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 12 of 15

551. NeurIPS 2023M3Exam: A Multilingual, Multimodal, Multilevel Benchmark for Examining Large Language Models
552. NeurIPS 2023MADLAD-400: A Multilingual And Document-Level Large Audited Dataset
553. NeurIPS 2023Make Pre-trained Model Reversible: From Parameter to Memory Efficient Fine-Tuning
554. NeurIPS 2023Making Scalable Meta Learning Practical
555. NeurIPS 2023MarioGPT: Open-Ended Text2Level Generation through Large Language Models
556. NeurIPS 2023Meet in the Middle: A New Pre-training Paradigm
557. NeurIPS 2023Memory-Efficient Fine-Tuning of Compressed Large Language Models via sub-4-bit Integer Quantization
558. NeurIPS 2023Meta-AdaM: An Meta-Learned Adaptive Optimizer with Momentum for Few-Shot Learning
559. NeurIPS 2023Mitigating Test-Time Bias for Fair Image Retrieval
560. NeurIPS 2023Mnemosyne: Learning to Train Transformers with Transformers
561. NeurIPS 2023Model Spider: Learning to Rank Pre-Trained Models Efficiently
562. NeurIPS 2023Modelling Cellular Perturbations with the Sparse Additive Mechanism Shift Variational Autoencoder
563. NeurIPS 2023Monarch Mixer: A Simple Sub-Quadratic GEMM-Based Architecture
564. NeurIPS 2023MotionGPT: Human Motion as a Foreign Language
565. NeurIPS 2023Natural Language Instruction-following with Task-related Language Development and Translation
566. NeurIPS 2023Neural Combinatorial Optimization with Heavy Decoder: Toward Large Scale Generalization
567. NeurIPS 2023Neural Sampling in Hierarchical Exponential-family Energy-based Models
568. NeurIPS 2023Neuro-symbolic Learning Yielding Logical Constraints
569. NeurIPS 2023Non-Rigid Shape Registration via Deep Functional Maps Prior
570. NeurIPS 2023On Learning Latent Models with Multi-Instance Weak Supervision
571. NeurIPS 2023On the Exploitability of Instruction Tuning
572. NeurIPS 2023On the Planning Abilities of Large Language Models - A Critical Investigation
573. NeurIPS 2023On-the-Fly Adapting Code Summarization on Trainable Cost-Effective Language Models
574. NeurIPS 2023One Fits All: Power General Time Series Analysis by Pretrained LM
575. NeurIPS 2023One-Step Diffusion Distillation via Deep Equilibrium Models
576. NeurIPS 2023OpenAGI: When LLM Meets Domain Experts
577. NeurIPS 2023OpenAssistant Conversations - Democratizing Large Language Model Alignment
578. NeurIPS 2023Order Matters in the Presence of Dataset Imbalance for Multilingual Learning
579. NeurIPS 2023Pairwise Causality Guided Transformers for Event Sequences
580. NeurIPS 2023PAPR: Proximity Attention Point Rendering
581. NeurIPS 2023Parameter and Computation Efficient Transfer Learning for Vision-Language Pre-trained Models
582. NeurIPS 2023Paraphrasing evades detectors of AI-generated text, but retrieval is an effective defense
583. NeurIPS 2023Pareto Frontiers in Deep Feature Learning: Data, Compute, Width, and Luck
584. NeurIPS 2023Passive learning of active causal strategies in agents and language models
585. NeurIPS 2023Paxion: Patching Action Knowledge in Video-Language Foundation Models
586. NeurIPS 2023Pengi: An Audio Language Model for Audio Tasks
587. NeurIPS 2023Performance-optimized deep neural networks are evolving into worse models of inferotemporal visual cortex
588. NeurIPS 2023PlanBench: An Extensible Benchmark for Evaluating Large Language Models on Planning and Reasoning about Change
589. NeurIPS 2023PoET: A generative model of protein families as sequences-of-sequences
590. NeurIPS 2023PolyDiffuse: Polygonal Shape Reconstruction via Guided Set Diffusion Models
591. NeurIPS 2023Polyhedron Attention Module: Learning Adaptive-order Interactions
592. NeurIPS 2023Post Hoc Explanations of Language Models Can Improve Language Models
593. NeurIPS 2023Pre-training Contextualized World Models with In-the-wild Videos for Reinforcement Learning
594. NeurIPS 2023Preference-grounded Token-level Guidance for Language Model Fine-tuning
595. NeurIPS 2023Projection Regret: Reducing Background Bias for Novelty Detection via Diffusion Models
596. NeurIPS 2023Propagating Knowledge Updates to LMs Through Distillation
597. NeurIPS 2023ProPILE: Probing Privacy Leakage in Large Language Models
598. NeurIPS 2023ProteinGym: Large-Scale Benchmarks for Protein Fitness Prediction and Design
599. NeurIPS 2023QATCH: Benchmarking SQL-centric tasks with Table Representation Learning Models on Your Data
600. NeurIPS 2023Quantification of Uncertainty with Adversarial Models

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.