Do Large Language Models Always Tell The Same Stories?

arXiv:2606.17350 · cs.CL, cs.AI · Submitted 2026-06-15 · Read on arXiv

cs.CL, cs.AI

Submitted: 2026-06-15

Updated: 2026-09-02

Code: https://github.com/thennal10/narrative-similarity

Terminology

• LLM judge — 17× in this paper · explained in 2 episodes
• LLM-as-a-Judge — 8× in this paper · explained in 3 episodes
• Core — 6× in this paper · explained in 2 episodes
• Adam — 3× in this paper · explained in 2 episodes
• Annotator Agreement — 3× in this paper · explained in 1 episode
• Embeddings — 3× in this paper · explained in 2 episodes
• Fine-Tuning — 3× in this paper · explained in 5 episodes
• Commentary — 2× in this paper · explained in 2 episodes
• Cosine Similarity — 2× in this paper · explained in 3 episodes
• Homogeneity — 2× in this paper · explained in 2 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Benchmark — 1× in this paper · explained in 2 episodes
• Calibration — 1× in this paper · explained in 7 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Direct Preference Optimization (DPO) — 1× in this paper · explained in 9 episodes
• Exposure Bias — 1× in this paper · explained in 2 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Mode Collapse — 1× in this paper · explained in 2 episodes
• Positional Bias — 1× in this paper · explained in 2 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes

Sources

• SemEval-2026 Task 4: Narrative Story Similarity and Narrative Representation Learning
• LLMs Generate Kitsch
• EQ-Bench: An Emotional Intelligence Benchmark for Large Language Models
• Gemini Embedding: Generalizable Embeddings from Gemini
• OpenAI GPT-5 System Card
• Restoring Exploration after Post-Training: Latent Exploration Decoding for Large Reasoning Models
• Gemma 3 Technical Report
• Kimi K2.5: Visual Agentic Intelligence
• Olmo 3
• Qwen3 Technical Report
• Verbalized Sampling: How to Mitigate Mode Collapse and Unlock LLM Diversity

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