026 年论文数排第 8；同组增长最快的扩散模型是 4.1 倍，深度学习 · foundation models是 2.5 倍。

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

• NeurIPS 2026Inferotemporal Cortex Collaborates Before It Codes: Non-Serial Inter-Area Synergy in the Macaque Ventral Stream
• ICML 2026ACO-MoE-LoRA: Evolving-while-Training for Adapting Segment Anything Model 2 to Specialized Domains
• ICLR 2026Qronos: Correcting the Past by Shaping the Future... in Post-Training Quantization
• CVPR 2026Adapting a Pre-trained Single-Cell Foundation Model to Spatial Gene Expression
• NeurIPS 2025An Investigation of Memorization Risk in Healthcare Foundation Models
• ICML 2025Contrastive Localized Language-Image Pre-Training
• ICLR 2025Revisiting Convolution Architecture in the Realm of DNA Foundation Models
• CVPR 2025DEFOM-Stereo: Depth Foundation Model Based Stereo Matching
• NeurIPS 2024$\textit{Read-ME}$: Refactorizing LLMs as Router-Decoupled Mixture of Experts with System Co-Design
• ICML 2024Position: On the Societal Impact of Open Foundation Models
• CVPR 20243D-LFM: Lifting Foundation Model
• NeurIPS 2023Bridging the Domain Gap: Self-Supervised 3D Scene Understanding with Foundation Models
• ICML 2023Improving Hyperparameter Learning under Approximate Inference in Gaussian Process Models
• NeurIPS 2026Do Pathology Foundation Models Encode Disease Progression? A Pseudotime Analysis of Visual Representations
• ICML 2026Alethia: a Foundational Encoder for Voice Deepfakes
• ICLR 2026DND: Boosting Large Language Models with Dynamic Nested Depth
• CVPR 2026UniSER A Foundation Model for Unified Soft Effects Removal
• NeurIPS 2025ChromFound: Towards A Universal Foundation Model for Single-Cell Chromatin Accessibiltiy Data
• ICML 2025Exploring Criteria of Loss Reweighting to Enhance LLM Unlearning
• ICLR 2025Recite, Reconstruct, Recollect: Memorization in LMs as a Multifaceted Phenomenon

全部深度学习 · foundation models论文

共 206 篇，第 1 / 5 页

1. ICML 2026A robust PPG foundation model using multimodal physiological supervision
2. ICML 2026ACO-MoE-LoRA: Evolving-while-Training for Adapting Segment Anything Model 2 to Specialized Domains
3. ICML 2026Adaptive Residual-Update Steering for Low-Overhead Hallucination Mitigation in Large Vision-Language Models
4. ICML 2026Adversarial Flow Models
5. ICML 2026Agent0-VL: Exploring Self-Evolving Agent for Tool-Integrated Vision-Language Reasoning
6. ICML 2026Alethia: a Foundational Encoder for Voice Deepfakes
7. ICML 2026AlphaGRPO: Unlocking Self-Reflective Multimodal Generation in Unified Multimodal Models via Decompositional Verifiable Reward
8. ICML 2026Are Common Substructures Transferable? Riemannian Graph Foundation Model with Neural Vector Bundles
9. ICML 2026Attention Sinks as Internal Signals for Hallucination Detection in Large Language Models
10. ICML 2026Attentive Multi-Layer Fusion for Vision Transformers
11. ICML 2026Attn-QAT: 4-Bit Attention With Quantization-Aware Training
12. ICML 2026Balancing Understanding and Generation in Discrete Diffusion Models
13. ICML 2026Beyond Log Likelihood: Probability-Based Objectives for Supervised Fine-Tuning across the Model Capability Continuum
14. ICML 2026BIOARC: Discovering Optimal Neural Architectures for Biological Foundation Models
15. ICML 2026BioToken and BioFM – Biologically-Informed Tokenization Enables Accurate and Efficient Genomic Foundation Models
16. ICML 2026BRIDGE: Predicting Human Task Completion Time From Model Performance
17. ICML 2026CAOS: Conformal Aggregation of One-Shot Predictors
18. ICML 2026ChaosNexus: A Foundation Model for ODE-based Chaotic System Forecasting with Hierarchical Multi-scale Awareness
19. ICML 2026Computational Arbitrage in AI Model Markets
20. ICML 2026ConceptMoE: Adaptive Token-to-Concept Compression for Implicit Compute Allocation
21. ICML 2026ConFlux: Multivariate Time Series in Flux, One Unified Forecast in Confluence
22. ICML 2026Curriculum Reinforcement Learning for Black-Box Prompt Tuning via Large Language Models
23. ICML 2026Data Selection for Fine-tuning Vision Language Models via Cross Modal Alignment Trajectories
24. ICML 2026Diversity Matters: Revisiting Test-Time Compute in Vision-Language Models
25. ICML 2026DTop-p MoE: Sparsity-Controlled Dynamic Top-p MoE for Foundation Model Pre-training
26. ICML 2026DyCon: Dynamic Reasoning Control via Evolving Difficulty Modeling
27. ICML 2026End-to-End Compression for Tabular Foundation Models
28. ICML 2026Evaluating Newtonian Mechanics in Video Generative Models with Real Physical Systems
29. ICML 2026Fair-FedMOE: Group-Fair One-Shot Federated Learning via Prototype-Guided Experts for Medical Imaging Analysis
30. ICML 2026Finding the Correct Visual Evidence Without Forgetting: Mitigating Hallucination in LVLMs via Inter-Layer Visual Attention Discrepancy
31. ICML 2026FlashBlock: Attention Caching for Efficient Long-Context Block Diffusion
32. ICML 2026FOCUS & RePAIR: Mitigating Text Degeneration via Token-Level Guidance For Pruned Large Language Models
33. ICML 2026Focusing Where Vision Matters: Selective Training for Large Vision Language Models via Visual Information Gain
34. ICML 2026Foundation Inference Models for Ordinary Differential Equations
35. ICML 2026FPTQuant: Function-Preserving Transforms for LLM Quantization
36. ICML 2026From Kepler to Newton: Inductive Biases Guide Learned World Models in Transformers
37. ICML 2026From Noise to Intent: Anchoring Generative VLA Policies with Residual Bridges
38. ICML 2026From Zero to Hero: Advancing Zero-Shot Foundation Models for Tabular Outlier Detection
39. ICML 2026Genome-Factory: A Library for Tuning, Deploying, and Interpreting Genomic Foundation Models
40. ICML 2026GePBench: Evaluating Fundamental Geometric Perception for Multimodal Large Language Models
41. ICML 2026GFMate: Empowering Graph Foundation Models with Test-time Prompt Tuning
42. ICML 2026Giving Sensors a Voice: Multimodal JEPA for Semantic Time-Series Embeddings
43. ICML 2026Graph is a Substrate Across Data Modalities
44. ICML 2026GraphPFN: A Prior-Data Fitted Graph Foundation Model
45. ICML 2026h1: Bootstrapping LLMs to Reason over Longer Horizons via Reinforcement Learning
46. ICML 2026HaloProbe: Bayesian Detection and Mitigation of Object Hallucinations in Vision-Language Models
47. ICML 2026Head-in-Head in Linear Attention
48. ICML 2026Heterogeneous Customizable Personalized Federated Fine-Tuning Approach for Large Language Models
49. ICML 2026Hierarchical Procedural Meta-Reasoning for Generalizable Multimodal Agents
50. ICML 2026Holi-Spatial: Evolving Video Streams into Holistic 3D Spatial Intelligence

常见问题

2023–2026 年四大会议一共有多少篇深度学习 · foundation models论文？

共 536 篇，按年份分别是 2023 年 72 篇、2024 年 209 篇、2025 年 78 篇、2026 年 177 篇。

NeurIPS 2026 有多少篇深度学习 · foundation models论文？

NeurIPS 2026 有 27 篇深度学习 · foundation models论文，上一届是 15 篇。

ICLR 2026 有多少篇深度学习 · foundation models论文？

ICLR 2026 有 8 篇深度学习 · foundation models论文，上一届是 6 篇。

ICML 2026 有多少篇深度学习 · foundation models论文？

ICML 2026 有 135 篇深度学习 · foundation models论文，上一届是 53 篇。

CVPR 2026 有多少篇深度学习 · foundation models论文？

CVPR 2026 有 7 篇深度学习 · foundation models论文，上一届是 4 篇。

哪个会议的深度学习 · foundation models论文最多？

NeurIPS，2023–2026 年共 299 篇。