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

1,608 papers, page 4 of 33

151. ICML 2026Causal Dependency-Aware Unsupervised Routing for Large Reasoning Models
152. ICML 2026Causal Direct Preference Optimization for Distributionally Robust Generative Recommendation
153. ICML 2026CausalGame: Benchmarking Causal Thinking of LLM Agents in Games
154. ICML 2026Causally Evaluating the Learnability of Formal Language Tasks
155. ICML 2026CausalRAG2: Hierarchical Causal Knowledge Graph Design for RAG
156. ICML 2026CauSciBench: Can LLMs Automate Causal Inference in Real-World Scientific Research?
157. ICML 2026Certain Head, Uncertain Tail: Expert-Sample for Test-Time Scaling in Fine-Grained MoE
158. ICML 2026CGSVD: Cascaded Granular Singular Value Decomposition for Large Language Model Compression
159. ICML 2026Characterizing, Evaluating, and Optimizing Complex Reasoning
160. ICML 2026Chiral Symmetry Breaking in Transformers: A Group-Equivariant Framework for Addressing the Reversal Curse via Adjoint Manifold Mappings
161. ICML 2026Circle-RoPE: Cone-like Decoupled Rotary Positional Embedding for Vision-Language Models
162. ICML 2026CircuitPrint: Mechanistic Circuit Fingerprints for Large Language Models
163. ICML 2026CLAA: Cross-Layer Attention Aggregation for Accelerating LLM Prefill
164. ICML 2026Clarify Before You Draw: Proactive Agents for Robust Text-to-CAD Generation
165. ICML 2026CLIMB: Taming the LoRA Residency Cliff in Multi-LoRA Serving
166. ICML 2026Clipping Bottleneck: Stabilizing RLVR via Stochastic Recovery of Near-Boundary Signals
167. ICML 2026CoDA-Bench: Can Code Agents Handle Data-Intensive Tasks?
168. ICML 2026CodeChemist: Test-Time Scaling for Low-Resource Code Generation via Functional Knowledge Transfer
169. ICML 2026Coevolutionary Continuous Discrete Diffusion: Make Your Diffusion Language Model a Latent Reasoner
170. ICML 2026CofactGVR: Counterfactual Intervention for Grounded Visual Reasoning
171. ICML 2026Cognitive Fatigue in Autoregressive Transformers: Formalization and Measurement
172. ICML 2026CoMem: Context Management with A Decoupled Long-Context Model
173. ICML 2026Compile to Compress: Boosting Formal Theorem Provers by Compiler Outputs
174. ICML 2026ComplexMCP: Evaluation of LLM Agents in Dynamic, Interdependent, and Large-Scale Tool Sandbox
175. ICML 2026Compress then Merge: From Multiple LoRAs into One Low-Rank Adapter
176. ICML 2026Computational Arbitrage in AI Model Markets
177. ICML 2026Compute as Teacher: Turning Inference Compute Into Reference-Free Supervision
178. ICML 2026Compute Where it Counts: Self Optimizing Language Models
179. ICML 2026Concept Heterogeneity-aware Representation Steering
180. ICML 2026Confidence is Not Universal: Task-Dependent Calibration and Emergent Behavior in LLMs
181. ICML 2026Configurable Reward Model for Balanced Safety Alignment
182. ICML 2026Conformal Thinking: Risk Control for Reasoning on a Compute Budget
183. ICML 2026ConFu: Contemplate the Future for Better Speculative Sampling
184. ICML 2026ConPress: Learning Efficient Reasoning from Multi-Question Contextual Pressure
185. ICML 2026ConServe: Fine-Grained GPU Harvesting for LLM Online and Offline Co-Serving
186. ICML 2026Context Tuning for In-Context Optimization
187. ICML 2026Context-level Language Modeling by Learning Predictive Context Embeddings
188. ICML 2026Contextual Rollout Bandits for Reinforcement Learning with Verifiable Rewards
189. ICML 2026Contextualized Privacy Defense for LLM Agents
190. ICML 2026Continuous Diffusion Models Can Obey Formal Syntax
191. ICML 2026Contrastive Weak-to-Strong Generalization
192. ICML 2026Convex Dataset Valuation for Post-Training
193. ICML 2026Convex Optimization for Alignment and Preference Learning on a Single GPU
194. ICML 2026ConvexBench: Can LLMs Recognize Convex Functions?
195. ICML 2026CoPE: A Framework for Optimizing Coordination between Planning and Execution in LLM-based Agents
196. ICML 2026CoPE: Continual Probe-guided Expansion for Large Vision-Language Models
197. ICML 2026CORE: Context-Robust Remasking for Diffusion Language Models
198. ICML 2026CORRECT: COndensed eRror RECognition via knowledge Transfer in multi-agent systems
199. ICML 2026Correcting in Hindsight: Editing Past Key-Value States for Robust LLM Reasoning
200. ICML 2026Correcting Visual Blur Induced by Attention Distraction to Reduce Hallucinations: Algorithm and Theory

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.