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 45 of 47

2201. NeurIPS 2023PAPR: Proximity Attention Point Rendering
2202. NeurIPS 2023Parameter and Computation Efficient Transfer Learning for Vision-Language Pre-trained Models
2203. NeurIPS 2023Paraphrasing evades detectors of AI-generated text, but retrieval is an effective defense
2204. NeurIPS 2023Pareto Frontiers in Deep Feature Learning: Data, Compute, Width, and Luck
2205. NeurIPS 2023Passive learning of active causal strategies in agents and language models
2206. NeurIPS 2023Paxion: Patching Action Knowledge in Video-Language Foundation Models
2207. NeurIPS 2023Pengi: An Audio Language Model for Audio Tasks
2208. NeurIPS 2023Performance-optimized deep neural networks are evolving into worse models of inferotemporal visual cortex
2209. NeurIPS 2023PlanBench: An Extensible Benchmark for Evaluating Large Language Models on Planning and Reasoning about Change
2210. NeurIPS 2023PoET: A generative model of protein families as sequences-of-sequences
2211. NeurIPS 2023PolyDiffuse: Polygonal Shape Reconstruction via Guided Set Diffusion Models
2212. NeurIPS 2023Polyhedron Attention Module: Learning Adaptive-order Interactions
2213. NeurIPS 2023Post Hoc Explanations of Language Models Can Improve Language Models
2214. NeurIPS 2023Pre-training Contextualized World Models with In-the-wild Videos for Reinforcement Learning
2215. NeurIPS 2023Preference-grounded Token-level Guidance for Language Model Fine-tuning
2216. NeurIPS 2023Projection Regret: Reducing Background Bias for Novelty Detection via Diffusion Models
2217. NeurIPS 2023Propagating Knowledge Updates to LMs Through Distillation
2218. NeurIPS 2023ProPILE: Probing Privacy Leakage in Large Language Models
2219. NeurIPS 2023ProteinGym: Large-Scale Benchmarks for Protein Fitness Prediction and Design
2220. NeurIPS 2023QATCH: Benchmarking SQL-centric tasks with Table Representation Learning Models on Your Data
2221. NeurIPS 2023Quantification of Uncertainty with Adversarial Models
2222. NeurIPS 2023QuantSR: Accurate Low-bit Quantization for Efficient Image Super-Resolution
2223. NeurIPS 2023RADAR: Robust AI-Text Detection via Adversarial Learning
2224. NeurIPS 2023RaLEs: a Benchmark for Radiology Language Evaluations
2225. NeurIPS 2023Random-Access Infinite Context Length for Transformers
2226. NeurIPS 2023RealTime QA: What's the Answer Right Now?
2227. NeurIPS 2023REFINE: A Fine-Grained Medication Recommendation System Using Deep Learning and Personalized Drug Interaction Modeling
2228. NeurIPS 2023Regularizing Neural Networks with Meta-Learning Generative Models
2229. NeurIPS 2023RenderMe-360: A Large Digital Asset Library and Benchmarks Towards High-fidelity Head Avatars
2230. NeurIPS 2023Reproducibility in Multiple Instance Learning: A Case For Algorithmic Unit Tests
2231. NeurIPS 2023Reproducibility study of the Fairness-enhanced Node Representation Learning
2232. NeurIPS 2023ResMem: Learn what you can and memorize the rest
2233. NeurIPS 2023Response Length Perception and Sequence Scheduling: An LLM-Empowered LLM Inference Pipeline
2234. NeurIPS 2023Rethinking Gauss-Newton for learning over-parameterized models
2235. NeurIPS 2023Revisit the Power of Vanilla Knowledge Distillation: from Small Scale to Large Scale
2236. NeurIPS 2023Revisiting Adversarial Training for ImageNet: Architectures, Training and Generalization across Threat Models
2237. NeurIPS 2023REx: Data-Free Residual Quantization Error Expansion
2238. NeurIPS 2023RoboCLIP: One Demonstration is Enough to Learn Robot Policies
2239. NeurIPS 2023Robust Learning with Progressive Data Expansion Against Spurious Correlation
2240. NeurIPS 2023RRHF: Rank Responses to Align Language Models with Human Feedback
2241. NeurIPS 2023S-CLIP: Semi-supervised Vision-Language Learning using Few Specialist Captions
2242. NeurIPS 2023SatLM: Satisfiability-Aided Language Models Using Declarative Prompting
2243. NeurIPS 2023Scale Alone Does not Improve Mechanistic Interpretability in Vision Models
2244. NeurIPS 2023Scaling Laws for Hyperparameter Optimization
2245. NeurIPS 2023Scaling laws for language encoding models in fMRI
2246. NeurIPS 2023Scaling MLPs: A Tale of Inductive Bias
2247. NeurIPS 2023Scaling Riemannian Diffusion Models
2248. NeurIPS 2023Schema-learning and rebinding as mechanisms of in-context learning and emergence
2249. NeurIPS 2023Scientific Document Retrieval using Multi-level Aspect-based Queries
2250. NeurIPS 2023Scissorhands: Exploiting the Persistence of Importance Hypothesis for LLM KV Cache Compression at Test Time

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.