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 27 / 33 页

1301. ICML 2025Investigating Non-Transitivity in LLM-as-a-Judge
1302. ICML 2025Iterative Vectors: In-Context Gradient Steering without Backpropagation
1303. ICML 2025Joint Localization and Activation Editing for Low-Resource Fine-Tuning
1304. ICML 2025KABB: Knowledge-Aware Bayesian Bandits for Dynamic Expert Coordination in Multi-Agent Systems
1305. ICML 2025KV Shifting Attention Enhances Language Modeling
1306. ICML 2025KVTuner: Sensitivity-Aware Layer-Wise Mixed-Precision KV Cache Quantization for Efficient and Nearly Lossless LLM Inference
1307. ICML 2025La RoSA: Enhancing LLM Efficiency via Layerwise Rotated Sparse Activation
1308. ICML 2025Ladder-Residual: Parallelism-Aware Architecture for Accelerating Large Model Inference with Communication Overlapping
1309. ICML 2025Language Models May Verbatim Complete Text They Were Not Explicitly Trained On
1310. ICML 2025Language Models over Canonical Byte-Pair Encodings
1311. ICML 2025Large Language Models are Demonstration Pre-Selectors for Themselves
1312. ICML 2025Large Language Models to Diffusion Finetuning
1313. ICML 2025Larger or Smaller Reward Margins to Select Preferences for LLM Alignment?
1314. ICML 2025Layer by Layer: Uncovering Hidden Representations in Language Models
1315. ICML 2025Learning Distribution-wise Control in Representation Space for Language Models
1316. ICML 2025Learning Dynamics in Continual Pre-Training for Large Language Models
1317. ICML 2025Learning Safety Constraints for Large Language Models
1318. ICML 2025Learning to Keep a Promise: Scaling Language Model Decoding Parallelism with Learned Asynchronous Decoding
1319. ICML 2025Learning to Plan & Reason for Evaluation with Thinking-LLM-as-a-Judge
1320. ICML 2025LensLLM: Unveiling Fine-Tuning Dynamics for LLM Selection
1321. ICML 2025Let LLM Tell What to Prune and How Much to Prune
1322. ICML 2025Lexico: Extreme KV Cache Compression via Sparse Coding over Universal Dictionaries
1323. ICML 2025LIFT the Veil for the Truth: Principal Weights Emerge after Rank Reduction for Reasoning-Focused Supervised Fine-Tuning
1324. ICML 2025Liger: Linearizing Large Language Models to Gated Recurrent Structures
1325. ICML 2025LLM Alignment as Retriever Optimization: An Information Retrieval Perspective
1326. ICML 2025LLM Data Selection and Utilization via Dynamic Bi-level Optimization
1327. ICML 2025LLMs Can Reason Faster Only If We Let Them
1328. ICML 2025LLMs on the Line: Data Determines Loss-to-Loss Scaling Laws
1329. ICML 2025Locate-then-edit for Multi-hop Factual Recall under Knowledge Editing
1330. ICML 2025Logits are All We Need to Adapt Closed Models
1331. ICML 2025LongRoPE2: Near-Lossless LLM Context Window Scaling
1332. ICML 2025Look Twice Before You Answer: Memory-Space Visual Retracing for Hallucination Mitigation in Multimodal Large Language Models
1333. ICML 2025Looking Beyond the Top-1: Transformers Determine Top Tokens in Order
1334. ICML 2025LoRA-Gen: Specializing Large Language Model via Online LoRA Generation
1335. ICML 2025MAGELLAN: Metacognitive predictions of learning progress guide autotelic LLM agents in large goal spaces
1336. ICML 2025MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning
1337. ICML 2025MAS-GPT: Training LLMs to Build LLM-based Multi-Agent Systems
1338. ICML 2025Mask-Enhanced Autoregressive Prediction: Pay Less Attention to Learn More
1339. ICML 2025MASS: Mathematical Data Selection via Skill Graphs for Pretraining Large Language Models
1340. ICML 2025Mastering Board Games by External and Internal Planning with Language Models
1341. ICML 2025MATH-Perturb: Benchmarking LLMs' Math Reasoning Abilities against Hard Perturbations
1342. ICML 2025MATS: An Audio Language Model under Text-only Supervision
1343. ICML 2025Maximizing Intermediate Checkpoint Value in LLM Pretraining with Bayesian Optimization
1344. ICML 2025Memorization Sinks: Isolating Memorization during LLM Training
1345. ICML 2025Memory Layers at Scale
1346. ICML 2025MetaAgent: Automatically Constructing Multi-Agent Systems Based on Finite State Machines
1347. ICML 2025Metadata Conditioning Accelerates Language Model Pre-training
1348. ICML 2025Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing
1349. ICML 2025Mitigating Object Hallucination in Large Vision-Language Models via Image-Grounded Guidance
1350. ICML 2025Mixture of Hidden-Dimensions: Not All Hidden-States’ Dimensions are Needed in Transformer

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。