A Semiotics-Aware Framework for Evaluating Fidelity and Coverage in Natural Language Generation

arXiv:2609.26527 · cs.CL, cs.AI · Submitted 2026-09-22 · Read on arXiv

cs.CL, cs.AI

Submitted: 2026-09-22

Updated: 2026-09-22

Code: https://github.com/AlexVerine/pr-4-llm

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

Terminology

• Fidelity — 25× in this paper · explained in 2 episodes
• Embeddings — 23× in this paper · explained in 2 episodes
• Semiotic Coverage — 20× in this paper
• Semiotic Fidelity — 17× in this paper
• Alignment — 14× in this paper · explained in 1 episode
• Transformer — 8× in this paper · explained in 2 episodes
• Core — 6× in this paper · explained in 2 episodes
• Ablation — 4× in this paper · explained in 1 episode
• Generative Model — 4× in this paper · explained in 2 episodes
• Generative Models — 4× in this paper · explained in 2 episodes
• Natural Language Generation — 4× in this paper
• LLM-as-a-Judge — 3× in this paper · explained in 3 episodes
• LLM judge — 2× in this paper · explained in 2 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Benchmark — 1× in this paper · explained in 2 episodes
• Benchmarking — 1× in this paper · explained in 3 episodes
• Clustering — 1× in this paper · explained in 2 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Masked Language Model — 1× in this paper
• Model-Agnostic — 1× in this paper · explained in 2 episodes
• Named Entity Recognition (NER) — 1× in this paper · explained in 2 episodes
• Objective Function — 1× in this paper · explained in 2 episodes
• Pairwise Comparisons — 1× in this paper · explained in 2 episodes
• Quantization — 1× in this paper · explained in 12 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Semantic Role Labeling — 1× in this paper
• Sparsity — 1× in this paper · explained in 4 episodes

Sources

• DeBERTa: Decoding-enhanced BERT with Disentangled Attention
• The Semiotic Channel Principle: Measuring the Capacity for Meaning in LLM Communication
• RoBERTa: A Robustly Optimized BERT Pretraining Approach
• Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference
• BERTScore: Evaluating Text Generation with BERT

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