深度学习 · large language models论文趋势 2023–2026

主要结论

• 深度学习 · large language models论文从 2023 年的 488 篇增长到 2026 年的 1,131 篇，三年间扩大到约 2.3 倍。
• ICML 是发深度学习 · large language models论文最多的会议，2023–2026 年共 1,608 篇，占四个会议总量的 69%。
• 交叉方向里涨得最快的是AI 智能体：同时属于两个主题的论文从 2023 年的 5 篇增至 2026 年的 184 篇。
• 在「深度学习」的 11 个主题里，它的 2026 年论文数排第 3；同组增长最快的扩散模型是 4.1 倍，深度学习 · large language models是 2.3 倍。

代表论文

按年份和会议均匀挑选，方便快速看到每一届的样貌

• 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

全部深度学习 · large language models论文

共 1,608 篇，第 24 / 33 页

1151. ICML 2025An Architecture Search Framework for Inference-Time Techniques
1152. ICML 2025An Efficient Pruner for Large Language Model with Theoretical Guarantee
1153. ICML 2025An Interpretable N-gram Perplexity Threat Model for Large Language Model Jailbreaks
1154. ICML 2025Analyze Feature Flow to Enhance Interpretation and Steering in Language Models
1155. ICML 2025any4: Learned 4-bit Numeric Representation for LLMs
1156. ICML 2025AnyEdit: Edit Any Knowledge Encoded in Language Models
1157. ICML 2025Are LLMs Prescient? A Continuous Evaluation using Daily News as the Oracle
1158. ICML 2025Attention Mechanisms Perspective: Exploring LLM Processing of Graph-Structured Data
1159. ICML 2025AuPair: Golden Example Pairs for Code Repair
1160. ICML 2025Automated Benchmark Generation for Repository-Level Coding Tasks
1161. ICML 2025Automated Hypothesis Validation with Agentic Sequential Falsifications
1162. ICML 2025Autonomy-of-Experts Models
1163. ICML 2025BackSlash: Rate Constrained Optimized Training of Large Language Models
1164. ICML 2025BanditSpec: Adaptive Speculative Decoding via Bandit Algorithms
1165. ICML 2025Benchmarking Abstract and Reasoning Abilities Through A Theoretical Perspective
1166. ICML 2025Benign Samples Matter! Fine-tuning On Outlier Benign Samples Severely Breaks Safety
1167. ICML 2025BEST-Route: Adaptive LLM Routing with Test-Time Optimal Compute
1168. ICML 2025Beyond Zero Initialization: Investigating the Impact of Non-Zero Initialization on LoRA Fine-Tuning Dynamics
1169. ICML 2025Binary Hypothesis Testing for Softmax Models and Leverage Score Models
1170. ICML 2025BlockDialect: Block-wise Fine-grained Mixed Format Quantization for Energy-Efficient LLM Inference
1171. ICML 2025Boosting Multi-Domain Fine-Tuning of Large Language Models through Evolving Interactions between Samples
1172. ICML 2025Bounded Rationality for LLMs: Satisficing Alignment at Inference-Time
1173. ICML 2025Bring Reason to Vision: Understanding Perception and Reasoning through Model Merging
1174. ICML 2025BRiTE: Bootstrapping Reinforced Thinking Process to Enhance Language Model Reasoning
1175. ICML 2025Cache Me If You Must: Adaptive Key-Value Quantization for Large Language Models
1176. ICML 2025Calibrated Language Models and How to Find Them with Label Smoothing
1177. ICML 2025Can Compressed LLMs Truly Act? An Empirical Evaluation of Agentic Capabilities in LLM Compression
1178. ICML 2025Can Large Language Models Understand Intermediate Representations in Compilers?
1179. ICML 2025Can MLLMs Reason in Multimodality? EMMA: An Enhanced MultiModal ReAsoning Benchmark
1180. ICML 2025Can We Predict Performance of Large Models across Vision-Language Tasks?
1181. ICML 2025Catch Your Emotion: Sharpening Emotion Perception in Multimodal Large Language Models
1182. ICML 2025CateKV: On Sequential Consistency for Long-Context LLM Inference Acceleration
1183. ICML 2025Chameleon: A Flexible Data-mixing Framework for Language Model Pretraining and Finetuning
1184. ICML 2025CLOVER: Cross-Layer Orthogonal Vectors Pruning
1185. ICML 2025CodeIO: Condensing Reasoning Patterns via Code Input-Output Prediction
1186. ICML 2025Collapse or Thrive: Perils and Promises of Synthetic Data in a Self-Generating World
1187. ICML 2025CoMemo: LVLMs Need Image Context with Image Memory
1188. ICML 2025Communicating Activations Between Language Model Agents
1189. ICML 2025CommVQ: Commutative Vector Quantization for KV Cache Compression
1190. ICML 2025Compositional Causal Reasoning Evaluation in Language Models
1191. ICML 2025Compress then Serve: Serving Thousands of LoRA Adapters with Little Overhead
1192. ICML 2025ConfPO: Exploiting Policy Model Confidence for Critical Token Selection in Preference Optimization
1193. ICML 2025Controlling Large Language Model with Latent Action
1194. ICML 2025Core Context Aware Transformers for Long Context Language Modeling
1195. ICML 2025CoreMatching: A Co-adaptive Sparse Inference Framework with Token and Neuron Pruning for Comprehensive Acceleration of Vision-Language Models
1196. ICML 2025Cost-efficient Collaboration between On-device and Cloud Language Models
1197. ICML 2025CPCF: A Cross-Prompt Contrastive Framework for Referring Multimodal Large Language Models
1198. ICML 2025CRANE: Reasoning with constrained LLM generation
1199. ICML 2025Critical Tokens Matter: Token-Level Contrastive Estimation Enhances LLM’s Reasoning Capability
1200. ICML 2025CROW: Eliminating Backdoors from Large Language Models via Internal Consistency Regularization

常见问题

2023–2026 年四大会议一共有多少篇深度学习 · large language models论文？

共 2,334 篇，按年份分别是 2023 年 488 篇、2024 年 298 篇、2025 年 417 篇、2026 年 1,131 篇。

NeurIPS 2024 有多少篇深度学习 · large language models论文？

NeurIPS 2024 有 298 篇深度学习 · large language models论文，上一届是 415 篇。

ICLR 2025 有多少篇深度学习 · large language models论文？

ICLR 2025 有 13 篇深度学习 · large language models论文。

ICML 2026 有多少篇深度学习 · large language models论文？

ICML 2026 有 1,131 篇深度学习 · large language models论文，上一届是 404 篇。

哪个会议的深度学习 · large language models论文最多？

ICML，2023–2026 年共 1,608 篇。