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 33 of 47

1601. NeurIPS 2024Compact Language Models via Pruning and Knowledge Distillation
1602. NeurIPS 2024Concentrate Attention: Towards Domain-Generalizable Prompt Optimization for Language Models
1603. NeurIPS 2024Connecting the Dots: LLMs can Infer and Verbalize Latent Structure from Disparate Training Data
1604. NeurIPS 2024ConStat: Performance-Based Contamination Detection in Large Language Models
1605. NeurIPS 2024ContextCite: Attributing Model Generation to Context
1606. NeurIPS 2024CorDA: Context-Oriented Decomposition Adaptation of Large Language Models for Task-Aware Parameter-Efficient Fine-tuning
1607. NeurIPS 2024Cost-efficient Knowledge-based Question Answering with Large Language Models
1608. NeurIPS 2024Cracking the Code of Juxtaposition: Can AI Models Understand the Humorous Contradictions
1609. NeurIPS 2024CriticEval: Evaluating Large-scale Language Model as Critic
1610. NeurIPS 2024Cross-model Control: Improving Multiple Large Language Models in One-time Training
1611. NeurIPS 2024D-CPT Law: Domain-specific Continual Pre-Training Scaling Law for Large Language Models
1612. NeurIPS 2024D-LLM: A Token Adaptive Computing Resource Allocation Strategy for Large Language Models
1613. NeurIPS 2024DAPE: Data-Adaptive Positional Encoding for Length Extrapolation
1614. NeurIPS 2024DART-Math: Difficulty-Aware Rejection Tuning for Mathematical Problem-Solving
1615. NeurIPS 2024Data Mixture Inference Attack: BPE Tokenizers Reveal Training Data Compositions
1616. NeurIPS 2024Dataset Decomposition: Faster LLM Training with Variable Sequence Length Curriculum
1617. NeurIPS 2024DDK: Distilling Domain Knowledge for Efficient Large Language Models
1618. NeurIPS 2024Decoding-Time Language Model Alignment with Multiple Objectives
1619. NeurIPS 2024Decompose, Analyze and Rethink: Solving Intricate Problems with Human-like Reasoning Cycle
1620. NeurIPS 2024Deep Bayesian Active Learning for Preference Modeling in Large Language Models
1621. NeurIPS 2024Delta-CoMe: Training-Free Delta-Compression with Mixed-Precision for Large Language Models
1622. NeurIPS 2024Delving into the Reversal Curse: How Far Can Large Language Models Generalize?
1623. NeurIPS 2024DeTeCtive: Detecting AI-generated Text via Multi-Level Contrastive Learning
1624. NeurIPS 2024DeTikZify: Synthesizing Graphics Programs for Scientific Figures and Sketches with TikZ
1625. NeurIPS 2024DHA: Learning Decoupled-Head Attention from Transformer Checkpoints via Adaptive Heads Fusion
1626. NeurIPS 2024DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning
1627. NeurIPS 2024Discovering Preference Optimization Algorithms with and for Large Language Models
1628. NeurIPS 2024Discovering Sparsity Allocation for Layer-wise Pruning of Large Language Models
1629. NeurIPS 2024Divide-and-Conquer Meets Consensus: Unleashing the Power of Functions in Code Generation
1630. NeurIPS 2024Do LLMs Build World Representations? Probing Through the Lens of State Abstraction
1631. NeurIPS 2024DropBP: Accelerating Fine-Tuning of Large Language Models by Dropping Backward Propagation
1632. NeurIPS 2024DuQuant: Distributing Outliers via Dual Transformation Makes Stronger Quantized LLMs
1633. NeurIPS 2024EAI: Emotional Decision-Making of LLMs in Strategic Games and Ethical Dilemmas
1634. NeurIPS 2024Easy-to-Hard Generalization: Scalable Alignment Beyond Human Supervision
1635. NeurIPS 2024Efficient Adversarial Training in LLMs with Continuous Attacks
1636. NeurIPS 2024Efficient Minimum Bayes Risk Decoding using Low-Rank Matrix Completion Algorithms
1637. NeurIPS 2024EffiLearner: Enhancing Efficiency of Generated Code via Self-Optimization
1638. NeurIPS 2024Embedding Trajectory for Out-of-Distribution Detection in Mathematical Reasoning
1639. NeurIPS 2024End-To-End Causal Effect Estimation from Unstructured Natural Language Data
1640. NeurIPS 2024Enhancing In-Context Learning Performance with just SVD-Based Weight Pruning: A Theoretical Perspective
1641. NeurIPS 2024Enhancing Large Language Models through Adaptive Tokenizers
1642. NeurIPS 2024Enhancing Large Vision Language Models with Self-Training on Image Comprehension
1643. NeurIPS 2024Enhancing LLM’s Cognition via Structurization
1644. NeurIPS 2024Enhancing Multiple Dimensions of Trustworthiness in LLMs via Sparse Activation Control
1645. NeurIPS 2024Enhancing Reasoning Capabilities of LLMs via Principled Synthetic Logic Corpus
1646. NeurIPS 2024Ensemble Learning for Heterogeneous Large Language Models with Deep Parallel Collaboration
1647. NeurIPS 2024Entity Alignment with Noisy Annotations from Large Language Models
1648. NeurIPS 2024Explaining Datasets in Words: Statistical Models with Natural Language Parameters
1649. NeurIPS 2024Exploring Context Window of Large Language Models via Decomposed Positional Vectors
1650. NeurIPS 2024FASTopic: Pretrained Transformer is a Fast, Adaptive, Stable, and Transferable Topic Model

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.