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 3 / 33 页

101. ICML 2026Beyond Heuristic Tuning: Power-Calibrated LLM Watermarking
102. ICML 2026Beyond Log Likelihood: Probability-Based Objectives for Supervised Fine-Tuning across the Model Capability Continuum
103. ICML 2026Beyond Logits: Metastable Latent Dynamics for Sample-Efficient Best-of-N Selection in LLMs
104. ICML 2026Beyond Majority Voting: Self-Reflective Test-Time Reinforcement Learning for LLM Reasoning
105. ICML 2026Beyond Mode Collapse: Distribution Matching for Diverse Reasoning
106. ICML 2026Beyond Next-Token Alignment: Distilling Multimodal Large Language Models via Token Interactions
107. ICML 2026Beyond Prediction: Tail-Aware Scheduling for LLM Inference
108. ICML 2026Beyond Problem Solving: UOJ-Bench for Evaluating Code Generation, Hacking, and Repair in Competitive Programming
109. ICML 2026Beyond Reactivity: Proactive Adaptive Conformal Inference for Online LLM Factuality
110. ICML 2026Beyond Scalars: Evaluating and Understanding LLM Reasoning via Geometric Progress and Stability
111. ICML 2026Beyond Sunk Costs: Boosting LLM Pre-training Efficiency via Orthogonal Growth of Mixture-of-Experts
112. ICML 2026Beyond Temperature: Hyperfitting as a Late-Stage Geometric Expansion
113. ICML 2026Beyond Test-Time Memory: State-Space Optimal Control for LLM Reasoning
114. ICML 2026BFCL Audio: An Audio Function Calling Evaluation for Large Language Models
115. ICML 2026Bits That Count: Quantifying and Predicting Capabilities of Language Models
116. ICML 2026Blending Supervised and Reinforcement Fine-Tuning with Prefix Sampling
117. ICML 2026BLISS: A Lightweight Bilevel Influence Scoring Method for Data Selection in Language Model Pretraining
118. ICML 2026Block Rotation is All You Need for MXFP4 Quantization
119. ICML 2026BLOCK-EM: Preventing Emergent Misalignment via Latent Blocking
120. ICML 2026Bottleneck Communication Delay Minimization for Communication-Efficient Decentralized Learning
121. ICML 2026Bounded Hyperbolic Tangent: A Stable and Efficient Alternative to Pre-Layer Normalization in Large Language Models
122. ICML 2026BPDQ: Bit-Plane Decomposition Quantization on a Variable Grid for Large Language Models
123. ICML 2026Break the Block: Dynamic-size Reasoning Blocks for Diffusion Large Language Models via Monotonic Entropy Descent with Reinforcement Learning
124. ICML 2026Breaking the Block: Preserving Data Continuity to Train Superior SAEs for Instruct Models
125. ICML 2026Breaking the Echo Chamber: A Dynamic Ensemble Pruning Perspective on MoE
126. ICML 2026Breaking the Exploration Bottleneck: Rubric-Scaffolded Reinforcement Learning for Open-Ended LLM Reasoning
127. ICML 2026Breaking the Self-Confirming Loop: Diagnosing and Mitigating Systemic Reward Bias in Self-Rewarding RL
128. ICML 2026BRIDGE: Predicting Human Task Completion Time From Model Performance
129. ICML 2026BRIDGE: Triangular Fixed-Point Refinement for Long-Horizon Persona Consistency
130. ICML 2026Bridging the Knowledge-Prediction Gap in LLMs on Multiple-Choice Questions
131. ICML 2026Bring Future Vision: Dynamic Computation Allocation Guided by Lightweight Feature Forecaster
132. ICML 2026Bringing Code ALIVE: Optimizing Interactive Frontend Mini-Games via Automated Play and Reinforcement Learning at Scale
133. ICML 2026Broadening the Backdoor Basin: Understanding LLM Backdoors Collapse and Making Backdoors Persistent
134. ICML 2026BrokenMath: A Benchmark for Sycophancy in Theorem Proving with LLMs
135. ICML 2026BroRL: Scaling Reinforcement Learning via Broadened Exploration
136. ICML 2026Cache Coherent Resampling for Efficient Test Time Scaling in LLM Reasoning via Adaptive Sequential Monte Carlo
137. ICML 2026CAMEL: Confidence-Gated Reflection for Reward Modeling
138. ICML 2026Can Agents Generalize to the Open World? Unveiling the Fragility of Static Training in Tool Use
139. ICML 2026Can I Have Your Order? Monte-Carlo Tree Search for Slot Filling Ordering in Diffusion Language Models
140. ICML 2026Can Large Language Models Generalize Procedures Across Representations?
141. ICML 2026Can LLM Agents Stick to the Script? Modeling Commitment in Interactive Narratives
142. ICML 2026Can LLMs Reason Structurally? Benchmarking via the lens of Data Structures
143. ICML 2026CANDI: Hybrid Discrete-Continuous Diffusion Models
144. ICML 2026Capability Traps in DPO
145. ICML 2026Capacity without Access: Reinterpreting the Mid-Depth Spectral Plateau in LLMs
146. ICML 2026Capacity-Aware Mixture Law Enables Efficient LLM Data Optimization
147. ICML 2026Capturing Gaze Shifts for Guidance: Cross-Modal Fusion Enhancement for VLM Hallucination Mitigation
148. ICML 2026CARE: Confounder-Aware Aggregation for Reliable LLM Evaluation
149. ICML 2026CAT-Q: Cost-efficient and Accurate Ternary Quantization for LLMs
150. ICML 2026CATArena: Evaluating Evolutionary Capabilities of Code Agents via Iterative Tournaments

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。