Supply-Chain Trust papers, 2023–2026

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.

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

35 papers, page 1 of 1

1. NeurIPS 2026A Solvable Model of Chain-of-Thought in In-Context Learning
2. NeurIPS 2026A Tight Hierarchy For Chain of Thought
3. NeurIPS 2026Beyond Suspicious Steps: Ontological Trust in Long-Horizon Agents
4. NeurIPS 2026Can We Trust Item Response Theory for AI Evaluation?
5. NeurIPS 2026Chain of Dual Structures in Transformer Attention
6. NeurIPS 2026Chain-of-Thought Is Not Explainability
7. NeurIPS 2026ComPose: When to Trust Hands for Object Pose Tracking
8. NeurIPS 2026Efficiently Representing Algorithms With Chain-of-Thought Transformers
9. NeurIPS 2026From Infrastructure to Interface, the AI Value Chain Drives LLM Homogenization
10. NeurIPS 2026Not All Routing Drift Is Harmful: Trust-Region Projection for Class-Incremental Learning
11. NeurIPS 2026Reliable Chain-of-Thought via Prefix Consistency
12. NeurIPS 2026SWE-Chain: Benchmarking Coding Agents on Chained Release-Level Package Upgrades
13. NeurIPS 2026TERMINATOR: Learning Optimal Exit Points for Early Stopping in Chain-of-Thought Reasoning
14. NeurIPS 2026Trust Guided Decision Transformer
15. NeurIPS 2026Trust Region Continual Learning as an Implicit Meta-Learner
16. NeurIPS 2026Trust Region Policy Distillation
17. NeurIPS 2026Trust Region Q Adjoint Matching
18. NeurIPS 2026When Alignment Fails: Stabilizing Cross-Dynamics RL with Prototype Trust Regions
19. NeurIPS 2026When the Same Coefficients Reach Different Places: Asymmetric Realizability in Transplanting Tokenizers across Large Language Models
20. NeurIPS 2025Analyzing the Power of Chain of Thought through Memorization Capabilities
21. NeurIPS 2025Attention (as Discrete-Time Markov) Chains
22. NeurIPS 2025Chain-of-Model Learning for Language Model
23. NeurIPS 2025CoT Information: Improved Sample Complexity under Chain-of-Thought Supervision
24. NeurIPS 2025Let Me Think! A Long Chain of Thought Can Be Worth Exponentially Many Short Ones
25. NeurIPS 2025QUT-DV25: A Dataset for Dynamic Analysis of Next-Gen Software Supply Chain Attacks
26. NeurIPS 2025Reasoning by Superposition: A Theoretical Perspective on Chain of Continuous Thought
27. NeurIPS 2025You Can Trust Your Clustering Model: A Parameter-free Self-Boosting Plug-in for Deep Clustering
28. NeurIPS 2024Accelerating Pre-training of Multimodal LLMs via Chain-of-Sight
29. NeurIPS 2024Auditing Local Explanations is Hard
30. NeurIPS 2024Chain-of-Thought Unfaithfulness as Disguised Accuracy
31. NeurIPS 2023Deductive Verification of Chain-of-Thought Reasoning
32. NeurIPS 2023DiffPack: A Torsional Diffusion Model for Autoregressive Protein Side-Chain Packing
33. NeurIPS 2023Predicting mutational effects on protein-protein binding via a side-chain diffusion probabilistic model
34. NeurIPS 2023Supply-Side Equilibria in Recommender Systems
35. NeurIPS 2023Towards Revealing the Mystery behind Chain of Thought: A Theoretical Perspective

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.