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Playing Along: Learning a Double-Agent Defender for Belief Steering via Theory of Mind RPA-Check: A Multi-Stage Automated Framework for Evaluating Dynamic LLM-based Role-Playing Agents A Triadic Suffix Tokenization Scheme for Numerical Reasoning Hidden Measurement Error in LLM Pipelines Distorts Annotation, Evaluation, and Benchmarking Synthius-Mem: Brain-Inspired Hallucination-Resistant Persona Memory Achieving 94.4% Memory Accuracy and 99.6% Adversarial Robustness on LoCoMo Time is Not a Label: Continuous Phase Rotation for Temporal Knowledge Graphs and Agentic Memory NovBench: Evaluating Large Language Models on Academic Paper Novelty Assessment Policy Split: Incentivizing Dual-Mode Exploration in LLM Reinforcement with Dual-Mode Entropy Regularization METER: Evaluating Multi-Level Contextual Causal Reasoning in Large Language Models Think Before you Write: QA-Guided Reasoning for Character Descriptions in Books METRO: Towards Strategy Induction from Expert Dialogue Transcripts for Non-collaborative Dialogues Retrieval as Generation: A Unified Framework with Self-Triggered Information Planning Do LLMs Know Tool Irrelevance? 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Simulating Organized Group Behavior: New Framework, Benchmark, and Analysis Spoiler Alert: Narrative Forecasting as a Metric for Tension in LLM Storytelling Claim2Vec: Embedding Fact-Check Claims for Multilingual Similarity and Clustering GIANTS: Generative Insight Anticipation from Scientific Literature Many-Tier Instruction Hierarchy in LLM Agents Interactive ASR: Towards Human-Like Interaction and Semantic Coherence Evaluation for Agentic Speech Recognition Regime-Conditional Retrieval: Theory and a Transferable Router for Two-Hop QA ASTRA: Adaptive Semantic Tree Reasoning Architecture for Complex Table Question Answering Revisiting the Capacity Gap in Chain-of-Thought Distillation from a Practical Perspective Dictionary-Aligned Concept Control for Safeguarding Multimodal LLMs $p1$: Better Prompt Optimization with Fewer Prompts Every Response Counts: Quantifying Uncertainty of LLM-based Multi-Agent Systems through Tensor Decomposition Skip-Connected Policy Optimization for Implicit Advantage PRAGMA: Revolut Foundation Model Linear Representations of Hierarchical Concepts in Language Models Generating High Quality Synthetic Data for Dutch Medical Conversations HumorGen: Cognitive Synergy for Humor Generation in Large Language Models via Persona-Based Distillation Toward Generalized Cross-Lingual Hateful Language Detection with Web-Scale Data and Ensemble LLM Annotations Self-Calibrating Language Models via Test-Time Discriminative Distillation Re-Mask and Redirect: Exploiting Denoising Irreversibility in Diffusion Language Models H-AdminSim: A Multi-Agent Simulator for Realistic Hospital Administrative Workflows with FHIR Integration Reasoning Models Will Sometimes Lie About Their Reasoning
LLM-Augmented Knowledge Base Construction For Root Cause Analysis
Nguyen Phuc Tran, Brigitte Jaumard, Oscar Delgado, Tristan Glata · 2026-01-10 · via cs.CL updates on arXiv.org

Communications networks now form the backbone of our digital world, with fast and reliable connectivity. However, even with appropriate redundancy and failover mechanisms, it is difficult to guarantee "five 9s" (99.999 %) reliability, requiring rapid and accurate root cause analysis (RCA) during outages. In the event of an outage, rapid and accurate RCA becomes essential to restore service and prevent future disruptions. This study evaluates three Large Language Model (LLM) methodologies - Fine-Tuning, RAG, and a Hybrid approach - for constructing a Root Cause Analysis (RCA) Knowledge Base from support tickets. We compare their performance using a comprehensive suite of lexical and semantic similarity metrics. Our experiments on a real industrial dataset demonstrate that the generated knowledge base provides an excellent starting point for accelerating RCA tasks and improving network resilience.

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