Time, Causality, and Observability Failures in Distributed AI Inference Systems
Fuente:
arXiv
Saved in:
| Main Authors: | Sharma, Ankur, Shah, Deep, Lariviere, David, ElBakoury, Hesham |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Agent Operating Systems (AOS): Integrating Agentic Control Planes into, and Beyond, Traditional Operating Systems
by: Sharma, Ankur, et al.
Published: (2026)
by: Sharma, Ankur, et al.
Published: (2026)
Automatic Failure Attribution and Critical Step Prediction Method for Multi-Agent Systems Based on Causal Inference
by: Ma, Guoqing, et al.
Published: (2025)
by: Ma, Guoqing, et al.
Published: (2025)
Does Inference Scaling Improve Reasoning Faithfulness? A Multi-Model Analysis of Self-Consistency Tradeoffs
by: Mehta, Deep
Published: (2026)
by: Mehta, Deep
Published: (2026)
Abduct, Act, Predict: Scaffolding Causal Inference for Automated Failure Attribution in Multi-Agent Systems
by: West, Alva, et al.
Published: (2025)
by: West, Alva, et al.
Published: (2025)
Early Diagnosis of Wasted Computation in Multi-Agent LLM Systems via Failure-Aware Observability
by: Li, Xianyou, et al.
Published: (2026)
by: Li, Xianyou, et al.
Published: (2026)
Taxonomy of the Retrieval System Framework: Pitfalls and Paradigms
by: Shah, Deep, et al.
Published: (2026)
by: Shah, Deep, et al.
Published: (2026)
AI-driven View Guidance System in Intra-cardiac Echocardiography Imaging
by: Huh, Jaeyoung, et al.
Published: (2024)
by: Huh, Jaeyoung, et al.
Published: (2024)
Agentic AI Process Observability: Discovering Behavioral Variability
by: Fournier, Fabiana, et al.
Published: (2025)
by: Fournier, Fabiana, et al.
Published: (2025)
Towards Causal Representation Learning with Observable Sources as Auxiliaries
by: Kim, Kwonho, et al.
Published: (2025)
by: Kim, Kwonho, et al.
Published: (2025)
Can We Trust AI Explanations? Evidence of Systematic Underreporting in Chain-of-Thought Reasoning
by: Mehta, Deep Pankajbhai
Published: (2025)
by: Mehta, Deep Pankajbhai
Published: (2025)
Beyond Attack Success Rate: Temporal Logit Observability for LLM Safety Failures
by: Park, Junyoung, et al.
Published: (2026)
by: Park, Junyoung, et al.
Published: (2026)
Causal Order: The Key to Leveraging Imperfect Experts in Causal Inference
by: Vashishtha, Aniket, et al.
Published: (2023)
by: Vashishtha, Aniket, et al.
Published: (2023)
Failures in Perspective-taking of Multimodal AI Systems
by: Leonard, Bridget, et al.
Published: (2024)
by: Leonard, Bridget, et al.
Published: (2024)
Inference Time Causal Probing in LLMs
by: Khorasani, Sadegh, et al.
Published: (2026)
by: Khorasani, Sadegh, et al.
Published: (2026)
CausalAgent: A Conversational Multi-Agent System for End-to-End Causal Inference
by: Zhu, Jiawei, et al.
Published: (2026)
by: Zhu, Jiawei, et al.
Published: (2026)
Multi-View Causal Representation Learning with Partial Observability
by: Yao, Dingling, et al.
Published: (2023)
by: Yao, Dingling, et al.
Published: (2023)
The Silent Vote: Improving Zero-Shot LLM Reliability by Aggregating Semantic Neighborhoods
by: Badhe, Sanket, et al.
Published: (2026)
by: Badhe, Sanket, et al.
Published: (2026)
Coherent Without Grounding, Grounded Without Success: Observability and Epistemic Failure
by: Sartori, Camilo Chacón
Published: (2026)
by: Sartori, Camilo Chacón
Published: (2026)
Provable Distributional Value Iteration under Partial Observability
by: Preuett III, Larry, et al.
Published: (2025)
by: Preuett III, Larry, et al.
Published: (2025)
CausalTrace: A Neurosymbolic Causal Analysis Agent for Smart Manufacturing
by: Shyalika, Chathurangi, et al.
Published: (2025)
by: Shyalika, Chathurangi, et al.
Published: (2025)
RobustDebias: Debiasing Language Models using Distributionally Robust Optimization
by: Gandhi, Deep, et al.
Published: (2026)
by: Gandhi, Deep, et al.
Published: (2026)
A Sparsity Principle for Partially Observable Causal Representation Learning
by: Xu, Danru, et al.
Published: (2024)
by: Xu, Danru, et al.
Published: (2024)
Causality-informed Anomaly Detection in Partially Observable Sensor Networks: Moving beyond Correlations
by: Xiao, Xiaofeng, et al.
Published: (2025)
by: Xiao, Xiaofeng, et al.
Published: (2025)
Eliciting Fine-Tuned Transformer Capabilities via Inference-Time Techniques
by: Sharma, Asankhaya
Published: (2025)
by: Sharma, Asankhaya
Published: (2025)
Orientability of Causal Relations in Time Series using Summary Causal Graphs and Faithful Distributions
by: Loranchet, Timothée, et al.
Published: (2025)
by: Loranchet, Timothée, et al.
Published: (2025)
Kolmogorov-Arnold Networks for Time Series Granger Causality Inference
by: Liu, Meiliang, et al.
Published: (2025)
by: Liu, Meiliang, et al.
Published: (2025)
Deconfounded Time Series Forecasting: A Causal Inference Approach
by: Gao, Wentao, et al.
Published: (2024)
by: Gao, Wentao, et al.
Published: (2024)
This Time is Different: An Observability Perspective on Time Series Foundation Models
by: Cohen, Ben, et al.
Published: (2025)
by: Cohen, Ben, et al.
Published: (2025)
Causal Imitation Learning under Expert-Observable and Expert-Unobservable Confounding
by: Shao, Daqian, et al.
Published: (2025)
by: Shao, Daqian, et al.
Published: (2025)
From What Ifs to Insights: Counterfactuals in Causal Inference vs. Explainable AI
by: Shmueli, Galit, et al.
Published: (2025)
by: Shmueli, Galit, et al.
Published: (2025)
Placement Semantics for Distributed Deep Learning: A Systematic Framework for Analyzing Parallelism Strategies
by: Mehta, Deep Pankajbhai
Published: (2026)
by: Mehta, Deep Pankajbhai
Published: (2026)
Failure Modes in LLM Systems: A System-Level Taxonomy for Reliable AI Applications
by: Vinay, Vaishali
Published: (2025)
by: Vinay, Vaishali
Published: (2025)
Growth Patterns of Inference
by: Sharma, Abhishek
Published: (2025)
by: Sharma, Abhishek
Published: (2025)
Long-Tail Knowledge in Large Language Models: Taxonomy, Mechanisms, Interventions and Implications
by: Badhe, Sanket, et al.
Published: (2026)
by: Badhe, Sanket, et al.
Published: (2026)
CausalFlow: Causal Attribution and Counterfactual Repair for LLM Agent Failures
by: Bonagiri, Akash, et al.
Published: (2026)
by: Bonagiri, Akash, et al.
Published: (2026)
Real-Time Out-of-Distribution Failure Prevention via Multi-Modal Reasoning
by: Ganai, Milan, et al.
Published: (2025)
by: Ganai, Milan, et al.
Published: (2025)
Causal Inference in Energy Demand Prediction
by: Ma, Chutian, et al.
Published: (2025)
by: Ma, Chutian, et al.
Published: (2025)
Debiasing Reward Models via Causally Motivated Inference-Time Intervention
by: Shinoda, Kazutoshi, et al.
Published: (2026)
by: Shinoda, Kazutoshi, et al.
Published: (2026)
Serving Heterogeneous LoRA Adapters in Distributed LLM Inference Systems
by: Jaiswal, Shashwat, et al.
Published: (2025)
by: Jaiswal, Shashwat, et al.
Published: (2025)
Deep Learning-based Group Causal Inference in Multivariate Time-series
by: Ahmad, Wasim, et al.
Published: (2024)
by: Ahmad, Wasim, et al.
Published: (2024)
Similar Items
-
Agent Operating Systems (AOS): Integrating Agentic Control Planes into, and Beyond, Traditional Operating Systems
by: Sharma, Ankur, et al.
Published: (2026) -
Automatic Failure Attribution and Critical Step Prediction Method for Multi-Agent Systems Based on Causal Inference
by: Ma, Guoqing, et al.
Published: (2025) -
Does Inference Scaling Improve Reasoning Faithfulness? A Multi-Model Analysis of Self-Consistency Tradeoffs
by: Mehta, Deep
Published: (2026) -
Abduct, Act, Predict: Scaffolding Causal Inference for Automated Failure Attribution in Multi-Agent Systems
by: West, Alva, et al.
Published: (2025) -
Early Diagnosis of Wasted Computation in Multi-Agent LLM Systems via Failure-Aware Observability
by: Li, Xianyou, et al.
Published: (2026)