Deep learning · foundation models papers, 2023–2026

Deep learning area: foundation_models

Scope: NeurIPS, ICLR, ICML and CVPR, 2023–2026. 536 papers are tagged with this topic.

Key findings

Papers per year

Papers per venue

Counts by year and venue

Deep learning · foundation models papers by year and venue
YearNeurIPSICLRICMLCVPRTotal
20236507072
20241920116209
202515653478
20262781357177

Representative papers

Spread across years and venues so every edition shows up

All Deep learning · foundation models papers

YearAll2023202420252026
VenueAllNeurIPSICLRICMLCVPR

299 papers, page 5 of 6

  1. NeurIPS 2024ShiftAddLLM: Accelerating Pretrained LLMs via Post-Training Multiplication-Less Reparameterization
  2. NeurIPS 2024SimVG: A Simple Framework for Visual Grounding with Decoupled Multi-modal Fusion
  3. NeurIPS 2024Single Image Reflection Separation via Dual-Stream Interactive Transformers
  4. NeurIPS 2024Slot State Space Models
  5. NeurIPS 2024SOFTS: Efficient Multivariate Time Series Forecasting with Series-Core Fusion
  6. NeurIPS 2024Spectral Adapter: Fine-Tuning in Spectral Space
  7. NeurIPS 2024Spiking Token Mixer: An event-driven friendly Former structure for spiking neural networks
  8. NeurIPS 2024START: A Generalized State Space Model with Saliency-Driven Token-Aware Transformation
  9. NeurIPS 2024Structured Unrestricted-Rank Matrices for Parameter Efficient Finetuning
  10. NeurIPS 2024SVFT: Parameter-Efficient Fine-Tuning with Singular Vectors
  11. NeurIPS 2024SwitchHead: Accelerating Transformers with Mixture-of-Experts Attention
  12. NeurIPS 2024The Empirical Impact of Neural Parameter Symmetries, or Lack Thereof
  13. NeurIPS 2024The Expressive Capacity of State Space Models: A Formal Language Perspective
  14. NeurIPS 2024The Mamba in the Llama: Distilling and Accelerating Hybrid Models
  15. NeurIPS 2024The Selective $G$-Bispectrum and its Inversion: Applications to $G$-Invariant Networks
  16. NeurIPS 2024Theoretical Characterisation of the Gauss Newton Conditioning in Neural Networks
  17. NeurIPS 2024Theoretical Foundations of Deep Selective State-Space Models
  18. NeurIPS 2024TimeXer: Empowering Transformers for Time Series Forecasting with Exogenous Variables
  19. NeurIPS 2024Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series
  20. NeurIPS 2024Towards Croppable Implicit Neural Representations
  21. NeurIPS 2024Transformers to SSMs: Distilling Quadratic Knowledge to Subquadratic Models
  22. NeurIPS 2024Understanding and Minimising Outlier Features in Transformer Training
  23. NeurIPS 2024Understanding Representation of Deep Equilibrium Models from Neural Collapse Perspective
  24. NeurIPS 2024Understanding the Differences in Foundation Models: Attention, State Space Models, and Recurrent Neural Networks
  25. NeurIPS 2024Understanding Transformer Reasoning Capabilities via Graph Algorithms
  26. NeurIPS 2024UNIT: Unifying Image and Text Recognition in One Vision Encoder
  27. NeurIPS 2024UniTS: A Unified Multi-Task Time Series Model
  28. NeurIPS 2024Universal Neural Functionals
  29. NeurIPS 2024Unveiling the Hidden Structure of Self-Attention via Kernel Principal Component Analysis
  30. NeurIPS 2024VB-LoRA: Extreme Parameter Efficient Fine-Tuning with Vector Banks
  31. NeurIPS 2024Vision Transformer Neural Architecture Search for Out-of-Distribution Generalization: Benchmark and Insights
  32. NeurIPS 2024xLSTM: Extended Long Short-Term Memory
  33. NeurIPS 2024YOLOv10: Real-Time End-to-End Object Detection
  34. NeurIPS 2024You Only Cache Once: Decoder-Decoder Architectures for Language Models
  35. NeurIPS 20234M: Massively Multimodal Masked Modeling
  36. NeurIPS 2023A Pseudo-Semantic Loss for Autoregressive Models with Logical Constraints
  37. NeurIPS 2023ADGym: Design Choices for Deep Anomaly Detection
  38. NeurIPS 2023Agnostically Learning Single-Index Models using Omnipredictors
  39. NeurIPS 2023An Information-Theoretic Evaluation of Generative Models in Learning Multi-modal Distributions
  40. NeurIPS 2023BayesTune: Bayesian Sparse Deep Model Fine-tuning
  41. NeurIPS 2023Beyond Confidence: Reliable Models Should Also Consider Atypicality
  42. NeurIPS 2023BiMatting: Efficient Video Matting via Binarization
  43. NeurIPS 2023Birth of a Transformer: A Memory Viewpoint
  44. NeurIPS 2023Bridging the Domain Gap: Self-Supervised 3D Scene Understanding with Foundation Models
  45. NeurIPS 2023C-Eval: A Multi-Level Multi-Discipline Chinese Evaluation Suite for Foundation Models
  46. NeurIPS 2023CHAMMI: A benchmark for channel-adaptive models in microscopy imaging
  47. NeurIPS 2023Compositional Abilities Emerge Multiplicatively: Exploring Diffusion Models on a Synthetic Task
  48. NeurIPS 2023Contextually Affinitive Neighborhood Refinery for Deep Clustering
  49. NeurIPS 2023Differentiable Random Partition Models
  50. NeurIPS 2023Distributed Inference and Fine-tuning of Large Language Models Over The Internet

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FAQ

How many Deep learning · foundation models papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?
536 in total: 72 in 2023, 209 in 2024, 78 in 2025, 177 in 2026.
How many Deep learning · foundation models papers are at NeurIPS 2026?
NeurIPS 2026 has 27 Deep learning · foundation models papers, versus 15 the year before.
How many Deep learning · foundation models papers are at ICLR 2026?
ICLR 2026 has 8 Deep learning · foundation models papers, versus 6 the year before.
How many Deep learning · foundation models papers are at ICML 2026?
ICML 2026 has 135 Deep learning · foundation models papers, versus 53 the year before.
How many Deep learning · foundation models papers are at CVPR 2026?
CVPR 2026 has 7 Deep learning · foundation models papers, versus 4 the year before.
Which conference publishes the most Deep learning · foundation models papers?
NeurIPS, with 299 papers from 2023 to 2026.

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