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 1,131 篇，第 12 / 23 页

551. ICML 2026LogicSAGE: Neuro-Symbolic Reasoning with Socratic-Guided Enhancement
552. ICML 2026Logit-Attention Divergence: Mitigating Position Bias in Multi-Image Retrieval via Attention-Guided Calibration
553. ICML 2026LoKiFormer: Locality-aware Attention with Decoupled Knowledge Memory for Efficient Large Language Model Pretraining
554. ICML 2026Long Live The Balance: Information Bottleneck Driven Tree-based Policy Optimization
555. ICML 2026Long-Context Modeling with Dynamic Hierarchical Sparse Attention for Memory-Constrained LLM Inference
556. ICML 2026LongCoT: Benchmarking Long-Horizon Chain-of-Thought Reasoning
557. ICML 2026Look on Demand: A Cognitive Scheduling Framework for Visual Evidence Acquisition in Multimodal Reasoning
558. ICML 2026Lookahead-GCG: Improving Universal Multi-Model Optimization-Based Jailbreaking Attacks via Stochastic Nesterov Optimization
559. ICML 2026LoRA-DA: Data-Aware Initialization for Low-Rank Adaptation via Asymptotic Analysis
560. ICML 2026LORD-GoF: A Robust Online Detection Approach for LLM Watermarks in Sparse and Mixed Streams
561. ICML 2026Low Kruskal-Rank Adaptation
562. ICML 2026Low-cost Full Fine-tuning: Learning What to Update for LLMs
563. ICML 2026LRAgent: Efficient KV Cache Sharing for Multi-LoRA LLM Agents
564. ICML 2026LUCID: Attention with Preconditioned Representations
565. ICML 2026LUGS: Latent-aware Guidance for Efficient Unmasking in Diffusion Large Language Models
566. ICML 2026M-Star: Markovian Projection of Star-Shaped Diffusion for Exponential Family Distributions
567. ICML 2026MACD: Model-Aware Contrastive Decoding via Counterfactual Data for Video-LLMs
568. ICML 2026MAGIC: A Co-Evolving Attacker–Defender Adversarial Game for Robust LLM Safety
569. ICML 2026Making Expert Reasoning Learnable with Self-Distillation
570. ICML 2026ManifoldKV: Training-Free KV Cache Compression via Euclidean Outlier Detection
571. ICML 2026Many-Shot CoT-ICL: Making In-Context Learning Truly Learn
572. ICML 2026MAPS: Memory-Aware Predictive Scheduling Framework for Large Language Model Serving
573. ICML 2026Margin-Adaptive Confidence Ranking for Reliable LLM Judgement
574. ICML 2026MAS-Architect: Declarative Multi-Agent System Design via Separation of Concerns
575. ICML 2026MAS-Orchestra: Understanding and Improving Multi-Agent Reasoning Through Holistic Orchestration and Controlled Benchmarks
576. ICML 2026MAS-ProVe: Understanding the Process Verification of Multi-Agent Systems
577. ICML 2026MASH: Modeling Abstention via Selective Help-Seeking
578. ICML 2026Masks Can Be Distracting: On Context Comprehension in Diffusion Language Models
579. ICML 2026MASPO: Joint Prompt Optimization for LLM-based Multi-Agent Systems
580. ICML 2026MASPOB: Bandit-Based Prompt Optimization for Multi-Agent Systems with Graph Neural Networks
581. ICML 2026Maximizing Mutual Information Between Prompt and Response Improves LLM Performance With No Additional Data
582. ICML 2026Maximum Likelihood Reinforcement Learning
583. ICML 2026MCCE: A Framework for Multi-LLM Collaborative Search in Discrete Spaces with Similarity-Filtered Preference Learning
584. ICML 2026Measuring and Mitigating Post-Hoc Rationalization in Reverse Chain-of-Thought Generation
585. ICML 2026Measuring Meta-Cultural Competency: A Spectral Framework for LLM Knowledge Structures
586. ICML 2026MechVQA: Benchmarking and Enhancing Multimodal LLMs on Comprehensive Mechanical Drawing Understanding
587. ICML 2026Mem-T: Densifying Rewards for Long-Horizon Memory Agents
588. ICML 2026MemEvolve: Meta-Evolution of Agent Memory Systems
589. ICML 2026MEMO: Memory-Augmented Model Context Optimization for Robust Multi-Turn Multi-Agent LLM Games
590. ICML 2026Memora: A Harmonic Memory Representation Balancing Abstraction and Specificity
591. ICML 2026Memory as a Markov Matrix: Sample Efficient Knowledge Expansion via Token-to-Dictionary Mapping
592. ICML 2026Memory is Reconstructed, Not Retrieved: Graph Memory for LLM Agents
593. ICML 2026Memory-Efficient LLM Pretraining via Minimalist Optimizer Design
594. ICML 2026Memory-Efficient LLM Training with Dynamic Sparsity: From Stability to Practical Scaling
595. ICML 2026MemoryLLM: Plug-n-Play Interpretable Feed-Forward Memory for Transformers
596. ICML 2026MergeMix: Optimizing Mid-Training Data Mixtures via Learnable Model Merging
597. ICML 2026Meta Context Engineering via Agentic Skill Evolution
598. ICML 2026MetaphorVU: Towards Metaphorical Video Understanding
599. ICML 2026mHC: Manifold-Constrained Hyper-Connections
600. ICML 2026Midtraining Bridges Pretraining and Posttraining Distributions

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。