社会层面 · accountability transparency and interpretability论文趋势 2023–2026
AI 社会议题：accountability_transparency_and_interpretability
统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 3,411 篇被归入该主题的论文。
主要结论
- 社会层面 · accountability transparency and interpretability论文从 2023 年的 301 篇增长到 2026 年的 1,357 篇，三年间扩大到约 4.5 倍。
- NeurIPS 是发社会层面 · accountability transparency and interpretability论文最多的会议，2023–2026 年共 1,275 篇，占四个会议总量的 37%。
- 交叉方向里涨得最快的是社会层面 · privacy：同时属于两个主题的论文从 2023 年的 0 篇增至 2026 年的 93 篇。
- 在「对齐与负责任 AI」的 5 个主题里，它的 2026 年论文数排第 2；同组增长最快的社会层面 · safety是 93 倍，社会层面 · accountability transparency and interpretability是 4.5 倍。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 2023 | 82 | 57 | 94 | 68 | 301 |
| 2024 | 255 | 83 | 152 | 99 | 589 |
| 2025 | 522 | 211 | 337 | 94 | 1,164 |
| 2026 | 416 | 292 | 541 | 108 | 1,357 |
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
- NeurIPS 2026A Unifying Perspective on Language Model Interpretability
- ICML 2026$\texttt{PRISM}$:A 3D Probabilistic Neural Representation for Interpretable Shape Modeling
- ICLR 2026Automated Interpretability Metrics Do Not Distinguish Trained and Random Transformers
- CVPR 2026Beyond Matching to Tiles Bridging Unaligned Aerial and Satellite Views
- NeurIPS 2025$\mathcal{X}^2$-DFD: A framework for e$\mathcal{X}$plainable and e$\mathcal{X}$tendable Deepfake Detection
- ICML 2025(How) Can Transformers Predict Pseudo-Random Numbers?
- ICLR 2025Adaptive Transformer Programs: Bridging the Gap Between Performance and Interpretability in Transformers
- CVPR 2025Attribute-formed Class-specific Concept Space: Endowing Language Bottleneck Model with Better Interpretability and Scalability
- NeurIPS 20242D-OOB: Attributing Data Contribution Through Joint Valuation Framework
- ICML 2024Attention Meets Post-hoc Interpretability: A Mathematical Perspective
- ICLR 2024"What Data Benefits My Classifier?" Enhancing Model Performance and Interpretability through Influence-Based Data Selection
- CVPR 2024Decompose-and-Compose: A Compositional Approach to Mitigating Spurious Correlation
- NeurIPS 2023(S)GD over Diagonal Linear Networks: Implicit bias, Large Stepsizes and Edge of Stability
- ICML 2023A Modern Look at the Relationship between Sharpness and Generalization
- ICLR 2023Deep Learning From Crowdsourced Labels: Coupled Cross-Entropy Minimization, Identifiability, and Regularization
- CVPR 2023Analyzing and Diagnosing Pose Estimation With Attributions
- NeurIPS 2026AdKnob: Ad Intensity Control and Labeling for LLM-Native Advertising
- ICML 2026$\texttt{ShaplEIG}$: Bayesian Experimental Design for Shapley Value Estimation
- ICLR 2026Bandits with Single-Peaked Preferences and Limited Resources
- CVPR 2026IEBGLAn Interpretability-Enhanced Brain Graph Learning Framework with LLM-Instructed Topology and
全部社会层面 · accountability transparency and interpretability论文
共 1,275 篇，第 8 / 26 页
- NeurIPS 2026The Algorithm Is Not the Behavior: Learned Priors Override Look-Ahead in a Chess-Playing Neural Network
- NeurIPS 2026The Alignment Tax Concentrates in Output Projections
- NeurIPS 2026The BatchNorm Illusion: Diagnosing Normalization Artifacts in Machine Unlearning Evaluation
- NeurIPS 2026The Benefits of Temporal Correlations: SGD Efficiently Learns k-Juntas from Random Walks
- NeurIPS 2026The Geometric Inductive Bias of Grokking: Bypassing Phase Transitions via Architectural Topology
- NeurIPS 2026The Geometric Wall: Manifold Structure Predicts Layerwise Sparse Autoencoder Scaling Laws
- NeurIPS 2026The Interplay of Data Structure and Imbalance in the Learning Dynamics of Diffusion Models
- NeurIPS 2026The Kernel Reality Check: Benchmarking and Distilling Efficient Attention at Scale
- NeurIPS 2026The Limits of AI-Driven Allocation: Optimal Screening under Aleatoric Uncertainty
- NeurIPS 2026The Panel Complexity of Sortition: Is 12 Angry Men Enough?
- NeurIPS 2026The parameters in weight-sparse transformers are interpretable
- NeurIPS 2026The Piggyback Hypothesis of Generalization: Explaining and Mitigating Emergent Misalignment
- NeurIPS 2026The Rate-Distortion-Polysemanticity Tradeoff in SAEs
- NeurIPS 2026The Scaling Paradox of Tool-Calling LLM Agents Under Realistic MCP Faults
- NeurIPS 2026The Structural Bias of $\ell_2$-Regularized Cross-Entropy Heads in Class-Incremental Learning: Characterization, Limits, and a Gauge-Anchoring Fix
- NeurIPS 2026The SuperActivator Mechanism: Transformers Concentrate Reliable Concept Signals in the Tail
- NeurIPS 2026Tight PAC-Bayes Generalisation Guarantees for Large Language Model Safety Monitoring
- NeurIPS 2026Topological Periodicity Test (TopPT) via Confidence Bound of Time-Delay Embeddings
- NeurIPS 2026Toward Optimal Regret in Robust Pricing: Decoupling Corruption and Time
- NeurIPS 2026Towards Differentially Private Reinforcement Learning with General Function Approximation
- NeurIPS 2026Towards Fair Graph Generation Without Sensitive Attribute
- NeurIPS 2026Towards Understanding and Measuring Cognitive Atrophy in LLM Behaviour
- NeurIPS 2026Tracing the Cascade: A Topology-Aware Evaluation Framework for Scientific Agent Hallucinations
- NeurIPS 2026Training Language Models to Explain Their Own Computations
- NeurIPS 2026Training ML Models with Predictable Failures
- NeurIPS 2026Transfer Entropy as a Measure of Information Flow in VLMs and LLMs
- NeurIPS 2026Transferring Visual Explainability from Self-Explaining to Prediction-Only Vision Transformers via Task Arithmetic
- NeurIPS 2026TraXion: Rethinking Pre-training Frameworks for Mobility and Beyond
- NeurIPS 2026TriBet: Relative E-values for Online Machine-generated Text Detection
- NeurIPS 2026TRIDENT: Post-Selection Evidence Accountability for Token-Efficient RAG
- NeurIPS 2026TrustMod-SM: A Multi-Axis Benchmark for Evaluating Trustworthiness of LLMs in Social Media Content Moderation
- NeurIPS 2026Two Speeds of Learning: A Representation-Readout Decomposition of Grokking and Double Descent
- NeurIPS 2026Uncovering Hidden Propensities in Language Models via Limited-Parameter Finetuning
- NeurIPS 2026Uncovering the latent structure of interwoven population and temporal codes
- NeurIPS 2026Understanding and Defending VLM Jailbreaks via Jailbreak-Related Representation Shift
- NeurIPS 2026Understanding and Mitigating Under-Confidence in GNNs from the Final Layer
- NeurIPS 2026Understanding Private Evolution as Learning-Augmented Clustering
- NeurIPS 2026Uniform Diffusion Models revisited: Leave-One-Out Denoiser and Absorbing State Reformulation
- NeurIPS 2026Uniform Spectral Growth under Factor-wise Muon Orthogonalization in Matrix Factorization and LoRA
- NeurIPS 2026Uniform Stability and Generalization Error of GD and SGD on Fixed-Point Parameters
- NeurIPS 2026Unifying Partner and Environment Diversity to Improve Human-AI Coordination
- NeurIPS 2026UniVer: A Unified Perspective for Multi-step and Multi-draft Speculative Decoding
- NeurIPS 2026Unsupervised Unlearnable Segmentation via Semantic Structure Disruption
- NeurIPS 2026Untrusted Content Masking for Web Agents with Security Guarantees
- NeurIPS 2026Values Are Not Single Labels: Distributional Value Profiling Across Groups and Contexts
- NeurIPS 2026Verified-Source Authority Is Not Generic Sycophancy: Cue-Family Decomposition of LLM Compliance
- NeurIPS 2026VerifyMAS: Hypothesis Verification for Failure Attribution in LLM Multi-Agent Systems
- NeurIPS 2026VIGOR: Benchmarking Visual Rationale Correctness in Multimodal Large Language Models
- NeurIPS 2026Watermarking as a Learned Intrinsic Property of Diffusion Models
- NeurIPS 2026Watermarking Without Standards Is Not AI Governance
在 Claude、Cursor 里直接问这个趋势
接上 Paperlist MCP 后，写综述、挑方向或准备投稿时，不用离开对话框就能拿到这页的数字：每年各会议的论文数、增长倍数、涨得最快的子方向和代表论文，AI 会按你的问题整理。
可以直接复制这句话问 AI
用 paperlist 查社会层面 · accountability transparency and interpretability在 NeurIPS 2023–2026 的论文趋势，哪一年涨得最快？
AI 会调用的工具：get_topic_stats {"topic": "social-accountability-transparency-and-interpretability"}
常见问题
- 2023–2026 年四大会议一共有多少篇社会层面 · accountability transparency and interpretability论文？
- 共 3,411 篇，按年份分别是 2023 年 301 篇、2024 年 589 篇、2025 年 1,164 篇、2026 年 1,357 篇。
- NeurIPS 2026 有多少篇社会层面 · accountability transparency and interpretability论文？
- NeurIPS 2026 有 416 篇社会层面 · accountability transparency and interpretability论文，上一届是 522 篇。
- ICLR 2026 有多少篇社会层面 · accountability transparency and interpretability论文？
- ICLR 2026 有 292 篇社会层面 · accountability transparency and interpretability论文，上一届是 211 篇。
- ICML 2026 有多少篇社会层面 · accountability transparency and interpretability论文？
- ICML 2026 有 541 篇社会层面 · accountability transparency and interpretability论文，上一届是 337 篇。
- CVPR 2026 有多少篇社会层面 · accountability transparency and interpretability论文？
- CVPR 2026 有 108 篇社会层面 · accountability transparency and interpretability论文，上一届是 94 篇。
- 哪个会议的社会层面 · accountability transparency and interpretability论文最多？
- NeurIPS，2023–2026 年共 1,275 篇。