Supply-Chain Trust papers, 2023–2026
Model supply chain
Scope: NeurIPS, ICLR, ICML and CVPR, 2023–2026. 91 papers are tagged with this topic.
Key findings
- Supply-Chain Trust went from 9 papers in 2023 to 41 in 2026, roughly 4.6x in three years.
- NeurIPS publishes the most Supply-Chain Trust work: 35 papers from 2023 to 2026, 38% of the four-venue total.
- The fastest-growing overlap is with Simulation for Driving: papers tagged with both rose from 1 in 2023 to 5 in 2026.
- Among the 5 topics under Security and Trust, it ranks #5 by 2026 paper count; the fastest grower in the group, Watermarking, is up 9.3x versus 4.6x here.
Papers per venue
Counts by year and venue
| Year | NeurIPS | ICLR | ICML | CVPR | Total |
|---|---|---|---|---|---|
| 2023 | 5 | 3 | 1 | 0 | 9 |
| 2024 | 3 | 5 | 8 | 5 | 21 |
| 2025 | 8 | 6 | 5 | 1 | 20 |
| 2026 | 19 | 8 | 7 | 7 | 41 |
Representative papers
Spread across years and venues so every edition shows up
- NeurIPS 2026Can We Trust Item Response Theory for AI Evaluation?
- ICML 2026Who can we trust? LLM-as-a-jury for Comparative Assessment
- ICLR 2026Hey, That's My Model! Introducing Chain & Hash, An LLM Fingerprinting Technique
- CVPR 2026Trust-calibrated Collaborative Learning for Long-Tailed Visual Recognition
- NeurIPS 2025Chain-of-Model Learning for Language Model
- ICML 2025Navigating Conflicting Views: Harnessing Trust for Learning
- ICLR 2025Parameter Expanded Stochastic Gradient Markov Chain Monte Carlo
- CVPR 2025Interleaved-Modal Chain-of-Thought
- NeurIPS 2024Chain-of-Thought Unfaithfulness as Disguised Accuracy
- ICML 2024Implicit meta-learning may lead language models to trust more reliable sources
- ICLR 2024Chain of Log-Concave Markov Chains
- CVPR 2024CoG-DQA: Chain-of-Guiding Learning with Large Language Models for Diagram Question Answering
- NeurIPS 2023Supply-Side Equilibria in Recommender Systems
- ICML 2023Synthetic Prompting: Generating Chain-of-Thought Demonstrations for Large Language Models
- ICLR 2023Rethinking skip connection model as a learnable Markov chain
- NeurIPS 2026From Infrastructure to Interface, the AI Value Chain Drives LLM Homogenization
- ICML 2026Covariance estimation using Markov chain Monte Carlo
- ICLR 2026Output Supervision Can Obfuscate the Chain of Thought
- CVPR 2026Cut to the Chase Training-free Multimodal Summarization via Chain-of-Events
- NeurIPS 2025You Can Trust Your Clustering Model: A Parameter-free Self-Boosting Plug-in for Deep Clustering
All Supply-Chain Trust papers
21 papers, page 1 of 1
- ICML 2026Chain-of-Thought Gradient Descent
- ICML 2026Covariance estimation using Markov chain Monte Carlo
- ICML 2026Reasoning about Reasoning: BAPO Bounds on Chain-of-Thought Token Complexity in LLMs
- ICML 2026The Expressive Power of Low Precision Softmax Transformers with (Summarized) Chain-of-Thought
- ICML 2026Thinking in Flow: A Dissipative Stabilization Operator for Robust Autoregressive Reasoning
- ICML 2026When Can We Trust Survival Model Evaluation ?
- ICML 2026Who can we trust? LLM-as-a-jury for Comparative Assessment
- ICML 2025Learning to Trust Bellman Updates: Selective State-Adaptive Regularization for Offline RL
- ICML 2025Lower Bounds for Chain-of-Thought Reasoning in Hard-Attention Transformers
- ICML 2025Navigating Conflicting Views: Harnessing Trust for Learning
- ICML 2025Position: Machine Learning Models Have a Supply Chain Problem
- ICML 2025Speeding up Policy Simulation in Supply Chain RL
- ICML 2024Chain-of-Thought Predictive Control
- ICML 2024Decoding Compressed Trust: Scrutinizing the Trustworthiness of Efficient LLMs Under Compression
- ICML 2024Don't trust your eyes: on the (un)reliability of feature visualizations
- ICML 2024Implicit meta-learning may lead language models to trust more reliable sources
- ICML 2024Keypoint-based Progressive Chain-of-Thought Distillation for LLMs
- ICML 2024Parallel Affine Transformation Tuning of Markov Chain Monte Carlo
- ICML 2024Trust Regions for Explanations via Black-Box Probabilistic Certification
- ICML 2024Trust the Model Where It Trusts Itself - Model-Based Actor-Critic with Uncertainty-Aware Rollout Adaption
- ICML 2023Synthetic Prompting: Generating Chain-of-Thought Demonstrations for Large Language Models
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FAQ
- How many Supply-Chain Trust papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?
- 91 in total: 9 in 2023, 21 in 2024, 20 in 2025, 41 in 2026.
- How many Supply-Chain Trust papers are at NeurIPS 2026?
- NeurIPS 2026 has 19 Supply-Chain Trust papers, versus 8 the year before.
- How many Supply-Chain Trust papers are at ICLR 2026?
- ICLR 2026 has 8 Supply-Chain Trust papers, versus 6 the year before.
- How many Supply-Chain Trust papers are at ICML 2026?
- ICML 2026 has 7 Supply-Chain Trust papers, versus 5 the year before.
- How many Supply-Chain Trust papers are at CVPR 2026?
- CVPR 2026 has 7 Supply-Chain Trust papers, versus 1 the year before.
- Which conference publishes the most Supply-Chain Trust papers?
- NeurIPS, with 35 papers from 2023 to 2026.