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

1,608 papers, page 20 of 33

951. ICML 2026TarGATE: Target-Aware Data Selection via Token-Attenuation Gates
952. ICML 2026Target-Oriented Pretraining Data Selection via Neuron-Activated Graph
953. ICML 2026Task-and-Model-Aware Fractal-Consistency for Efficient LLM Reasoning
954. ICML 2026Task-Aware Preference Calibration for Direct Preference Optimization
955. ICML 2026Task-Awareness Improves LLM Generations and Uncertainty
956. ICML 2026TCAP: Tri-Component Attention Profiling for Unsupervised Backdoor Detection in MLLM Fine-Tuning
957. ICML 2026Teaching Models to Teach Themselves: Reasoning at the Edge of Learnability
958. ICML 2026TEAM: Temporal–Spatial Consistency Guided Expert Activation for MoE Diffusion Language Model Acceleration
959. ICML 2026TeamTR: Trust-Region Fine-Tuning for Multi-Agent LLM Coordination
960. ICML 2026Temporal Self-Rewarding Language Models: Decoupling Chosen-Rejected via Past-Future
961. ICML 2026Test-Time Detoxification without Training or Learning Anything
962. ICML 2026Text Generation as Continuous Latent Dynamics via Reinforcement Learning
963. ICML 2026TextResNet: Decoupling and Routing Optimization Signals in Compound AI Systems via Deep Residual Tuning
964. ICML 2026Textual Stochastic Gradient Descent: Discrete Optimization of External Memory for Reasoning Language Agents
965. ICML 2026TGPO: Efficient Policy Optimization through Sequence Anchor and Information Gating
966. ICML 2026The Appeal and Reality of Recycling LoRAs with Adaptive Merging
967. ICML 2026The Art of Interrogation: Consistency Amplifies Factuality in Spatial Reasoning
968. ICML 2026The Bridge-Garden Dilemma in LLM Distillation: Why Mixing Hard and Soft Labels Works
969. ICML 2026The Convergent Representation of Contrastive Vision-Language Models: Geometry, Modality Gap and Shared Space Alignment
970. ICML 2026The Cylindrical Representation Hypothesis for Language Model Steering
971. ICML 2026The Devil is in the Spectrum: Mitigating Representation Collapse in LLMs via Topologically Regularized Side-Path
972. ICML 2026The Differences Between Direct Alignment Algorithms are a Blur
973. ICML 2026The Easy, the Hard, and the Learnable: Confidence and Difficulty-Adaptive Policy Optimization for LLM Reasoning
974. ICML 2026The Flexibility Trap: Rethinking the Value of Arbitrary Order in Diffusion Language Models
975. ICML 2026The Geometric Reasoner: Manifold-Informed Latent Foresight Search for Long-Context Reasoning
976. ICML 2026The Geometry of Narrow Fine-Tuning Degradation: Trajectory Lock-in and Spectral Bifurcation
977. ICML 2026The Geometry of Reasoning: Self-Evaluation via Layerwise Trajectory Evolution
978. ICML 2026The Hidden Cost of Structured Generation in LLMs: Draft-Conditioned Constrained Decoding
979. ICML 2026The Invisible Lottery: How Subtle Cues Steer Algorithm Choice in LLM Code Generation
980. ICML 2026The Labyrinth and the Thread: Rethinking Regularizations in Sequential Knowledge Editing for Large Language Models
981. ICML 2026The Optimal Token Baseline: Variance Reduction for Long-Horizon LLM-RL
982. ICML 2026The Perceptual Bandwidth Bottleneck in Vision-Language Models: Active Visual Reasoning via Sequential Experimental Design
983. ICML 2026The Quality-Utility Paradox: Why High-Reward Data Impairs Small Model Mathematical Reasoning
984. ICML 2026The Shadow Price of Reasoning: Economic Perspective on Optimal Budget Allocation for LLMs
985. ICML 2026The Shape of Addition: Geometric Structures of Arithmetic in Large Language Models
986. ICML 2026The Structural Origin of Attention Sink: Variance Discrepancy, Super Neurons, and Dimension Disparity
987. ICML 2026The Tell-Tale Norm: $\ell_2$ Magnitude as a Signal for Reasoning Dynamics in Large Language Models
988. ICML 2026The Truth Stays in the Family: Enhancing Contextual Truthfulness via Inherited Heads in Model Lineages
989. ICML 2026The Unlearnability Phenomenon in RLVR for Language Models
990. ICML 2026ThetaEvolve: Test-time Learning on Open Problems
991. ICML 2026Think Deep, Not Just Long: Measuring LLM Reasoning Effort via Deep-Thinking Tokens
992. ICML 2026Think in Latent, Explain in Language: Self-Explainable Latent Reasoning
993. ICML 2026Think-at-Hard: Selective Latent Iterations to Improve Reasoning Language Models
994. ICML 2026Thinking with Geometry: Active Geometry Integration for Spatial Reasoning
995. ICML 2026ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning
996. ICML 2026ThreadWeaver: Adaptive Threading for Efficient Parallel Reasoning in Language Models
997. ICML 2026Threshold-Based Exclusive Batching for LLM Inference
998. ICML 2026ThunderAgent: A Fast, Simple, and Program-Aware Agentic Inference System
999. ICML 2026TileQ: Efficient Low-Rank Quantization of Mixture-of-Experts with 2D Tiling
1000. ICML 2026TIME: Tensor-Factorized Mixture-of-Experts with Intrinsic Routing for Lifelong Multimodal Knowledge Editing

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.