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 16 / 47 页

751. ICML 2026R2-Router: A New Paradigm for LLM Routing with Reasoning
752. ICML 2026RaBitQCache: Rotated Binary Quantization for KVCache in Long Context LLM Inference
753. ICML 2026RAG without Forgetting: Continual Query-Infused Key Memory
754. ICML 2026RaGEP: Rank-aware Geometric Expert Pruning for Mixture-of-Experts Language Models
755. ICML 2026Random Selection Reveals Implicit Knowledge Consensus in Code Generation
756. ICML 2026Rank-Aware Spectral Bounds on Attention Logits for Stable Low-Precision Training
757. ICML 2026Rapid Poison: Practical Poisoning Attacks Against the Rapid Response Framework
758. ICML 2026Rare Event Analysis of Large Language Models
759. ICML 2026Rate or Fate? RLV$^{\varepsilon}$R: Reinforcement Learning with Verifiable Noisy Rewards
760. ICML 2026Ratio-Variance Regularized Policy Optimization
761. ICML 2026RBCBF: Decoding Time Safety Alignment via Risk Guided Rollback and Barrier Control
762. ICML 2026Re-FORC: Adaptive Reward Prediction for Efficient Chain-of-Thought Reasoning
763. ICML 2026Real-Time Aligned Reward Model beyond Semantics
764. ICML 2026Real-Time Monitoring and Calibration of Chain-of-Thought Sycophancy in Large Reasoning Models
765. ICML 2026REAL: Resolving Knowledge Conflicts in Knowledge-Intensive Visual Question Answering via Reasoning-Pivot Alignment
766. ICML 2026RealtimeTool: Parallel Decoding for Real-Time LLM Function Calling
767. ICML 2026REAR: Test-time Preference Realignment through Reward Decomposition
768. ICML 2026Reasoning Cache: Continual Improvement Over Long Horizons via Short-Horizon RL
769. ICML 2026Reasoning Can Be Restored by Correcting a Few Decision Tokens
770. ICML 2026Reasoning Compartmentalization: Bridging the Concretization Gap via Abstraction-based Routing
771. ICML 2026Reasoning Is Not Free: Robust Adaptive Cost-Efficient Routing for LLM-as-a-Judge
772. ICML 2026Reasoning LLM Improves Speaker Recognition in Long-form TV Dramas
773. ICML 2026Reasoning over Boundaries: Enhancing Specification Alignment via Test-time Deliberation
774. ICML 2026Reasoning Quality Emerges Early: Data Curation for Reasoning Models
775. ICML 2026Reasoning Structure of Large Language Models
776. ICML 2026Reasoning Theater: Disentangling Model Beliefs from Chain-of-Thought
777. ICML 2026Reasoning-preserved Efficient Distillation of Large Language Models via Activation-aware Initialization
778. ICML 2026Recognize Your Orchestrator: An Entropy Dynamics Perspective for LLM Multi-Agent Systems
779. ICML 2026Recontextualization Mitigates Specification Gaming Without Modifying the Specification
780. ICML 2026Recursive Models for Long-Horizon Reasoning
781. ICML 2026Regret Pre-training: Bridging Prior and Posterior Views for Enhanced Knowledge Grounding
782. ICML 2026Reinforcement Fine-Tuning Naturally Mitigates Forgetting in Continual Post-Training
783. ICML 2026Reinforcement-aware Knowledge Distillation for LLM Reasoning
784. ICML 2026RelayCaching: Accelerating LLM Collaboration via Decoding KV Cache Reuse
785. ICML 2026Reliability-Aware LLM Alignment from Inconsistent Human Feedback
786. ICML 2026ReMoE: Boosting Expert Reuse through Router Fine-Tuning in Memory-Constrained MoE LLM Inference
787. ICML 2026Removing Noise, not Finding Gold: Quality Filtering for Large-Scale Pretraining
788. ICML 2026rePIRL: Learn PRM with Inverse RL for LLM Reasoning
789. ICML 2026Replay Failures as Successes: Sample-Efficient Reinforcement Learning for Instruction Following
790. ICML 2026RePo: Language Models with Context Re-Positioning
791. ICML 2026Representation Drift Compensation: A Near-Zero Inference Cost Enhancement for LLM Decomposition
792. ICML 2026Representational Curvature Modulates Behavioral Uncertainty in Large Language Models
793. ICML 2026RePro: Training Language Models to Faithfully Recycle the Web for Pretraining
794. ICML 2026ReQAT: Achieving Full-Precision Reasoning Accuracy with 4-bit Floating-Point Quantization-Aware Training
795. ICML 2026ReSpinQuant: Efficient Layer-Wise LLM Quantization via Subspace Residual Rotation Approximation
796. ICML 2026ResRL: Boosting LLM Reasoning via Negative Sample Projection Residual Reinforcement Learning
797. ICML 2026Restoring Exploration after Post-Training: Latent Exploration Decoding for Large Reasoning Models
798. ICML 2026Retaining by Doing: The Role of On-Policy Data in Mitigating Forgetting
799. ICML 2026Rethinking 1-bit Optimization Leveraging Pre-trained Large Language Models
800. ICML 2026Rethinking KV Cache Eviction via a Unified Information-Theoretic Objective

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。