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 14 / 23 页

651. ICML 2026Numina-Lean-Agent: An Open and General Agentic Reasoning System for Formal Mathematics
652. ICML 2026OBCache: Optimal Brain KV Cache Pruning for Efficient Long-Context LLM Inference
653. ICML 2026OCNR: Stabilizing Self-Play by Mitigating Iteration-Collapse With One-Class Novelty Rewards
654. ICML 2026Olmix: A Framework for Data Mixing Throughout LM Development
655. ICML 2026Omni-Diffusion: Unified Multimodal Understanding and Generation with Masked Discrete Diffusion
656. ICML 2026OmniFit: Bridging Modalities via Layer-Adaptive Token Compression for Omnimodal Large Language Models
657. ICML 2026OmniSIFT: Modality-Asymmetric Token Compression for Efficient Omni-modal Large Language Models
658. ICML 2026On Group Relative Policy Optimization Collapse in Agent Search: The Lazy Likelihood-Displacement
659. ICML 2026On Information Self-Locking in Reinforcement Learning for Active Reasoning of LLM agents
660. ICML 2026On the Entropy Dynamics in Reinforcement Fine-Tuning of Large Language Models
661. ICML 2026On the Generalization Gap in Self-Evolving Language Model Reasoning
662. ICML 2026On the Interplay of Pre-Training, Mid-Training, and RL on Reasoning Language Models
663. ICML 2026On the Limits of LLM Adaptability: Impact of Model-Internalized Priors on Annotation Task Performance
664. ICML 2026On the Limits of Test-Time Compute: Sequential Reward Filtering for Better Inference
665. ICML 2026On the Plasticity and Stability for Post-Training Large Language Models
666. ICML 2026On Training Large Language Models for Long-Horizon Tasks: An Empirical Study of Horizon Length
667. ICML 2026One LR Doesn’t Fit All: Heavy-Tail Guided Layerwise Learning Rates for LLMs
668. ICML 2026One Tool Is Enough: Reinforcement Learning of LLM Agents for Repository-Level Code Navigation
669. ICML 2026One-shot Entropy Minimization for Language Model Reasoning
670. ICML 2026One-Step Residual Shifting Diffusion for Image Super-Resolution via Distillation
671. ICML 2026One-Way Policy Optimization for Self-Evolving LLMs
672. ICML 2026OnePO: Direct One-stage Policy Optimization for SFT-free Domain Adaptation
673. ICML 2026Op-CAD: Benchmarking and Investigating Operation-oriented CAD Generation
674. ICML 2026Optimal Transport for LLM Reward Modeling from Noisy Feedback
675. ICML 2026OptProver: Bridging Olympiad and Optimization through Continual Training in Formal Theorem Proving
676. ICML 2026OPUS: Towards Efficient and Principled Data Selection in Large Language Model Pre-training in Every Iteration
677. ICML 2026Orthogonal Hierarchical Decomposition for Structure-Aware Table Understanding with Large Language Models
678. ICML 2026OSAQ: Outlier Self-Absorption for Accurate Low-bit LLM Quantization
679. ICML 2026OTora: A Unified Red Teaming Framework for Reasoning-Level Denial-of-Service in LLM Agents
680. ICML 2026Out-of-Distribution Evaluation of Rule-Based and Strategic Reasoning in Chess Transformers
681. ICML 2026Outrunning LLM Cutoffs: A Live Kernel Crash Resolution Benchmark for All
682. ICML 2026Overthinking: Amplifying Reasoning Weights to Extract Learned Secrets
683. ICML 2026PADA-Coder: Improving Plan-Following Code Generation via Perturbation-Verified Attention Distillation and Dynamic Alignment
684. ICML 2026Parallel-Probe: Towards Efficient Parallel Thinking via 2D Probing
685. ICML 2026ParamMem: Augmenting Language Agents with Parametric Reflective Memory
686. ICML 2026ParaTool: Shifting Tool Representations from Context to Parameters
687. ICML 2026ParEVO: Synthesizing Code for Irregular Data: High-Performance Parallelism through Agentic Evolution
688. ICML 2026PASA: A Principled Embedding-Space Watermarking Approach for LLM-Generated Text under Semantic-Invariant Attacks
689. ICML 2026PatternKV: Flattening KV Representation Expands Quantization Headroom
690. ICML 2026Perceptual Flow Network for Visually Grounded Reasoning
691. ICML 2026Persistent Semantic Entities in Tool-Augmented LLM Systems
692. ICML 2026Persona-Pruner: Sculpting Lightweight Models for Role-Playing
693. ICML 2026Persona2Web: Benchmarking Personalized Web Agents for Contextual Reasoning with User History
694. ICML 2026PETS: A Principled Framework Towards Optimal Trajectory Allocation for Efficient Test-Time Self-Consistency
695. ICML 2026PGS: Effective LLM Code Refinement via Property-Oriented and Structurally Minimal Feedback
696. ICML 2026PISA: Privacy-Preserving Split Adaptation with Model IP Protection
697. ICML 2026Plan for Speed: Dilated Scheduling for Masked Diffusion Language Models
698. ICML 2026PLANTAIN: Plan-Answer Interleaved Reasoning
699. ICML 2026PlotCraft: Pushing the Limits of LLMs for Complex and Interactive Data Visualization
700. ICML 2026Plug-and-Play Spiking Operators: Breaking the Nonlinearity Bottleneck in Spiking Transformers

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。