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 23 of 33

1101. ICML 2026What LLMs Explain Is Not What They Believe: Evaluating Explanation Sufficiency Under Models' Own Input Beliefs
1102. ICML 2026What Makes Effective Supervision in Latent Chain-of-Thought: An Information-Theoretic Analysis
1103. ICML 2026What Really Improves Mathematical Reasoning: Structured Reasoning Signals Beyond Pure Code
1104. ICML 2026When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems
1105. ICML 2026When Diffusion Language Models Hesitate: Detecting and Correcting Visual Hallucinations via Confidence Fluctuation
1106. ICML 2026When Distance Distracts: Representation Distance Bias in BT-Loss for Reward Models
1107. ICML 2026When Do Hallucinations Arise? A Graph Perspective on the Evolution of Path Reuse and Path Compression
1108. ICML 2026When Does Sparsity Mitigate the Curse of Depth in LLMs
1109. ICML 2026When Drafts Evolve: Speculative Decoding Meets Online Learning
1110. ICML 2026When Labelers Stay Silent: The Power of Ties in Cost-Effective Preference Learning
1111. ICML 2026When LLMs Encounter Open-world Graph Learning: A Fresh View on Unlabeled Data Uncertainty
1112. ICML 2026When Model Merging Breaks Routing: Training-Free Calibration for MoE
1113. ICML 2026When RAG Hurts: Diagnosing and Mitigating Attention Distraction in Retrieval-Augmented LVLMs
1114. ICML 2026When RL Meets Adaptive Speculative Training: A Unified Training-Serving System
1115. ICML 2026When Search Goes Wrong: Red-Teaming Web-Augmented Large Language Models
1116. ICML 2026When Simple Problems Wear Complex Costumes: Improving Efficiency in LRM's Adaptive Reasoning
1117. ICML 2026When to Think, When to Speak: Learning Disclosure Policies for LLM Reasoning
1118. ICML 2026Which Heads Matter for Reasoning? RL-Guided KV Cache Compression
1119. ICML 2026Who can we trust? LLM-as-a-jury for Comparative Assessment
1120. ICML 2026Why Deep Jacobian Spectra Separate: Depth-Induced Scaling and Singular-Vector Alignment
1121. ICML 2026WinDeskGround: A Benchmark for Robust GUI Grounding in Complex Multi-Window Desktop Environments
1122. ICML 2026WinQ: Accelerating Quantization-Aware Training of Language Models Around Saddle Points
1123. ICML 2026Words & Weights: Streamlining Multi-Turn Interactions via Co-Adaptation
1124. ICML 2026WorldTravel: A Realistic Multimodal Travel-Planning Benchmark with Tightly Coupled Constraints
1125. ICML 2026WUSH: Near-Optimal Adaptive Transforms for LLM Quantization
1126. ICML 2026xKV: Cross-Layer KV-Cache Compression via Aligned Singular Vector Extraction
1127. ICML 2026XSkill: Continual Learning from Experience and Skills in Multimodal Agents
1128. ICML 2026XSpecMesh: Quality-Preserving Auto-Regressive Mesh Generation Acceleration via Multi-Head Speculative Decoding
1129. ICML 2026You Can Learn Tokenization End-to-End with Reinforcement Learning
1130. ICML 2026Zero Sum SVD: Balancing Loss Sensitivity for Low Rank LLM Compression
1131. ICML 2026ZipMoE: Efficient On-Device MoE Serving via Lossless Compression and Cache-Affinity Scheduling
1132. ICML 2025(How) Do Language Models Track State?
1133. ICML 2025A Hitchhiker's Guide to Scaling Law Estimation
1134. ICML 2025A Tale of Two Structures: Do LLMs Capture the Fractal Complexity of Language?
1135. ICML 2025A Unified Approach to Routing and Cascading for LLMs
1136. ICML 2025Accelerating Large Language Model Reasoning via Speculative Search
1137. ICML 2025Accelerating LLM Inference with Lossless Speculative Decoding Algorithms for Heterogeneous Vocabularies
1138. ICML 2025Accelerating Unbiased LLM Evaluation via Synthetic Feedback
1139. ICML 2025Active Reward Modeling: Adaptive Preference Labeling for Large Language Model Alignment
1140. ICML 2025AdaDecode: Accelerating LLM Decoding with Adaptive Layer Parallelism
1141. ICML 2025Adapting While Learning: Grounding LLMs for Scientific Problems with Tool Usage Adaptation
1142. ICML 2025Adaptive Localization of Knowledge Negation for Continual LLM Unlearning
1143. ICML 2025AdaptiveStep: Automatically Dividing Reasoning Step through Model Confidence
1144. ICML 2025Aligning LLMs by Predicting Preferences from User Writing Samples
1145. ICML 2025Aligning with Logic: Measuring, Evaluating and Improving Logical Preference Consistency in Large Language Models
1146. ICML 2025AlphaDPO: Adaptive Reward Margin for Direct Preference Optimization
1147. ICML 2025AlphaPO: Reward Shape Matters for LLM Alignment
1148. ICML 2025AlphaVerus: Bootstrapping Formally Verified Code Generation through Self-Improving Translation and Treefinement
1149. ICML 2025AMPO: Active Multi Preference Optimization for Self-play Preference Selection
1150. ICML 2025An Analysis for Reasoning Bias of Language Models with Small Initialization

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.