Loom: Weaving Diagnostic Strands into Free-Text Consensus via Embedding-Space Reweighting

arXiv:2609.02649 · cs.AI, cs.CL, cs.LG · Submitted 2026-09-02 · Read on arXiv

cs.AI, cs.CL, cs.LG

Submitted: 2026-09-02

Updated: 2026-09-02

Comments: Accepted to EMNLP 2026

Code: https://github.com/microsoft/OpenRCA

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Accuracy — 17× in this paper · explained in 1 episode
• Benchmark — 16× in this paper · explained in 2 episodes
• Diagnostic Strand — 15× in this paper
• Redundancy — 12× in this paper · explained in 2 episodes
• Large Language Model — 7× in this paper
• Aggregation — 6× in this paper · explained in 1 episode
• Hallucination — 6× in this paper · explained in 3 episodes
• Embeddings — 4× in this paper · explained in 2 episodes
• Subject Matter Expert — 4× in this paper
• Trace — 4× in this paper · explained in 2 episodes
• Ablation — 3× in this paper · explained in 1 episode
• Consistency — 3× in this paper · explained in 3 episodes
• RAG — 3× in this paper · explained in 3 episodes
• Root Cause Analysis — 3× in this paper
• Alignment — 2× in this paper · explained in 1 episode
• Large Language Model (LLM) — 2× in this paper · explained in 3 episodes
• Self-consistency — 2× in this paper · explained in 2 episodes
• AI Agents — 1× in this paper · explained in 2 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Agentic Loop — 1× in this paper · explained in 1 episode
• Congestion Notification Packet — 1× in this paper
• Core — 1× in this paper · explained in 2 episodes
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Decoupling — 1× in this paper · explained in 2 episodes
• Explicit Congestion Notification — 1× in this paper
• Generative AI — 1× in this paper · explained in 2 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Hybrid Approach — 1× in this paper · explained in 4 episodes
• LLM judge — 1× in this paper · explained in 2 episodes
• LLM-as-a-Judge — 1× in this paper · explained in 3 episodes
• Priority Flow Control — 1× in this paper
• Query Complexity — 1× in this paper · explained in 2 episodes
• Semantic Alignment — 1× in this paper · explained in 3 episodes

Sources

• Replacing Judges with Juries: Evaluating LLM Generations with a Panel of Diverse Models

Related papers

• MAVEN-T: Reinforced Heterogeneous Distillation for Real-Time Multi-Agent Trajectory Prediction
• Model Discovery Agent: LLM-assisted Bayesian experiment design for data-efficient discovery of mechanistic world models
• The Clinician's Veto: Navigating Trust, Liability, and Uncertainty in Autonomous AI Prescribing
• MindHelper: Closed-Loop Embodied Mental-State Reasoning for Precision Intervention
• Incumbent Advantage: Brand Bias and Cognitive Manipulation Dynamics in LLM Recommendation Systems
• VSAL: A Vision Solver with Adaptive Layouts for Graph Property Detection