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 20 / 33 页

951. ICML 2026TarGATE: Target-Aware Data Selection via Token-Attenuation Gates
952. ICML 2026Target-Oriented Pretraining Data Selection via Neuron-Activated Graph
953. ICML 2026Task-and-Model-Aware Fractal-Consistency for Efficient LLM Reasoning
954. ICML 2026Task-Aware Preference Calibration for Direct Preference Optimization
955. ICML 2026Task-Awareness Improves LLM Generations and Uncertainty
956. ICML 2026TCAP: Tri-Component Attention Profiling for Unsupervised Backdoor Detection in MLLM Fine-Tuning
957. ICML 2026Teaching Models to Teach Themselves: Reasoning at the Edge of Learnability
958. ICML 2026TEAM: Temporal–Spatial Consistency Guided Expert Activation for MoE Diffusion Language Model Acceleration
959. ICML 2026TeamTR: Trust-Region Fine-Tuning for Multi-Agent LLM Coordination
960. ICML 2026Temporal Self-Rewarding Language Models: Decoupling Chosen-Rejected via Past-Future
961. ICML 2026Test-Time Detoxification without Training or Learning Anything
962. ICML 2026Text Generation as Continuous Latent Dynamics via Reinforcement Learning
963. ICML 2026TextResNet: Decoupling and Routing Optimization Signals in Compound AI Systems via Deep Residual Tuning
964. ICML 2026Textual Stochastic Gradient Descent: Discrete Optimization of External Memory for Reasoning Language Agents
965. ICML 2026TGPO: Efficient Policy Optimization through Sequence Anchor and Information Gating
966. ICML 2026The Appeal and Reality of Recycling LoRAs with Adaptive Merging
967. ICML 2026The Art of Interrogation: Consistency Amplifies Factuality in Spatial Reasoning
968. ICML 2026The Bridge-Garden Dilemma in LLM Distillation: Why Mixing Hard and Soft Labels Works
969. ICML 2026The Convergent Representation of Contrastive Vision-Language Models: Geometry, Modality Gap and Shared Space Alignment
970. ICML 2026The Cylindrical Representation Hypothesis for Language Model Steering
971. ICML 2026The Devil is in the Spectrum: Mitigating Representation Collapse in LLMs via Topologically Regularized Side-Path
972. ICML 2026The Differences Between Direct Alignment Algorithms are a Blur
973. ICML 2026The Easy, the Hard, and the Learnable: Confidence and Difficulty-Adaptive Policy Optimization for LLM Reasoning
974. ICML 2026The Flexibility Trap: Rethinking the Value of Arbitrary Order in Diffusion Language Models
975. ICML 2026The Geometric Reasoner: Manifold-Informed Latent Foresight Search for Long-Context Reasoning
976. ICML 2026The Geometry of Narrow Fine-Tuning Degradation: Trajectory Lock-in and Spectral Bifurcation
977. ICML 2026The Geometry of Reasoning: Self-Evaluation via Layerwise Trajectory Evolution
978. ICML 2026The Hidden Cost of Structured Generation in LLMs: Draft-Conditioned Constrained Decoding
979. ICML 2026The Invisible Lottery: How Subtle Cues Steer Algorithm Choice in LLM Code Generation
980. ICML 2026The Labyrinth and the Thread: Rethinking Regularizations in Sequential Knowledge Editing for Large Language Models
981. ICML 2026The Optimal Token Baseline: Variance Reduction for Long-Horizon LLM-RL
982. ICML 2026The Perceptual Bandwidth Bottleneck in Vision-Language Models: Active Visual Reasoning via Sequential Experimental Design
983. ICML 2026The Quality-Utility Paradox: Why High-Reward Data Impairs Small Model Mathematical Reasoning
984. ICML 2026The Shadow Price of Reasoning: Economic Perspective on Optimal Budget Allocation for LLMs
985. ICML 2026The Shape of Addition: Geometric Structures of Arithmetic in Large Language Models
986. ICML 2026The Structural Origin of Attention Sink: Variance Discrepancy, Super Neurons, and Dimension Disparity
987. ICML 2026The Tell-Tale Norm: $\ell_2$ Magnitude as a Signal for Reasoning Dynamics in Large Language Models
988. ICML 2026The Truth Stays in the Family: Enhancing Contextual Truthfulness via Inherited Heads in Model Lineages
989. ICML 2026The Unlearnability Phenomenon in RLVR for Language Models
990. ICML 2026ThetaEvolve: Test-time Learning on Open Problems
991. ICML 2026Think Deep, Not Just Long: Measuring LLM Reasoning Effort via Deep-Thinking Tokens
992. ICML 2026Think in Latent, Explain in Language: Self-Explainable Latent Reasoning
993. ICML 2026Think-at-Hard: Selective Latent Iterations to Improve Reasoning Language Models
994. ICML 2026Thinking with Geometry: Active Geometry Integration for Spatial Reasoning
995. ICML 2026ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning
996. ICML 2026ThreadWeaver: Adaptive Threading for Efficient Parallel Reasoning in Language Models
997. ICML 2026Threshold-Based Exclusive Batching for LLM Inference
998. ICML 2026ThunderAgent: A Fast, Simple, and Program-Aware Agentic Inference System
999. ICML 2026TileQ: Efficient Low-Rank Quantization of Mixture-of-Experts with 2D Tiling
1000. ICML 2026TIME: Tensor-Factorized Mixture-of-Experts with Intrinsic Routing for Lifelong Multimodal Knowledge Editing

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。