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 488 篇，第 6 / 10 页

251. NeurIPS 2023Improving CLIP Training with Language Rewrites
252. NeurIPS 2023Improving Few-Shot Generalization by Exploring and Exploiting Auxiliary Data
253. NeurIPS 2023In-Context Impersonation Reveals Large Language Models' Strengths and Biases
254. NeurIPS 2023In-Context Learning Unlocked for Diffusion Models
255. NeurIPS 2023Inference-Time Intervention: Eliciting Truthful Answers from a Language Model
256. NeurIPS 2023Instructing Goal-Conditioned Reinforcement Learning Agents with Temporal Logic Objectives
257. NeurIPS 2023Interactive Multi-fidelity Learning for Cost-effective Adaptation of Language Model with Sparse Human Supervision
258. NeurIPS 2023Intervention Generalization: A View from Factor Graph Models
259. NeurIPS 2023Intriguing Properties of Quantization at Scale
260. NeurIPS 2023Is Distance Matrix Enough for Geometric Deep Learning?
261. NeurIPS 2023Is Your Code Generated by ChatGPT Really Correct? Rigorous Evaluation of Large Language Models for Code Generation
262. NeurIPS 2023KAKURENBO: Adaptively Hiding Samples in Deep Neural Network Training
263. NeurIPS 2023Kiki or Bouba? Sound Symbolism in Vision-and-Language Models
264. NeurIPS 2023Koopa: Learning Non-stationary Time Series Dynamics with Koopman Predictors
265. NeurIPS 2023L-CAD: Language-based Colorization with Any-level Descriptions using Diffusion Priors
266. NeurIPS 2023LAMM: Language-Assisted Multi-Modal Instruction-Tuning Dataset, Framework, and Benchmark
267. NeurIPS 2023LANCE: Stress-testing Visual Models by Generating Language-guided Counterfactual Images
268. NeurIPS 2023Language Is Not All You Need: Aligning Perception with Language Models
269. NeurIPS 2023Language Model Alignment with Elastic Reset
270. NeurIPS 2023Language Model Tokenizers Introduce Unfairness Between Languages
271. NeurIPS 2023Language Models are Weak Learners
272. NeurIPS 2023Language Models Can Improve Event Prediction by Few-Shot Abductive Reasoning
273. NeurIPS 2023Language Models can Solve Computer Tasks
274. NeurIPS 2023Language Models Don't Always Say What They Think: Unfaithful Explanations in Chain-of-Thought Prompting
275. NeurIPS 2023Language Models Meet World Models: Embodied Experiences Enhance Language Models
276. NeurIPS 2023Large Language Model as Attributed Training Data Generator: A Tale of Diversity and Bias
277. NeurIPS 2023Large Language Models are Fixated by Red Herrings: Exploring Creative Problem Solving and Einstellung Effect using the Only Connect Wall Dataset
278. NeurIPS 2023Large Language Models Are Latent Variable Models: Explaining and Finding Good Demonstrations for In-Context Learning
279. NeurIPS 2023Large Language Models Are Semi-Parametric Reinforcement Learning Agents
280. NeurIPS 2023Large Language Models are Visual Reasoning Coordinators
281. NeurIPS 2023Large Language Models as Commonsense Knowledge for Large-Scale Task Planning
282. NeurIPS 2023Large Language Models can Implement Policy Iteration
283. NeurIPS 2023Large Language Models for Automated Data Science: Introducing CAAFE for Context-Aware Automated Feature Engineering
284. NeurIPS 2023Large language models implicitly learn to straighten neural sentence trajectories to construct a predictive representation of natural language.
285. NeurIPS 2023Large Language Models of Code Fail at Completing Code with Potential Bugs
286. NeurIPS 2023Large language models transition from integrating across position-yoked, exponential windows to structure-yoked, power-law windows
287. NeurIPS 2023Large sample spectral analysis of graph-based multi-manifold clustering
288. NeurIPS 2023Large-Scale Distributed Learning via Private On-Device LSH
289. NeurIPS 2023Laughing Hyena Distillery: Extracting Compact Recurrences From Convolutions
290. NeurIPS 2023LayoutGPT: Compositional Visual Planning and Generation with Large Language Models
291. NeurIPS 2023LayoutPrompter: Awaken the Design Ability of Large Language Models
292. NeurIPS 2023LeanDojo: Theorem Proving with Retrieval-Augmented Language Models
293. NeurIPS 2023Learning Descriptive Image Captioning via Semipermeable Maximum Likelihood Estimation
294. NeurIPS 2023Learning Domain-Aware Detection Head with Prompt Tuning
295. NeurIPS 2023Learning Large Graph Property Prediction via Graph Segment Training
296. NeurIPS 2023Learning Large-Scale MTP$_2$ Gaussian Graphical Models via Bridge-Block Decomposition
297. NeurIPS 2023Learning Large-scale Neural Fields via Context Pruned Meta-Learning
298. NeurIPS 2023Learning Mask-aware CLIP Representations for Zero-Shot Segmentation
299. NeurIPS 2023Learning Mixtures of Gaussians Using the DDPM Objective
300. NeurIPS 2023Learning Nonparametric Latent Causal Graphs with Unknown Interventions

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。