# DACRI: Decision-Aware Causal Intervention Ranking for Critical Supply Chains

arXiv: https://arxiv.org/abs/2608.11154 · HTML: https://mlsanity.com/paper/2608.11154/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 12 of its 29 references that are in the map.
- First posted on arXiv 11 Aug 2026.

## Builds on (most cited first, 12 of 12)

- [Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks](https://mlsanity.com/paper/2005.11401/) (2020)
- [FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation](https://mlsanity.com/paper/2305.14251/) (2023)
- [SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Models](https://mlsanity.com/paper/2303.08896/) (2023)
- [DYNOTEARS: Structure Learning from Time-Series Data](https://mlsanity.com/paper/2002.00498/) (2020)
- [Multivariate Time-series Anomaly Detection via Graph Attention Network](https://mlsanity.com/paper/2009.02040/) (2020)
- [Time-Series Anomaly Detection Service at Microsoft](https://mlsanity.com/paper/1906.03821/) (2019)
- [Discovering contemporaneous and lagged causal relations in autocorrelated nonlinear time series datasets](https://mlsanity.com/paper/2003.03685/) (2020)
- [Hybrid Meta-learners for Estimating Heterogeneous Treatment Effects](https://mlsanity.com/paper/2506.13680/) (2025)
- [Are Anomaly Scores Telling the Whole Story? A Benchmark for Multilevel Anomaly Detection](https://mlsanity.com/paper/2411.14515/) (2024)
- [Triage in Software Engineering: A Systematic Review of Research and Practice](https://mlsanity.com/paper/2511.08607/) (2025)
- [Alignment of Cybersecurity Incident Prioritisation with Incident Response Management Maturity Capabilities](https://mlsanity.com/paper/2410.02259/) (2024)
- [A Feature Engineering Approach for Business Impact-Oriented Failure Detection in Distributed Instant Payment Systems](https://mlsanity.com/paper/2510.21710/) (2025)

## Built on by (most cited first, 1 of 1)

- [Style Over Substance: Content-Invariant Wrappers Flip LLM Safety-Judge Verdicts](https://mlsanity.com/paper/2609.08236/) (2026)

## Abstract (arXiv)

Detecting or attributing a supply-chain disruption is not the same as selecting the intervention that maximizes recoverable net value. We present CriticalSCM-Bench v1, a controlled synthetic benchmark with causal ground truth, paired factual/counterfactual rollouts, and an explicit net-value objective. Relative to a full-information train-selected static benchmark, LambdaMART improves median normalized net value by 5.7--16.2%, with paired statistical support on the semiconductor and critical-material archetypes but not on digital infrastructure. On digital infrastructure, a domain-informed constant-buffer policy remains stronger, showing that greater model complexity is not uniformly justified. Across partial and delayed settings, LambdaMART retains 33--75% of full-clamp value. Stress tests further show that intervention fidelity, timing, cost, and held-out disruptions can alter policy ordering. Critical materials show the weakest out-of-distribution retention. Separately, a guarded explanation study over 540 generations preserves every fixed intervention decision after deterministic validation and template fallback, although exact wording remains unstable. Within this controlled setting, the results identify regimes in which adaptive ranking adds value and those in which simpler structural policies remain preferable.