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

1,131 papers, page 8 of 23

351. ICML 2026Fast and Accurate Causal Parallel Decoding using Jacobi Forcing
352. ICML 2026Fast Byte Latent Transformer
353. ICML 2026Fast KV Compaction via Attention Matching
354. ICML 2026Feature-Aware (Hyper)graph Generation via Next-Scale Prediction
355. ICML 2026Federated Sketching LoRA: A Flexible Framework for Heterogeneous Collaborative Fine-Tuning of LLMs
356. ICML 2026Federated Variational Preference Alignment with Gumbel-Softmax Prior for Personalized User Preferences
357. ICML 2026FedPissa: Towards Federated Personalized Adaptation of Foundation Models via LoRA Subspace Mapping
358. ICML 2026FedRot-LoRA: Mitigating Rotational Misalignment in Federated LoRA
359. ICML 2026FedSDR: Federated Self-Distillation with Rectification
360. ICML 2026FlexRank: Nested Low-Rank Knowledge Decomposition for Adaptive Model Deployment
361. ICML 2026Float8@2bits: Entropy Coding Enables Data-Free Model Compression
362. ICML 2026FlowBot: Inducing LLM Workflows with Bilevel Optimization and Textual Gradients
363. ICML 2026FOAM: Blocked State Folding for Memory-Efficient LLM Training
364. ICML 2026FOCA: Future-Oriented Conditioning for Data-Efficient Vision-Language-Action Adaptation
365. ICML 2026FOCUS & RePAIR: Mitigating Text Degeneration via Token-Level Guidance For Pruned Large Language Models
366. ICML 2026FOCUS: DLLMs Know How to Tame Their Compute Bound
367. ICML 2026FormulaCode: Evaluating Agentic Optimization on Large Codebases
368. ICML 2026FPTQuant: Function-Preserving Transforms for LLM Quantization
369. ICML 2026From Absolute to Relative: Rethinking Reward Shaping in Group-Based Reinforcement Learning
370. ICML 2026From Backward Spreading to Forward Replay: Revisiting Target Construction in LLM Parameter Editing
371. ICML 2026From Bits to Rounds: Parallel Decoding with Exploration for Diffusion Language Models
372. ICML 2026From Drift to Coherence: Stabilizing Beliefs in LLMs
373. ICML 2026From Extraction to Deduction: Resolving Functional Misalignment in RAG via a Collaborative Critic-Reasoner Framework
374. ICML 2026From Flat Facts to Sharp Hallucinations: Detecting Stubborn Errors via Gradient Sensitivity
375. ICML 2026From Growing to Looping: A Unified View of Iterative Computation in LLMs
376. ICML 2026From Historical Patches to Repair Plans: Outcome-Conditioned Reasoning for Repository-Level Program Repair
377. ICML 2026From Interactions to Principles: Experience-Driven Self-Distillation for Evolving LLM Agents
378. ICML 2026From LLM-Generated Conjectures to Lean Formalizations: Automated Polynomial Inequality Proving via Sum-of-Squares Certificates
379. ICML 2026From Out-of-Distribution Detection to Hallucination Detection: A Geometric View
380. ICML 2026From Outcomes to Actions: Leveraging Hindsight for Long-Horizon Language Agent Training
381. ICML 2026From Parameters to Data: A Task-Parameter-Guided Fine-Tuning Pipeline for Efficient LLM Alignment
382. ICML 2026From Player to Master: Enhancing Test-Time Learning of LLM Agents via Reinforcement Learning over Memory
383. ICML 2026From Prompts to Responses: Dual-Sided Data Leakage and Defense in Split Large Language Models
384. ICML 2026From Prompts to Tokens: Internalizing Causal Supervision in Vision-Language Model for Multi-Image Causal Reasoning
385. ICML 2026From Reasoning Traces to Reusable Modules: Understanding Compositional Generalization in Language Model Reasoning
386. ICML 2026From Retrieval to Translation: Translating Query into Graph-level Clues for Retrieval-Augmented Generation
387. ICML 2026From Winning to Understanding: A Diagnostic Long-Horizon RTS Benchmark for LLMs
388. ICML 2026FrontierCS: Evolving Challenges for Evolving Intelligence
389. ICML 2026Future-Gain Guided Test-Time Learning for Large Language Models
390. ICML 2026FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs
391. ICML 2026G$^2$RPO: Geometric GRPO; Escaping LLM's Reasoning Rut to Break Accuracy--Entropy Trade-off
392. ICML 2026GAM-RAG: Gain-Adaptive Memory for Evolving Retrieval in Retrieval-Augmented Generation
393. ICML 2026GDPO: Group reward-Decoupled Normalization Policy Optimization for Multi-reward RL Optimization
394. ICML 2026GEM: Geometric Entropy Mixing for Optimal LLM Data Curation
395. ICML 2026GEMQ: Global Expert-Level Mixed-Precision Quantization for MoE LLMs
396. ICML 2026Generalized Correctness Models: Learning Calibrated and Cross-Model Correctness Predictors from Historical Patterns
397. ICML 2026GeoAlign: Geometric Rollout Curation for Robust LLM Reinforcement Learning
398. ICML 2026Geometry-Aware Decoding with Wasserstein-Regularized Truncation and Mass Penalties for Large Language Models
399. ICML 2026GLARE: Scalable Neuro-Symbolic Reward Shaping for LLM Agents via Group-Level Automata
400. ICML 2026Golden Goose: A Simple Trick to Synthesize Unlimited RLVR Tasks from Unverifiable Internet Text

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.