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 29 / 33 页

1401. ICML 2025Potemkin Understanding in Large Language Models
1402. ICML 2025Predictive Data Selection: The Data That Predicts Is the Data That Teaches
1403. ICML 2025Preference Learning for AI Alignment: a Causal Perspective
1404. ICML 2025Premise-Augmented Reasoning Chains Improve Error Identification in Math reasoning with LLMs
1405. ICML 2025Principled Data Selection for Alignment: The Hidden Risks of Difficult Examples
1406. ICML 2025Product of Experts with LLMs: Boosting Performance on ARC Is a Matter of Perspective
1407. ICML 2025Programming Every Example: Lifting Pre-training Data Quality Like Experts at Scale
1408. ICML 2025Progressively Label Enhancement for Large Language Model Alignment
1409. ICML 2025ProofAug: Efficient Neural Theorem Proving via Fine-grained Proof Structure Analysis
1410. ICML 2025Proposer-Agent-Evaluator (PAE): Autonomous Skill Discovery For Foundation Model Internet Agents
1411. ICML 2025ProSec: Fortifying Code LLMs with Proactive Security Alignment
1412. ICML 2025PROXSPARSE: REGULARIZED LEARNING OF SEMI-STRUCTURED SPARSITY MASKS FOR PRETRAINED LLMS
1413. ICML 2025Prune 'n Predict: Optimizing LLM Decision-making with Conformal Prediction
1414. ICML 2025Puzzle: Distillation-Based NAS for Inference-Optimized LLMs
1415. ICML 2025QLASS: Boosting Language Agent Inference via Q-Guided Stepwise Search
1416. ICML 2025Quamba2: A Robust and Scalable Post-training Quantization Framework for Selective State Space Models
1417. ICML 2025QuantSpec: Self-Speculative Decoding with Hierarchical Quantized KV Cache
1418. ICML 2025R.I.P.: Better Models by Survival of the Fittest Prompts
1419. ICML 2025RATE: Causal Explainability of Reward Models with Imperfect Counterfactuals
1420. ICML 2025RE-Bench: Evaluating Frontier AI R&D Capabilities of Language Model Agents against Human Experts
1421. ICML 2025Reasoning-as-Logic-Units: Scaling Test-Time Reasoning in Large Language Models Through Logic Unit Alignment
1422. ICML 2025Reflection-Window Decoding: Text Generation with Selective Refinement
1423. ICML 2025Regress, Don't Guess: A Regression-like Loss on Number Tokens for Language Models
1424. ICML 2025Reinforced Lifelong Editing for Language Models
1425. ICML 2025Reliable and Efficient Amortized Model-based Evaluation
1426. ICML 2025Residual Matrix Transformers: Scaling the Size of the Residual Stream
1427. ICML 2025Resolving Lexical Bias in Model Editing
1428. ICML 2025ResQ: Mixed-Precision Quantization of Large Language Models with Low-Rank Residuals
1429. ICML 2025Restoring Calibration for Aligned Large Language Models: A Calibration-Aware Fine-Tuning Approach
1430. ICML 2025Rethinking Addressing in Language Models via Contextualized Equivariant Positional Encoding
1431. ICML 2025Rethinking Chain-of-Thought from the Perspective of Self-Training
1432. ICML 2025Rethinking External Slow-Thinking: From Snowball Errors to Probability of Correct Reasoning
1433. ICML 2025Retraining-free Merging of Sparse MoE via Hierarchical Clustering
1434. ICML 2025Retrieval-Augmented Perception: High-resolution Image Perception Meets Visual RAG
1435. ICML 2025Revealing Weaknesses in Text Watermarking Through Self-Information Rewrite Attacks
1436. ICML 2025ReVISE: Learning to Refine at Test-Time via Intrinsic Self-Verification
1437. ICML 2025Revisiting Chain-of-Thought in Code Generation: Do Language Models Need to Learn Reasoning before Coding?
1438. ICML 2025Revolve: Optimizing AI Systems by Tracking Response Evolution in Textual Optimization
1439. ICML 2025Reward Modeling with Ordinal Feedback: Wisdom of the Crowd
1440. ICML 2025Reward-Augmented Data Enhances Direct Preference Alignment of LLMs
1441. ICML 2025Reward-Guided Prompt Evolving in Reinforcement Learning for LLMs
1442. ICML 2025Reward-Guided Speculative Decoding for Efficient LLM Reasoning
1443. ICML 2025Right Now, Wrong Then: Non-Stationary Direct Preference Optimization under Preference Drift
1444. ICML 2025RLEF: Grounding Code LLMs in Execution Feedback with Reinforcement Learning
1445. ICML 2025RLTHF: Targeted Human Feedback for LLM Alignment
1446. ICML 2025Robust Multimodal Large Language Models Against Modality Conflict
1447. ICML 2025Roll the dice & look before you leap: Going beyond the creative limits of next-token prediction
1448. ICML 2025ROPO: Robust Preference Optimization for Large Language Models
1449. ICML 2025RoSTE: An Efficient Quantization-Aware Supervised Fine-Tuning Approach for Large Language Models
1450. ICML 2025RuleAdapter: Dynamic Rules for training Safety Reward Models in RLHF

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。