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 30 / 47 页

1451. ICML 2025Revolve: Optimizing AI Systems by Tracking Response Evolution in Textual Optimization
1452. ICML 2025Reward Modeling with Ordinal Feedback: Wisdom of the Crowd
1453. ICML 2025Reward-Augmented Data Enhances Direct Preference Alignment of LLMs
1454. ICML 2025Reward-Guided Prompt Evolving in Reinforcement Learning for LLMs
1455. ICML 2025Reward-Guided Speculative Decoding for Efficient LLM Reasoning
1456. ICML 2025Right Now, Wrong Then: Non-Stationary Direct Preference Optimization under Preference Drift
1457. ICML 2025RLEF: Grounding Code LLMs in Execution Feedback with Reinforcement Learning
1458. ICML 2025RLTHF: Targeted Human Feedback for LLM Alignment
1459. ICML 2025Robust Multimodal Large Language Models Against Modality Conflict
1460. ICML 2025Roll the dice & look before you leap: Going beyond the creative limits of next-token prediction
1461. ICML 2025ROPO: Robust Preference Optimization for Large Language Models
1462. ICML 2025RoSTE: An Efficient Quantization-Aware Supervised Fine-Tuning Approach for Large Language Models
1463. ICML 2025RuleAdapter: Dynamic Rules for training Safety Reward Models in RLHF
1464. ICML 2025RWKVQuant: Quantizing the RWKV Family with Proxy Guided Hybrid of Scalar and Vector Quantization
1465. ICML 2025Safe Delta: Consistently Preserving Safety when Fine-Tuning LLMs on Diverse Datasets
1466. ICML 2025Sample, Scrutinize and Scale: Effective Inference-Time Search by Scaling Verification
1467. ICML 2025Satori: Reinforcement Learning with Chain-of-Action-Thought Enhances LLM Reasoning via Autoregressive Search
1468. ICML 2025Scaling Inference-Efficient Language Models
1469. ICML 2025Scaling Laws for Floating–Point Quantization Training
1470. ICML 2025Scaling Laws for Upcycling Mixture-of-Experts Language Models
1471. ICML 2025Scaling Sparse Feature Circuits For Studying In-Context Learning
1472. ICML 2025Scaling Test-Time Compute Without Verification or RL is Suboptimal
1473. ICML 2025Self-Improving Language Models for Evolutionary Program Synthesis: A Case Study on ARC-AGI
1474. ICML 2025SelfCite: Self-Supervised Alignment for Context Attribution in Large Language Models
1475. ICML 2025SepLLM: Accelerate Large Language Models by Compressing One Segment into One Separator
1476. ICML 2025ShadowKV: KV Cache in Shadows for High-Throughput Long-Context LLM Inference
1477. ICML 2025SIMPLEMIX: Frustratingly Simple Mixing of Off- and On-policy Data in Language Model Preference Learning
1478. ICML 2025SkipGPT: Each Token is One of a Kind
1479. ICML 2025SliM-LLM: Salience-Driven Mixed-Precision Quantization for Large Language Models
1480. ICML 2025SlimLLM: Accurate Structured Pruning for Large Language Models
1481. ICML 2025SNS-Bench: Defining, Building, and Assessing Capabilities of Large Language Models in Social Networking Services
1482. ICML 2025Soft Reasoning: Navigating Solution Spaces in Large Language Models through Controlled Embedding Exploration
1483. ICML 2025SparseLoRA: Accelerating LLM Fine-Tuning with Contextual Sparsity
1484. ICML 2025Sparsing Law: Towards Large Language Models with Greater Activation Sparsity
1485. ICML 2025SpeCache: Speculative Key-Value Caching for Efficient Generation of LLMs
1486. ICML 2025Speculate, then Collaborate: Fusing Knowledge of Language Models during Decoding
1487. ICML 2025Speculative Prefill: Turbocharging TTFT with Lightweight and Training-Free Token Importance Estimation
1488. ICML 2025Splitting with Importance-aware Updating for Heterogeneous Federated Learning with Large Language Models
1489. ICML 2025Steer LLM Latents for Hallucination Detection
1490. ICML 2025Streamline Without Sacrifice - Squeeze out Computation Redundancy in LMM
1491. ICML 2025Structure-Guided Large Language Models for Text-to-SQL Generation
1492. ICML 2025Synthetic Text Generation for Training Large Language Models via Gradient Matching
1493. ICML 2025Taming Knowledge Conflicts in Language Models
1494. ICML 2025Targeted Low-rank Refinement: Enhancing Sparse Language Models with Precision
1495. ICML 2025Teaching Language Models to Critique via Reinforcement Learning
1496. ICML 2025Teaching Physical Awareness to LLMs through Sounds
1497. ICML 2025Teaching Transformers Causal Reasoning through Axiomatic Training
1498. ICML 2025Test-Time Learning for Large Language Models
1499. ICML 2025Test-Time Preference Optimization: On-the-Fly Alignment via Iterative Textual Feedback
1500. ICML 2025TGDPO: Harnessing Token-Level Reward Guidance for Enhancing Direct Preference Optimization

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。