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

713 papers, page 14 of 15

651. NeurIPS 2023SugarCrepe: Fixing Hackable Benchmarks for Vision-Language Compositionality
652. NeurIPS 2023SwapPrompt: Test-Time Prompt Adaptation for Vision-Language Models
653. NeurIPS 2023SwiFT: Swin 4D fMRI Transformer
654. NeurIPS 2023Symbol-LLM: Leverage Language Models for Symbolic System in Visual Human Activity Reasoning
655. NeurIPS 2023TART: A plug-and-play Transformer module for task-agnostic reasoning
656. NeurIPS 2023Task Arithmetic in the Tangent Space: Improved Editing of Pre-Trained Models
657. NeurIPS 2023Temporal Dynamic Quantization for Diffusion Models
658. NeurIPS 2023Test-Time Distribution Normalization for Contrastively Learned Visual-language Models
659. NeurIPS 2023Testing the General Deductive Reasoning Capacity of Large Language Models Using OOD Examples
660. NeurIPS 2023Text Promptable Surgical Instrument Segmentation with Vision-Language Models
661. NeurIPS 2023Textually Pretrained Speech Language Models
662. NeurIPS 2023The Contextual Lasso: Sparse Linear Models via Deep Neural Networks
663. NeurIPS 2023The Emergence of Essential Sparsity in Large Pre-trained Models: The Weights that Matter
664. NeurIPS 2023The geometry of hidden representations of large transformer models
665. NeurIPS 2023The Goldilocks of Pragmatic Understanding: Fine-Tuning Strategy Matters for Implicature Resolution by LLMs
666. NeurIPS 2023The Learnability of In-Context Learning
667. NeurIPS 2023The Quantization Model of Neural Scaling
668. NeurIPS 2023The Shaped Transformer: Attention Models in the Infinite Depth-and-Width Limit
669. NeurIPS 2023Three Towers: Flexible Contrastive Learning with Pretrained Image Models
670. NeurIPS 2023To Repeat or Not To Repeat: Insights from Scaling LLM under Token-Crisis
671. NeurIPS 2023Token-Scaled Logit Distillation for Ternary Weight Generative Language Models
672. NeurIPS 2023Toolformer: Language Models Can Teach Themselves to Use Tools
673. NeurIPS 2023ToolkenGPT: Augmenting Frozen Language Models with Massive Tools via Tool Embeddings
674. NeurIPS 2023Tools for Verifying Neural Models' Training Data
675. NeurIPS 2023Top-Ambiguity Samples Matter: Understanding Why Deep Ensemble Works in Selective Classification
676. NeurIPS 2023Topological Parallax: A Geometric Specification for Deep Perception Models
677. NeurIPS 2023Towards Federated Foundation Models: Scalable Dataset Pipelines for Group-Structured Learning
678. NeurIPS 2023Towards Optimal Caching and Model Selection for Large Model Inference
679. NeurIPS 2023Towards Semi-Structured Automatic ICD Coding via Tree-based Contrastive Learning
680. NeurIPS 2023Towards Unbounded Machine Unlearning
681. NeurIPS 2023Train Faster, Perform Better: Modular Adaptive Training in Over-Parameterized Models
682. NeurIPS 2023Training Chain-of-Thought via Latent-Variable Inference
683. NeurIPS 2023Training Private Models That Know What They Don’t Know
684. NeurIPS 2023Transformer-based Planning for Symbolic Regression
685. NeurIPS 2023Transformers are uninterpretable with myopic methods: a case study with bounded Dyck grammars
686. NeurIPS 2023Tree of Thoughts: Deliberate Problem Solving with Large Language Models
687. NeurIPS 2023TrojLLM: A Black-box Trojan Prompt Attack on Large Language Models
688. NeurIPS 2023Truly Scale-Equivariant Deep Nets with Fourier Layers
689. NeurIPS 2023Two Sides of The Same Coin: Bridging Deep Equilibrium Models and Neural ODEs via Homotopy Continuation
690. NeurIPS 2023Unbiased learning of deep generative models with structured discrete representations
691. NeurIPS 2023Understanding Social Reasoning in Language Models with Language Models
692. NeurIPS 2023Unifying GANs and Score-Based Diffusion as Generative Particle Models
693. NeurIPS 2023UP-DP: Unsupervised Prompt Learning for Data Pre-Selection with Vision-Language Models
694. NeurIPS 2023Using Imperfect Surrogates for Downstream Inference: Design-based Supervised Learning for Social Science Applications of Large Language Models
695. NeurIPS 2023VanillaNet: the Power of Minimalism in Deep Learning
696. NeurIPS 2023VCC: Scaling Transformers to 128K Tokens or More by Prioritizing Important Tokens
697. NeurIPS 2023Video Prediction Models as Rewards for Reinforcement Learning
698. NeurIPS 2023VisionLLM: Large Language Model is also an Open-Ended Decoder for Vision-Centric Tasks
699. NeurIPS 2023Visual Explanations of Image-Text Representations via Multi-Modal Information Bottleneck Attribution
700. NeurIPS 2023WalkLM: A Uniform Language Model Fine-tuning Framework for Attributed Graph Embedding

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.