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 2,334 篇，第 47 / 47 页

2301. NeurIPS 2023Towards Unbounded Machine Unlearning
2302. NeurIPS 2023Train Faster, Perform Better: Modular Adaptive Training in Over-Parameterized Models
2303. NeurIPS 2023Training Chain-of-Thought via Latent-Variable Inference
2304. NeurIPS 2023Training Private Models That Know What They Don’t Know
2305. NeurIPS 2023Transformer-based Planning for Symbolic Regression
2306. NeurIPS 2023Transformers are uninterpretable with myopic methods: a case study with bounded Dyck grammars
2307. NeurIPS 2023Tree of Thoughts: Deliberate Problem Solving with Large Language Models
2308. NeurIPS 2023TrojLLM: A Black-box Trojan Prompt Attack on Large Language Models
2309. NeurIPS 2023Truly Scale-Equivariant Deep Nets with Fourier Layers
2310. NeurIPS 2023Two Sides of The Same Coin: Bridging Deep Equilibrium Models and Neural ODEs via Homotopy Continuation
2311. NeurIPS 2023Unbiased learning of deep generative models with structured discrete representations
2312. NeurIPS 2023Understanding Social Reasoning in Language Models with Language Models
2313. NeurIPS 2023Unifying GANs and Score-Based Diffusion as Generative Particle Models
2314. NeurIPS 2023UP-DP: Unsupervised Prompt Learning for Data Pre-Selection with Vision-Language Models
2315. NeurIPS 2023Using Imperfect Surrogates for Downstream Inference: Design-based Supervised Learning for Social Science Applications of Large Language Models
2316. NeurIPS 2023VanillaNet: the Power of Minimalism in Deep Learning
2317. NeurIPS 2023VCC: Scaling Transformers to 128K Tokens or More by Prioritizing Important Tokens
2318. NeurIPS 2023Video Prediction Models as Rewards for Reinforcement Learning
2319. NeurIPS 2023VisionLLM: Large Language Model is also an Open-Ended Decoder for Vision-Centric Tasks
2320. NeurIPS 2023Visual Explanations of Image-Text Representations via Multi-Modal Information Bottleneck Attribution
2321. NeurIPS 2023WalkLM: A Uniform Language Model Fine-tuning Framework for Attributed Graph Embedding
2322. NeurIPS 2023Waymax: An Accelerated, Data-Driven Simulator for Large-Scale Autonomous Driving Research
2323. NeurIPS 2023WCLD: Curated Large Dataset of Criminal Cases from Wisconsin Circuit Courts
2324. NeurIPS 2023What can Large Language Models do in chemistry? A comprehensive benchmark on eight tasks
2325. NeurIPS 2023What Do Deep Saliency Models Learn about Visual Attention?
2326. NeurIPS 2023What is the Inductive Bias of Flatness Regularization? A Study of Deep Matrix Factorization Models
2327. NeurIPS 2023When Does Optimizing a Proper Loss Yield Calibration?
2328. NeurIPS 2023White-Box Transformers via Sparse Rate Reduction
2329. NeurIPS 2023Why Does Sharpness-Aware Minimization Generalize Better Than SGD?
2330. NeurIPS 2023Wide Neural Networks as Gaussian Processes: Lessons from Deep Equilibrium Models
2331. NeurIPS 2023Winner-Take-All Column Row Sampling for Memory Efficient Adaptation of Language Model
2332. NeurIPS 2023Your representations are in the network: composable and parallel adaptation for large scale models
2333. NeurIPS 2023YouTube-ASL: A Large-Scale, Open-Domain American Sign Language-English Parallel Corpus
2334. NeurIPS 2023ZipLM: Inference-Aware Structured Pruning of Language Models

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。