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

2,334 papers, page 46 of 47

2251. NeurIPS 2023Selective Amnesia: A Continual Learning Approach to Forgetting in Deep Generative Models
2252. NeurIPS 2023Self-Chained Image-Language Model for Video Localization and Question Answering
2253. NeurIPS 2023Self-Evaluation Guided Beam Search for Reasoning
2254. NeurIPS 2023Semantic HELM: A Human-Readable Memory for Reinforcement Learning
2255. NeurIPS 2023Semantic segmentation of sparse irregular point clouds for leaf/wood discrimination
2256. NeurIPS 2023Semi-Implicit Denoising Diffusion Models (SIDDMs)
2257. NeurIPS 2023Setting the Trap: Capturing and Defeating Backdoors in Pretrained Language Models through Honeypots
2258. NeurIPS 2023SGFormer: Simplifying and Empowering Transformers for Large-Graph Representations
2259. NeurIPS 2023Skill-it! A data-driven skills framework for understanding and training language models
2260. NeurIPS 2023Smooth, exact rotational symmetrization for deep learning on point clouds
2261. NeurIPS 2023Smoothing the Landscape Boosts the Signal for SGD: Optimal Sample Complexity for Learning Single Index Models
2262. NeurIPS 2023SoTTA: Robust Test-Time Adaptation on Noisy Data Streams
2263. NeurIPS 2023SPAE: Semantic Pyramid AutoEncoder for Multimodal Generation with Frozen LLMs
2264. NeurIPS 2023Sparse Deep Learning for Time Series Data: Theory and Applications
2265. NeurIPS 2023Sparse Parameterization for Epitomic Dataset Distillation
2266. NeurIPS 2023SpecTr: Fast Speculative Decoding via Optimal Transport
2267. NeurIPS 2023Statistically Valid Variable Importance Assessment through Conditional Permutations
2268. NeurIPS 2023Stochastic Collapse: How Gradient Noise Attracts SGD Dynamics Towards Simpler Subnetworks
2269. NeurIPS 2023Structural Pruning for Diffusion Models
2270. NeurIPS 2023Structured Prediction with Stronger Consistency Guarantees
2271. NeurIPS 2023Structured State Space Models for In-Context Reinforcement Learning
2272. NeurIPS 2023SugarCrepe: Fixing Hackable Benchmarks for Vision-Language Compositionality
2273. NeurIPS 2023SwapPrompt: Test-Time Prompt Adaptation for Vision-Language Models
2274. NeurIPS 2023SwiFT: Swin 4D fMRI Transformer
2275. NeurIPS 2023Symbol-LLM: Leverage Language Models for Symbolic System in Visual Human Activity Reasoning
2276. NeurIPS 2023TART: A plug-and-play Transformer module for task-agnostic reasoning
2277. NeurIPS 2023Task Arithmetic in the Tangent Space: Improved Editing of Pre-Trained Models
2278. NeurIPS 2023Temporal Dynamic Quantization for Diffusion Models
2279. NeurIPS 2023Test-Time Distribution Normalization for Contrastively Learned Visual-language Models
2280. NeurIPS 2023Testing the General Deductive Reasoning Capacity of Large Language Models Using OOD Examples
2281. NeurIPS 2023Text Promptable Surgical Instrument Segmentation with Vision-Language Models
2282. NeurIPS 2023Textually Pretrained Speech Language Models
2283. NeurIPS 2023The Contextual Lasso: Sparse Linear Models via Deep Neural Networks
2284. NeurIPS 2023The Emergence of Essential Sparsity in Large Pre-trained Models: The Weights that Matter
2285. NeurIPS 2023The geometry of hidden representations of large transformer models
2286. NeurIPS 2023The Goldilocks of Pragmatic Understanding: Fine-Tuning Strategy Matters for Implicature Resolution by LLMs
2287. NeurIPS 2023The Learnability of In-Context Learning
2288. NeurIPS 2023The Quantization Model of Neural Scaling
2289. NeurIPS 2023The Shaped Transformer: Attention Models in the Infinite Depth-and-Width Limit
2290. NeurIPS 2023Three Towers: Flexible Contrastive Learning with Pretrained Image Models
2291. NeurIPS 2023To Repeat or Not To Repeat: Insights from Scaling LLM under Token-Crisis
2292. NeurIPS 2023Token-Scaled Logit Distillation for Ternary Weight Generative Language Models
2293. NeurIPS 2023Toolformer: Language Models Can Teach Themselves to Use Tools
2294. NeurIPS 2023ToolkenGPT: Augmenting Frozen Language Models with Massive Tools via Tool Embeddings
2295. NeurIPS 2023Tools for Verifying Neural Models' Training Data
2296. NeurIPS 2023Top-Ambiguity Samples Matter: Understanding Why Deep Ensemble Works in Selective Classification
2297. NeurIPS 2023Topological Parallax: A Geometric Specification for Deep Perception Models
2298. NeurIPS 2023Towards Federated Foundation Models: Scalable Dataset Pipelines for Group-Structured Learning
2299. NeurIPS 2023Towards Optimal Caching and Model Selection for Large Model Inference
2300. NeurIPS 2023Towards Semi-Structured Automatic ICD Coding via Tree-based Contrastive Learning

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.