activity
20242026
collaborators

7 papers

cs.CL2026

The Nuts and Bolts of Natural Language to SQL Translation: A Systematic Analysis of Model Pipeline Optimisation Approaches and their Interactions

Filip Klubicka, Vasudevan Nedumpozhimana, Sneha Rautmare +3

In the age of large language models, Natural Language to SQL (NL2SQL) translation remains an open problem with many useful applications. We explore interactions between several NL2…

cs.IR2026

Log-Insight: Automating Microservice Incident Diagnosis via Neuro-Symbolic Log Analysis

Carlos Garcia-Hernandez, Aymane Abdali, Guangyu Wu +4

Diagnosing production incidents in large-scale microservice systems is time-critical for Site Reliability Engineers (SREs). A single 30-minute incident window in our deployment can…

cs.LG2026

Adversarial Causal Tuning for Realistic Time-series Generation

Nikolaos Gkorgkolis, Nikolaos Kougioulis, MingXue Wang +4

We address the problem of generating simulated, yet realistic, time-series data from a causal model with the same observational and interventional distributions as a given real dat…

cs.LG2026

Efficient Multi-Cohort Inference for Long-Term Effects and Lifetime Value in A/B Testing with User Learning

Dario Simionato, Andrea Tonon, Mingxue Wang +3

In streaming platforms churn is extremely costly, yet A/B tests are typically evaluated using outcomes observed within a limited experimental horizon. Even when both short- and pre…

cs.LG2026

Large Causal Models for Temporal Causal Discovery

Nikolaos Kougioulis, Nikolaos Gkorgkolis, MingXue Wang +4

Causal discovery for both cross-sectional and temporal data has traditionally followed a dataset-specific paradigm, where a new model is fitted for each individual dataset. Such an…

cs.SE2025

RADICE: Causal Graph Based Root Cause Analysis for System Performance Diagnostic

Andrea Tonon, Meng Zhang, Bora Caglayan +4

Root cause analysis is one of the most crucial operations in software reliability regarding system performance diagnostic. It aims to identify the root causes of system performance…