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

415 papers, page 7 of 9

301. NeurIPS 2023QATCH: Benchmarking SQL-centric tasks with Table Representation Learning Models on Your Data
302. NeurIPS 2023Quantification of Uncertainty with Adversarial Models
303. NeurIPS 2023QuantSR: Accurate Low-bit Quantization for Efficient Image Super-Resolution
304. NeurIPS 2023RADAR: Robust AI-Text Detection via Adversarial Learning
305. NeurIPS 2023RaLEs: a Benchmark for Radiology Language Evaluations
306. NeurIPS 2023Random-Access Infinite Context Length for Transformers
307. NeurIPS 2023RealTime QA: What's the Answer Right Now?
308. NeurIPS 2023REFINE: A Fine-Grained Medication Recommendation System Using Deep Learning and Personalized Drug Interaction Modeling
309. NeurIPS 2023Regularizing Neural Networks with Meta-Learning Generative Models
310. NeurIPS 2023RenderMe-360: A Large Digital Asset Library and Benchmarks Towards High-fidelity Head Avatars
311. NeurIPS 2023Reproducibility in Multiple Instance Learning: A Case For Algorithmic Unit Tests
312. NeurIPS 2023Reproducibility study of the Fairness-enhanced Node Representation Learning
313. NeurIPS 2023ResMem: Learn what you can and memorize the rest
314. NeurIPS 2023Response Length Perception and Sequence Scheduling: An LLM-Empowered LLM Inference Pipeline
315. NeurIPS 2023Rethinking Gauss-Newton for learning over-parameterized models
316. NeurIPS 2023Revisit the Power of Vanilla Knowledge Distillation: from Small Scale to Large Scale
317. NeurIPS 2023Revisiting Adversarial Training for ImageNet: Architectures, Training and Generalization across Threat Models
318. NeurIPS 2023REx: Data-Free Residual Quantization Error Expansion
319. NeurIPS 2023RoboCLIP: One Demonstration is Enough to Learn Robot Policies
320. NeurIPS 2023Robust Learning with Progressive Data Expansion Against Spurious Correlation
321. NeurIPS 2023RRHF: Rank Responses to Align Language Models with Human Feedback
322. NeurIPS 2023S-CLIP: Semi-supervised Vision-Language Learning using Few Specialist Captions
323. NeurIPS 2023SatLM: Satisfiability-Aided Language Models Using Declarative Prompting
324. NeurIPS 2023Scale Alone Does not Improve Mechanistic Interpretability in Vision Models
325. NeurIPS 2023Scaling Laws for Hyperparameter Optimization
326. NeurIPS 2023Scaling laws for language encoding models in fMRI
327. NeurIPS 2023Scaling MLPs: A Tale of Inductive Bias
328. NeurIPS 2023Scaling Riemannian Diffusion Models
329. NeurIPS 2023Schema-learning and rebinding as mechanisms of in-context learning and emergence
330. NeurIPS 2023Scientific Document Retrieval using Multi-level Aspect-based Queries
331. NeurIPS 2023Scissorhands: Exploiting the Persistence of Importance Hypothesis for LLM KV Cache Compression at Test Time
332. NeurIPS 2023Selective Amnesia: A Continual Learning Approach to Forgetting in Deep Generative Models
333. NeurIPS 2023Self-Chained Image-Language Model for Video Localization and Question Answering
334. NeurIPS 2023Self-Evaluation Guided Beam Search for Reasoning
335. NeurIPS 2023Semantic HELM: A Human-Readable Memory for Reinforcement Learning
336. NeurIPS 2023Semantic segmentation of sparse irregular point clouds for leaf/wood discrimination
337. NeurIPS 2023Semi-Implicit Denoising Diffusion Models (SIDDMs)
338. NeurIPS 2023Setting the Trap: Capturing and Defeating Backdoors in Pretrained Language Models through Honeypots
339. NeurIPS 2023SGFormer: Simplifying and Empowering Transformers for Large-Graph Representations
340. NeurIPS 2023Skill-it! A data-driven skills framework for understanding and training language models
341. NeurIPS 2023Smooth, exact rotational symmetrization for deep learning on point clouds
342. NeurIPS 2023Smoothing the Landscape Boosts the Signal for SGD: Optimal Sample Complexity for Learning Single Index Models
343. NeurIPS 2023SoTTA: Robust Test-Time Adaptation on Noisy Data Streams
344. NeurIPS 2023SPAE: Semantic Pyramid AutoEncoder for Multimodal Generation with Frozen LLMs
345. NeurIPS 2023Sparse Deep Learning for Time Series Data: Theory and Applications
346. NeurIPS 2023Sparse Parameterization for Epitomic Dataset Distillation
347. NeurIPS 2023SpecTr: Fast Speculative Decoding via Optimal Transport
348. NeurIPS 2023Statistically Valid Variable Importance Assessment through Conditional Permutations
349. NeurIPS 2023Stochastic Collapse: How Gradient Noise Attracts SGD Dynamics Towards Simpler Subnetworks
350. NeurIPS 2023Structural Pruning for Diffusion Models

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.