深度学习 · foundation models论文趋势 2023–2026
ICML/NeurIPS 深度学习方向:foundation_models
统计范围:NeurIPS、ICLR、ICML、CVPR 四个会议,2023–2026 年,共 536 篇被归入该主题的论文。
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。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 2023 | 65 | 0 | 7 | 0 | 72 |
| 2024 | 192 | 0 | 11 | 6 | 209 |
| 2025 | 15 | 6 | 53 | 4 | 78 |
| 2026 | 27 | 8 | 135 | 7 | 177 |
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 177 篇,第 1 / 4 页
- CVPR 20262D-LFM Lifting Foundation Model without 3D Supervision
- CVPR 2026Adapting a Pre-trained Single-Cell Foundation Model to Spatial Gene Expression
- CVPR 2026CARE A Molecular-Guided Foundation Model with Adaptive Region Modeling for
- CVPR 2026Emergent Extreme-View Geometry in 3D Foundation Models
- CVPR 2026Fine-Tuning Impairs the Balancedness of Foundation Models in Long-tailed Personalized
- CVPR 2026Revisiting Model Stitching In the Foundation Model Era
- CVPR 2026UniSER A Foundation Model for Unified Soft Effects Removal
- ICLR 2026DND: Boosting Large Language Models with Dynamic Nested Depth
- ICLR 2026Fine-Grained Activation Steering: Steering Less, Achieving More
- ICLR 2026FoNE: Precise Single-Token Number Embeddings via Fourier Features
- ICLR 2026How Base Frequency Shapes RoPE: An Analytical Study of Frequency-Band Formation
- ICLR 2026Not All Models Suit Expert Offloading: On Local Routing Consistency of Mixture-of-Expert Models
- ICLR 2026Qronos: Correcting the Past by Shaping the Future... in Post-Training Quantization
- ICLR 2026Speculative Speculative Decoding
- ICLR 2026The Softmax Bottleneck Does Not Limit the Probabilities of the Most Likely Tokens
- ICML 2026A robust PPG foundation model using multimodal physiological supervision
- ICML 2026ACO-MoE-LoRA: Evolving-while-Training for Adapting Segment Anything Model 2 to Specialized Domains
- ICML 2026Adaptive Residual-Update Steering for Low-Overhead Hallucination Mitigation in Large Vision-Language Models
- ICML 2026Adversarial Flow Models
- ICML 2026Agent0-VL: Exploring Self-Evolving Agent for Tool-Integrated Vision-Language Reasoning
- ICML 2026Alethia: a Foundational Encoder for Voice Deepfakes
- ICML 2026AlphaGRPO: Unlocking Self-Reflective Multimodal Generation in Unified Multimodal Models via Decompositional Verifiable Reward
- ICML 2026Are Common Substructures Transferable? Riemannian Graph Foundation Model with Neural Vector Bundles
- ICML 2026Attention Sinks as Internal Signals for Hallucination Detection in Large Language Models
- ICML 2026Attentive Multi-Layer Fusion for Vision Transformers
- ICML 2026Attn-QAT: 4-Bit Attention With Quantization-Aware Training
- ICML 2026Balancing Understanding and Generation in Discrete Diffusion Models
- ICML 2026Beyond Log Likelihood: Probability-Based Objectives for Supervised Fine-Tuning across the Model Capability Continuum
- ICML 2026BIOARC: Discovering Optimal Neural Architectures for Biological Foundation Models
- ICML 2026BioToken and BioFM – Biologically-Informed Tokenization Enables Accurate and Efficient Genomic Foundation Models
- ICML 2026BRIDGE: Predicting Human Task Completion Time From Model Performance
- ICML 2026CAOS: Conformal Aggregation of One-Shot Predictors
- ICML 2026ChaosNexus: A Foundation Model for ODE-based Chaotic System Forecasting with Hierarchical Multi-scale Awareness
- ICML 2026Computational Arbitrage in AI Model Markets
- ICML 2026ConceptMoE: Adaptive Token-to-Concept Compression for Implicit Compute Allocation
- ICML 2026ConFlux: Multivariate Time Series in Flux, One Unified Forecast in Confluence
- ICML 2026Curriculum Reinforcement Learning for Black-Box Prompt Tuning via Large Language Models
- ICML 2026Data Selection for Fine-tuning Vision Language Models via Cross Modal Alignment Trajectories
- ICML 2026Diversity Matters: Revisiting Test-Time Compute in Vision-Language Models
- ICML 2026DTop-p MoE: Sparsity-Controlled Dynamic Top-p MoE for Foundation Model Pre-training
- ICML 2026DyCon: Dynamic Reasoning Control via Evolving Difficulty Modeling
- ICML 2026End-to-End Compression for Tabular Foundation Models
- ICML 2026Evaluating Newtonian Mechanics in Video Generative Models with Real Physical Systems
- ICML 2026Fair-FedMOE: Group-Fair One-Shot Federated Learning via Prototype-Guided Experts for Medical Imaging Analysis
- ICML 2026Finding the Correct Visual Evidence Without Forgetting: Mitigating Hallucination in LVLMs via Inter-Layer Visual Attention Discrepancy
- ICML 2026FlashBlock: Attention Caching for Efficient Long-Context Block Diffusion
- ICML 2026FOCUS & RePAIR: Mitigating Text Degeneration via Token-Level Guidance For Pruned Large Language Models
- ICML 2026Focusing Where Vision Matters: Selective Training for Large Vision Language Models via Visual Information Gain
- ICML 2026Foundation Inference Models for Ordinary Differential Equations
- ICML 2026FPTQuant: Function-Preserving Transforms for LLM Quantization
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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。
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用 paperlist 查深度学习 · foundation models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": "dl-foundation-models"}
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。
「深度学习」下的其他主题
- 扩散模型 6,900
- 深度学习 · generative models and autoencoders 4,314
- 深度学习 · large language models 2,334
- 深度学习 · self supervised learning 1,958
- 深度学习 · graph neural networks 1,648
- 深度学习 · optimization 953
- 深度学习 · representation learning 802
- 深度学习 · probabilistic methods 637
- 深度学习 · causal inference 316
- 深度学习 · transfer learning 197