LAURA: Knowledge Distillation for Interpretable Ambiguous Clause Identification in Legal Contracts

arXiv:2609.36707 · cs.CL · Submitted 2026-09-29 · Read on arXiv

cs.CL

Submitted: 2026-09-29

Updated: 2026-09-29

Terminology

• Accuracy — 13× in this paper · explained in 1 episode
• Interpretability — 9× in this paper · explained in 15 episodes
• Distillation — 6× in this paper · explained in 2 episodes
• Fine-Tuning — 6× in this paper · explained in 5 episodes
• Knowledge Distillation — 5× in this paper · explained in 11 episodes
• Chain-of-Thought (CoT) — 4× in this paper · explained in 4 episodes
• Adam — 3× in this paper · explained in 2 episodes
• Alignment — 2× in this paper · explained in 1 episode
• Transformer — 2× in this paper · explained in 2 episodes
• Actor — 1× in this paper · explained in 3 episodes
• AdamW Optimizer — 1× in this paper · explained in 1 episode
• Benchmark — 1× in this paper · explained in 2 episodes
• Benchmarking — 1× in this paper · explained in 3 episodes
• Chain-of-Thought (CoT) Prompting — 1× in this paper · explained in 3 episodes
• Core — 1× in this paper · explained in 2 episodes
• Hallucination — 1× in this paper · explained in 3 episodes
• Hierarchical Classification — 1× in this paper · explained in 2 episodes
• Self Correction — 1× in this paper

Sources

• RoBERTa: A Robustly Optimized BERT Pretraining Approach
• Small Language Models: Survey, Measurements, and Insights
• A Survey of Small Language Models
• Small Language Models (SLMs) Can Still Pack a Punch: A survey (updated 2026)
• LLaMA: Open and Efficient Foundation Language Models
• Qwen2 Technical Report
• Benchmarking Multi-Step Legal Reasoning and Analyzing Chain-of-Thought Effects in Large Language Models

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