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 17 of 23

801. ICML 2026Rethinking LLM Ensembling from the Perspective of Mixture Models
802. ICML 2026Rethinking Personalization in Large Language Models at the Token Level
803. ICML 2026Rethinking Pretraining Data Detection for LLMs: From Local to Global
804. ICML 2026Rethinking Sparse Mixture of Experts from a Unified Perspective
805. ICML 2026Rethinking the Trust Region in LLM Reinforcement Learning
806. ICML 2026Rethinking Thinking Tokens: LLMs as Improvement Operators
807. ICML 2026Retrieval-Aware Distillation for Transformer-SSM Hybrids
808. ICML 2026Reuse your FLOPs: Scaling RL on Hard Problems by Conditioning on Very Off-Policy Prefixes
809. ICML 2026Revealing Behavioral Plasticity in Large Language Models: A Token-Conditional Perspective
810. ICML 2026Revealing Long-context Potential of Attention Heads via Frequency Kernels
811. ICML 2026REVIS: Sparse Latent Steering to Mitigate Object Hallucination in Large Vision-Language Models
812. ICML 2026Revisiting Anisotropy in Language Transformers: The Geometry of Learning Dynamics
813. ICML 2026Revisiting Efficiency–Accuracy Scaling in Mixture-of-Experts Architectures
814. ICML 2026Revisiting Parameter-Based Knowledge Editing in Large Language Models: Theoretical Limits and Empirical Evidence
815. ICML 2026Reward Auditor: Inference on Reward Modeling Suitability in Real-World Perturbed Scenarios
816. ICML 2026Reward Shaping for (Inference-Time) Alignment: A Stackelberg Game Perspective
817. ICML 2026Reward Under Attack: Analyzing the Robustness and Hackability of Process Reward Models
818. ICML 2026Reward-free Alignment for Conflicting Objectives
819. ICML 2026RLAnything: Forge Environment, Policy, and Reward Model in Completely Dynamic RL System
820. ICML 2026RLIE: Rule Generation with Logistic Regression, Iterative Refinement, and Evaluation for Large Language Models
821. ICML 2026RLVE: Scaling Up Reinforcement Learning for Language Models with Adaptive Verifiable Environments
822. ICML 2026Robust Harmful Features Under Jailbreak Attacks: Mechanistic Evidence from Attention Head Specialization in Large Language Models
823. ICML 2026RSPO: Regularized Self-Play Alignment of Large Language Models
824. ICML 2026Rubric Curriculum RL: Exploiting the Generation-Verification Gap in Non-Verifiable Domains
825. ICML 2026RubricRobustness: Evaluating the Sensitivity of Rubrics-Based Benchmarks to Simple Perturbations
826. ICML 2026Rule2DRC: Benchmarking LLM Agents for DRC Script Synthesis with Execution-Guided Test Generation
827. ICML 2026S-Quant: Rethinking Weight Quantization with Seed-Based Generation
828. ICML 2026SAC-Opt: Semantic Anchors for Iterative Correction in Optimization Modeling
829. ICML 2026SafeCompass: Dynamic Chain-of-Thought Steering via Inference-Time Safety Signals
830. ICML 2026SafeHarbor: Defining Precise Decision Boundaries via Hierarchical Memory-Augmented Guardrail for LLM Agent Safety
831. ICML 2026SafeSeek: Universal Attribution of Safety Circuits in Language Models
832. ICML 2026SafeSpec: Fast and Safe LLM via Dynamic Reflective Sampling
833. ICML 2026Safety Anchor: Defending Harmful Fine-tuning via Geometric Bottlenecks
834. ICML 2026Safety Recovery in Reasoning Models Is Only a Few Early Steering Steps Away
835. ICML 2026SAGE: Shaping Anchors for Guided Exploration in RLVR of LLMs
836. ICML 2026SALE : Low-bit Estimation for Efficient Sparse Attention in Long-context LLM Prefilling
837. ICML 2026SAME: Stabilized Mixture-of-Experts for Multimodal Continual Instruction Tuning
838. ICML 2026Sampling from Your Language Model One Byte at a Time
839. ICML 2026SARSteer: Safeguarding Large Audio Language Models via Safe-Ablated Refusal Steering
840. ICML 2026ScaleEnv: Scaling Environment Synthesis from Scratch for Generalist Interactive Tool-Use Agent Training
841. ICML 2026Scaling Beyond Masked Diffusion Language Models
842. ICML 2026Scaling Generative Verifiers For Natural Language Mathematical Proof Verification And Selection
843. ICML 2026Scaling Inference-Time Computation via Opponent Simulation: Enabling Online Strategic Adaptation in Repeated Negotiation
844. ICML 2026Scaling Law for Quantization-Aware Training
845. ICML 2026Scaling Prompt Synthesis for Large Language Model Reasoning
846. ICML 2026Scaling-Aware Adapter for Structure-Grounded LLM Reasoning
847. ICML 2026ScaLoRA: Optimally Scaled Low-Rank Adaptation for Efficient High-Rank Fine-Tuning
848. ICML 2026Scene Graph Thinking: Reinforcing Structured Visual Reasoning for Multimodal Large Language Models
849. ICML 2026Scheduling LLM Inference with Uncertainty-Aware Output Length Predictions
850. ICML 2026Scheduling Thoughts: Learning the Order of Thought in Diffusion Language 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.