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 417 篇，第 6 / 9 页

251. ICML 2025Occult: Optimizing Collaborative Communications across Experts for Accelerated Parallel MoE Training and Inference
252. ICML 2025Olica: Efficient Structured Pruning of Large Language Models without Retraining
253. ICML 2025OmniBal: Towards Fast Instruction-Tuning for Vision-Language Models via Omniverse Computation Balance
254. ICML 2025On Teacher Hacking in Language Model Distillation
255. ICML 2025On the Duality between Gradient Transformations and Adapters
256. ICML 2025On the Robustness of Reward Models for Language Model Alignment
257. ICML 2025On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention for Long-Context LLM Serving
258. ICML 2025Optimizing Large Language Model Training Using FP4 Quantization
259. ICML 2025Optimizing Temperature for Language Models with Multi-Sample Inference
260. ICML 2025Optimizing Test-Time Compute via Meta Reinforcement Finetuning
261. ICML 2025Oracle-MoE: Locality-preserving Routing in the Oracle Space for Memory-constrained Large Language Model Inference
262. ICML 2025Organize the Web: Constructing Domains Enhances Pre-Training Data Curation
263. ICML 2025OrthoRank: Token Selection via Sink Token Orthogonality for Efficient LLM inference
264. ICML 2025Over-Tokenized Transformer: Vocabulary is Generally Worth Scaling
265. ICML 2025Overcoming Multi-step Complexity in Multimodal Theory-of-Mind Reasoning: A Scalable Bayesian Planner
266. ICML 2025Overcoming Vocabulary Mismatch: Vocabulary-agnostic Teacher Guided Language Modeling
267. ICML 2025Overtrained Language Models Are Harder to Fine-Tune
268. ICML 2025PANDAS: Improving Many-shot Jailbreaking via Positive Affirmation, Negative Demonstration, and Adaptive Sampling
269. ICML 2025Parameters vs FLOPs: Scaling Laws for Optimal Sparsity for Mixture-of-Experts Language Models
270. ICML 2025PARM: Multi-Objective Test-Time Alignment via Preference-Aware Autoregressive Reward Model
271. ICML 2025Parrot: Multilingual Visual Instruction Tuning
272. ICML 2025PENCIL: Long Thoughts with Short Memory
273. ICML 2025Perception in Reflection
274. ICML 2025Peripheral Memory for LLMs: Integration of Sequential Memory Banks with Adaptive Querying
275. ICML 2025Persistent Topological Features in Large Language Models
276. ICML 2025PILAF: Optimal Human Preference Sampling for Reward Modeling
277. ICML 2025PIPA: Preference Alignment as Prior-Informed Statistical Estimation
278. ICML 2025Pivoting Factorization: A Compact Meta Low-Rank Representation of Sparsity for Efficient Inference in Large Language Models
279. ICML 2025Plan-and-Act: Improving Planning of Agents for Long-Horizon Tasks
280. ICML 2025PoisonBench: Assessing Language Model Vulnerability to Poisoned Preference Data
281. ICML 2025Policy Guided Tree Search for Enhanced LLM Reasoning
282. ICML 2025polybasic Speculative Decoding Through a Theoretical Perspective
283. ICML 2025Potemkin Understanding in Large Language Models
284. ICML 2025Predictive Data Selection: The Data That Predicts Is the Data That Teaches
285. ICML 2025Preference Learning for AI Alignment: a Causal Perspective
286. ICML 2025Premise-Augmented Reasoning Chains Improve Error Identification in Math reasoning with LLMs
287. ICML 2025Principled Data Selection for Alignment: The Hidden Risks of Difficult Examples
288. ICML 2025Product of Experts with LLMs: Boosting Performance on ARC Is a Matter of Perspective
289. ICML 2025Programming Every Example: Lifting Pre-training Data Quality Like Experts at Scale
290. ICML 2025Progressively Label Enhancement for Large Language Model Alignment
291. ICML 2025ProofAug: Efficient Neural Theorem Proving via Fine-grained Proof Structure Analysis
292. ICML 2025Proposer-Agent-Evaluator (PAE): Autonomous Skill Discovery For Foundation Model Internet Agents
293. ICML 2025ProSec: Fortifying Code LLMs with Proactive Security Alignment
294. ICML 2025PROXSPARSE: REGULARIZED LEARNING OF SEMI-STRUCTURED SPARSITY MASKS FOR PRETRAINED LLMS
295. ICML 2025Prune 'n Predict: Optimizing LLM Decision-making with Conformal Prediction
296. ICML 2025Puzzle: Distillation-Based NAS for Inference-Optimized LLMs
297. ICML 2025QLASS: Boosting Language Agent Inference via Q-Guided Stepwise Search
298. ICML 2025Quamba2: A Robust and Scalable Post-training Quantization Framework for Selective State Space Models
299. ICML 2025QuantSpec: Self-Speculative Decoding with Hierarchical Quantized KV Cache
300. ICML 2025R.I.P.: Better Models by Survival of the Fittest Prompts

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。