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

417 papers, page 3 of 9

101. ICML 2025Do NOT Think That Much for 2+3=? On the Overthinking of Long Reasoning Models
102. ICML 2025DocKS-RAG: Optimizing Document-Level Relation Extraction through LLM-Enhanced Hybrid Prompt Tuning
103. ICML 2025Domain2Vec: Vectorizing Datasets to Find the Optimal Data Mixture without Training
104. ICML 2025DPO Meets PPO: Reinforced Token Optimization for RLHF
105. ICML 2025DS-VLM: Diffusion Supervision Vision Language Model
106. ICML 2025DyCodeEval: Dynamic Benchmarking of Reasoning Capabilities in Code Large Language Models Under Data Contamination
107. ICML 2025Earley-Driven Dynamic Pruning for Efficient Structured Decoding
108. ICML 2025Efficient Long Context Fine-tuning with Chunk Flow
109. ICML 2025EffiCoder: Enhancing Code Generation in Large Language Models through Efficiency-Aware Fine-tuning
110. ICML 2025Eliciting Language Model Behaviors with Investigator Agents
111. ICML 2025EmbodiedBench: Comprehensive Benchmarking Multi-modal Large Language Models for Vision-Driven Embodied Agents
112. ICML 2025Emergence and Effectiveness of Task Vectors in In-Context Learning: An Encoder Decoder Perspective
113. ICML 2025Emergent Misalignment: Narrow finetuning can produce broadly misaligned LLMs
114. ICML 2025Emergent Response Planning in LLMs
115. ICML 2025Emergent Symbolic Mechanisms Support Abstract Reasoning in Large Language Models
116. ICML 2025Energy-Based Preference Model Offers Better Offline Alignment than the Bradley-Terry Preference Model
117. ICML 2025Enhancing Decision-Making of Large Language Models via Actor-Critic
118. ICML 2025EpiCoder: Encompassing Diversity and Complexity in Code Generation
119. ICML 2025Evaluating Judges as Evaluators: The JETTS Benchmark of LLM-as-Judges as Test-Time Scaling Evaluators
120. ICML 2025Evaluating LLMs Across Multi-Cognitive Levels: From Medical Knowledge Mastery to Scenario-Based Problem Solving
121. ICML 2025Everything Everywhere All at Once: LLMs can In-Context Learn Multiple Tasks in Superposition
122. ICML 2025EVOLvE: Evaluating and Optimizing LLMs For In-Context Exploration
123. ICML 2025Evolving Prompts In-Context: An Open-ended, Self-replicating Perspective
124. ICML 2025EvoPress: Accurate Dynamic Model Compression via Evolutionary Search
125. ICML 2025Explicit Preference Optimization: No Need for an Implicit Reward Model
126. ICML 2025Exploiting Presentative Feature Distributions for Parameter-Efficient Continual Learning of Large Language Models
127. ICML 2025FactTest: Factuality Testing in Large Language Models with Finite-Sample and Distribution-Free Guarantees
128. ICML 2025Fast Large Language Model Collaborative Decoding via Speculation
129. ICML 2025Federated In-Context Learning: Iterative Refinement for Improved Answer Quality
130. ICML 2025FedPHA: Federated Prompt Learning for Heterogeneous Client Adaptation
131. ICML 2025Ferret: Federated Full-Parameter Tuning at Scale for Large Language Models
132. ICML 2025FlatQuant: Flatness Matters for LLM Quantization
133. ICML 2025FlipAttack: Jailbreak LLMs via Flipping
134. ICML 2025FloE: On-the-Fly MoE Inference on Memory-constrained GPU
135. ICML 2025Flow-of-Options: Diversified and Improved LLM Reasoning by Thinking Through Options
136. ICML 2025Focus On This, Not That! Steering LLMs with Adaptive Feature Specification
137. ICML 2025Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning
138. ICML 2025Fourier Position Embedding: Enhancing Attention’s Periodic Extension for Length Generalization
139. ICML 2025Fragments to Facts: Partial-Information Fragment Inference from LLMs
140. ICML 2025Free Process Rewards without Process Labels
141. ICML 2025From Debate to Equilibrium: Belief‑Driven Multi‑Agent LLM Reasoning via Bayesian Nash Equilibrium
142. ICML 2025From Language Models over Tokens to Language Models over Characters
143. ICML 2025From Passive to Active Reasoning: Can Large Language Models Ask the Right Questions under Incomplete Information?
144. ICML 2025From RAG to Memory: Non-Parametric Continual Learning for Large Language Models
145. ICML 2025FunBO: Discovering Acquisition Functions for Bayesian Optimization with FunSearch
146. ICML 2025Function-to-Style Guidance of LLMs for Code Translation
147. ICML 2025GANQ: GPU-Adaptive Non-Uniform Quantization for Large Language Models
148. ICML 2025Generalists vs. Specialists: Evaluating LLMs on Highly-Constrained Biophysical Sequence Optimization Tasks
149. ICML 2025Generalizing from SIMPLE to HARD Visual Reasoning: Can We Mitigate Modality Imbalance in VLMs?
150. ICML 2025GRAM: A Generative Foundation Reward Model for Reward Generalization

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.