Deep learning · large language models papers, 2023–2026

Key findings

• Deep learning · large language models went from 488 papers in 2023 to 1,131 in 2026, roughly 2.3x in three years.
• ICML publishes the most Deep learning · large language models work: 1,608 papers from 2023 to 2026, 69% of the four-venue total.
• The fastest-growing overlap is with AI Agents: papers tagged with both rose from 5 in 2023 to 184 in 2026.
• Among the 11 topics under Deep Learning, it ranks #3 by 2026 paper count; the fastest grower in the group, Diffusion Models, is up 4.1x versus 2.3x here.

Representative papers

Spread across years and venues so every edition shows up

• ICML 2026“very likely” Means “uncertain”? How LLMs Diverge from Humans in Linguistic Uncertainty Quantification
• ICML 2025(How) Do Language Models Track State?
• ICLR 2025AdvWave: Stealthy Adversarial Jailbreak Attack against Large Audio-Language Models
• NeurIPS 2024$\beta$-DPO: Direct Preference Optimization with Dynamic $\beta$
• NeurIPS 20233D-LLM: Injecting the 3D World into Large Language Models
• ICML 2023Are Large Kernels Better Teachers than Transformers for ConvNets?
• ICML 2026$f$-Divergence Self-Play for Tabular Anomaly Detection via Large Language Models
• ICML 2025A Tale of Two Structures: Do LLMs Capture the Fractal Complexity of Language?
• ICLR 2025Emergence of a High-Dimensional Abstraction Phase in Language Transformers
• NeurIPS 2024$\textit{Trans-LoRA}$: towards data-free Transferable Parameter Efficient Finetuning
• NeurIPS 2023A fast heuristic to optimize time-space tradeoff for large models
• ICML 2023Arithmetic Sampling: Parallel Diverse Decoding for Large Language Models
• ICML 2026$L^3$: Large Lookup Layers
• ICML 2025Accelerating LLM Inference with Lossless Speculative Decoding Algorithms for Heterogeneous Vocabularies
• ICLR 2025Holistically Evaluating the Environmental Impact of Creating Language Models
• NeurIPS 2024A distributional simplicity bias in the learning dynamics of transformers
• NeurIPS 2023A Pseudo-Semantic Loss for Autoregressive Models with Logical Constraints
• ICML 2023Auto-Differentiation of Relational Computations for Very Large Scale Machine Learning
• ICML 2026$V_0$: A Generalist Value Model for Any Policy at State Zero
• ICML 2025Accelerating Unbiased LLM Evaluation via Synthetic Feedback

All Deep learning · large language models papers

73 papers, page 2 of 2

51. ICML 2023PAC Prediction Sets for Large Language Models of Code
52. ICML 2023Parallel $Q$-Learning: Scaling Off-policy Reinforcement Learning under Massively Parallel Simulation
53. ICML 2023Pareto Manifold Learning: Tackling multiple tasks via ensembles of single-task models
54. ICML 2023Poisoning Language Models During Instruction Tuning
55. ICML 2023POUF: Prompt-Oriented Unsupervised Fine-tuning for Large Pre-trained Models
56. ICML 2023Pretraining Language Models with Human Preferences
57. ICML 2023QASA: Advanced Question Answering on Scientific Articles
58. ICML 2023Regularizing Towards Soft Equivariance Under Mixed Symmetries
59. ICML 2023SAM operates far from home: eigenvalue regularization as a dynamical phenomenon
60. ICML 2023Same Pre-training Loss, Better Downstream: Implicit Bias Matters for Language Models
61. ICML 2023Searching Large Neighborhoods for Integer Linear Programs with Contrastive Learning
62. ICML 2023Self-supervised learning of Split Invariant Equivariant representations
63. ICML 2023SGD with Large Step Sizes Learns Sparse Features
64. ICML 2023Solving High-Dimensional PDEs with Latent Spectral Models
65. ICML 2023Special Properties of Gradient Descent with Large Learning Rates
66. ICML 2023Structure-informed Language Models Are Protein Designers
67. ICML 2023Towards Sustainable Learning: Coresets for Data-efficient Deep Learning
68. ICML 2023Tractable Control for Autoregressive Language Generation
69. ICML 2023Trompt: Towards a Better Deep Neural Network for Tabular Data
70. ICML 2023Understanding the Distillation Process from Deep Generative Models to Tractable Probabilistic Circuits
71. ICML 2023When Sparsity Meets Contrastive Models: Less Graph Data Can Bring Better Class-Balanced Representations
72. ICML 2023Whose Opinions Do Language Models Reflect?
73. ICML 2023Why do Nearest Neighbor Language Models Work?

FAQ

How many Deep learning · large language models papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

2,334 in total: 488 in 2023, 298 in 2024, 417 in 2025, 1,131 in 2026.

How many Deep learning · large language models papers are at NeurIPS 2024?

NeurIPS 2024 has 298 Deep learning · large language models papers, versus 415 the year before.

How many Deep learning · large language models papers are at ICLR 2025?

ICLR 2025 has 13 Deep learning · large language models papers.

How many Deep learning · large language models papers are at ICML 2026?

ICML 2026 has 1,131 Deep learning · large language models papers, versus 404 the year before.

Which conference publishes the most Deep learning · large language models papers?

ICML, with 1,608 papers from 2023 to 2026.