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 18 / 23 页

851. ICML 2026SCHUR-A*: Layer-wise Optimal Expert Pruning for MoEs via Schur-Complement Guided A* Search
852. ICML 2026SciPredict: Can LLMs Predict the Outcomes of Scientific Experiments in Natural Sciences?
853. ICML 2026SCOPE and SCION: A Benchmark and an Auditable Reference Pipeline for Schema Induction and Fusion from Text
854. ICML 2026SCOPE: Selective Conformal Optimized Pairwise LLM Judging
855. ICML 2026SD-MoE: Spectral Decomposition for Effective Expert Specialization
856. ICML 2026Search for Truth from Reasoning: A Dynamic Representation Editing Framework for Steering LLM Trajectories
857. ICML 2026Search or Accelerate: Confidence-Switched Position Beam Search for Diffusion Language Models
858. ICML 2026Search-R2: Enhancing Search-Integrated Reasoning via Actor-Refiner Collaboration
859. ICML 2026Seeing is Understanding: Unlocking Causal Attention into Modality-Mutual Attention for Multimodal LLMs
860. ICML 2026Seeing the Unseen: Physics-as-Representation for Generalizable Gaze Perception
861. ICML 2026Select to Think: Unlocking SLM Potential with Local Sufficiency
862. ICML 2026Selective Deferred Routing: Enabling Cost-Efficient Collaboration between Local SLMs and Remote LLMs
863. ICML 2026Self-Augmenting Retrieval for Diffusion Language Models
864. ICML 2026Self-Distilled Reasoner: On-Policy Self-Distillation for Large Language Models
865. ICML 2026Self-evolving LLM agents with in-distribution Optimization
866. ICML 2026Self-Prophetic Decoding to Unlock Visual Search in LVLMs
867. ICML 2026SelfJudge: Faster Speculative Decoding via Self-Supervised Judge Verification
868. ICML 2026Sem-Detect: Semantic Level Detection of AI Generated Peer-Reviews
869. ICML 2026Semantic Cache Distillation: Efficient State Transfer via Reuse and Selective Patching
870. ICML 2026Semantic Impact–Driven Visual Scheduling in Vision-Language Models
871. ICML 2026Semantic Tube Prediction: Beating LLM Data Efficiency with JEPA
872. ICML 2026SERA: Soft-Verified Efficient Repository Agents
873. ICML 2026SetPO: Set-Level Policy Optimization for Diversity-Preserving LLM Reasoning
874. ICML 2026Sharpness-Aware Pretraining Mitigates Catastrophic Forgetting
875. ICML 2026SHINE: A Scalable In-Context Hypernetwork for Mapping Context to LoRA in a Single Pass
876. ICML 2026Short Chains, Deep Thoughts: Balancing Reasoning Efficiency and Intra-Segment Capability via Split-Merge Optimization
877. ICML 2026Shrinking the Variance: Shrinkage Baselines for Reinforcement Learning with Verifiable Rewards
878. ICML 2026Shuffle the Context: RoPE-Perturbed Self-Distillation for Long-Context Adaptation
879. ICML 2026SiameseNorm: Breaking the Barrier to Reconciling Pre/Post-Norm
880. ICML 2026Sim2Reason: Solving Physics Olympiad via Reinforcement Learning on Physics Simulators
881. ICML 2026Simple Policy Gradients for Reasoning with Diffusion Language Models
882. ICML 2026SimpleGPT: Improving GPT via A Simple Normalization Strategy
883. ICML 2026SimpleMem: Efficient Lifelong Memory for LLM Agents
884. ICML 2026Simultaneous Speech-to-Speech Translation Without Aligned Data
885. ICML 2026Singular Proxies for Adaptive Caching in Diffusion Language Models
886. ICML 2026Singular Vectors of Attention Heads Align with Features
887. ICML 2026SINQ: Sinkhorn-Normalized Quantization for Calibration-Free Low-Precision LLM Weights
888. ICML 2026Skill Neologisms: Towards Skill-based Continual Learning
889. ICML 2026Skill-Based Mixture-of-Experts: Adaptive Routing for Heterogeneous Reasoning via Inferred Skills
890. ICML 2026Skip a Layer or Loop It? Learning Program-of-Layers in LLMs
891. ICML 2026SL-VC: A Benchmark and Automated Framework for Separation Logic Verification Condition Proving
892. ICML 2026SLASH the Sink: Sharpening Structural Attention Inside LLMs
893. ICML 2026SLAT: Segment-Level Adaptive Trimming for Efficient CoT Reasoning
894. ICML 2026SliceFine: The Universal Winning-Slice Hypothesis for Pretrained Networks
895. ICML 2026SLQ: Bridging Modalities via Shared Latent Queries for Retrieval with Frozen MLLMs
896. ICML 2026Small Generalizable Prompt Predictive Models Can Steer Efficient RL Post-Training of Large Reasoning Models
897. ICML 2026Smaller Models are Natural Explorers for Policy-Level Diversity in GRPO
898. ICML 2026SmartThinker: Progressive Chain-of-Thought Length Calibration for Efficient Large Language Model Reasoning
899. ICML 2026SMILE: Extended Deep Submodular Function-Based Instruction and In-context Learning Demonstration Selection
900. ICML 2026Smoothie: Smoothing Diffusion on Token Embeddings for Text Generation

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。