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

每年论文数

各会议论文数

按年份和会议统计

深度学习 · foundation models论文数,按年份和会议
年份NeurIPSICLRICMLCVPR合计
20236507072
20241920116209
202515653478
20262781357177

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

全部深度学习 · foundation models论文

共 536 篇,第 1 / 11 页

  1. CVPR 20262D-LFM Lifting Foundation Model without 3D Supervision
  2. CVPR 2026Adapting a Pre-trained Single-Cell Foundation Model to Spatial Gene Expression
  3. CVPR 2026CARE A Molecular-Guided Foundation Model with Adaptive Region Modeling for
  4. CVPR 2026Emergent Extreme-View Geometry in 3D Foundation Models
  5. CVPR 2026Fine-Tuning Impairs the Balancedness of Foundation Models in Long-tailed Personalized
  6. CVPR 2026Revisiting Model Stitching In the Foundation Model Era
  7. CVPR 2026UniSER A Foundation Model for Unified Soft Effects Removal
  8. ICLR 2026DND: Boosting Large Language Models with Dynamic Nested Depth
  9. ICLR 2026Fine-Grained Activation Steering: Steering Less, Achieving More
  10. ICLR 2026FoNE: Precise Single-Token Number Embeddings via Fourier Features
  11. ICLR 2026How Base Frequency Shapes RoPE: An Analytical Study of Frequency-Band Formation
  12. ICLR 2026Not All Models Suit Expert Offloading: On Local Routing Consistency of Mixture-of-Expert Models
  13. ICLR 2026Qronos: Correcting the Past by Shaping the Future... in Post-Training Quantization
  14. ICLR 2026Speculative Speculative Decoding
  15. ICLR 2026The Softmax Bottleneck Does Not Limit the Probabilities of the Most Likely Tokens
  16. ICML 2026A robust PPG foundation model using multimodal physiological supervision
  17. ICML 2026ACO-MoE-LoRA: Evolving-while-Training for Adapting Segment Anything Model 2 to Specialized Domains
  18. ICML 2026Adaptive Residual-Update Steering for Low-Overhead Hallucination Mitigation in Large Vision-Language Models
  19. ICML 2026Adversarial Flow Models
  20. ICML 2026Agent0-VL: Exploring Self-Evolving Agent for Tool-Integrated Vision-Language Reasoning
  21. ICML 2026Alethia: a Foundational Encoder for Voice Deepfakes
  22. ICML 2026AlphaGRPO: Unlocking Self-Reflective Multimodal Generation in Unified Multimodal Models via Decompositional Verifiable Reward
  23. ICML 2026Are Common Substructures Transferable? Riemannian Graph Foundation Model with Neural Vector Bundles
  24. ICML 2026Attention Sinks as Internal Signals for Hallucination Detection in Large Language Models
  25. ICML 2026Attentive Multi-Layer Fusion for Vision Transformers
  26. ICML 2026Attn-QAT: 4-Bit Attention With Quantization-Aware Training
  27. ICML 2026Balancing Understanding and Generation in Discrete Diffusion Models
  28. ICML 2026Beyond Log Likelihood: Probability-Based Objectives for Supervised Fine-Tuning across the Model Capability Continuum
  29. ICML 2026BIOARC: Discovering Optimal Neural Architectures for Biological Foundation Models
  30. ICML 2026BioToken and BioFM – Biologically-Informed Tokenization Enables Accurate and Efficient Genomic Foundation Models
  31. ICML 2026BRIDGE: Predicting Human Task Completion Time From Model Performance
  32. ICML 2026CAOS: Conformal Aggregation of One-Shot Predictors
  33. ICML 2026ChaosNexus: A Foundation Model for ODE-based Chaotic System Forecasting with Hierarchical Multi-scale Awareness
  34. ICML 2026Computational Arbitrage in AI Model Markets
  35. ICML 2026ConceptMoE: Adaptive Token-to-Concept Compression for Implicit Compute Allocation
  36. ICML 2026ConFlux: Multivariate Time Series in Flux, One Unified Forecast in Confluence
  37. ICML 2026Curriculum Reinforcement Learning for Black-Box Prompt Tuning via Large Language Models
  38. ICML 2026Data Selection for Fine-tuning Vision Language Models via Cross Modal Alignment Trajectories
  39. ICML 2026Diversity Matters: Revisiting Test-Time Compute in Vision-Language Models
  40. ICML 2026DTop-p MoE: Sparsity-Controlled Dynamic Top-p MoE for Foundation Model Pre-training
  41. ICML 2026DyCon: Dynamic Reasoning Control via Evolving Difficulty Modeling
  42. ICML 2026End-to-End Compression for Tabular Foundation Models
  43. ICML 2026Evaluating Newtonian Mechanics in Video Generative Models with Real Physical Systems
  44. ICML 2026Fair-FedMOE: Group-Fair One-Shot Federated Learning via Prototype-Guided Experts for Medical Imaging Analysis
  45. ICML 2026Finding the Correct Visual Evidence Without Forgetting: Mitigating Hallucination in LVLMs via Inter-Layer Visual Attention Discrepancy
  46. ICML 2026FlashBlock: Attention Caching for Efficient Long-Context Block Diffusion
  47. ICML 2026FOCUS & RePAIR: Mitigating Text Degeneration via Token-Level Guidance For Pruned Large Language Models
  48. ICML 2026Focusing Where Vision Matters: Selective Training for Large Vision Language Models via Visual Information Gain
  49. ICML 2026Foundation Inference Models for Ordinary Differential Equations
  50. ICML 2026FPTQuant: Function-Preserving Transforms for LLM Quantization

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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。

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