Which India Survives Translation? Narrative Homogenisation Across Indian Oral Traditions in LLMs

arXiv:2608.26123 · cs.CL · Submitted 2026-06-21 · Read on arXiv

cs.CL

Submitted: 2026-06-21

Updated: 2026-08-29

Terminology

• Fidelity — 15× in this paper · explained in 2 episodes
• Cosine Similarity — 9× in this paper · explained in 3 episodes
• Embeddings — 9× in this paper · explained in 2 episodes
• Benchmark — 7× in this paper · explained in 2 episodes
• Accuracy — 6× in this paper · explained in 1 episode
• Alignment — 3× in this paper · explained in 1 episode
• Hallucination — 3× in this paper · explained in 4 episodes
• Large Language Models (LLMs) — 2× in this paper · explained in 6 episodes
• Benchmarking — 1× in this paper · explained in 4 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• Homogeneity — 1× in this paper · explained in 2 episodes
• Trace — 1× in this paper · explained in 2 episodes

Sources

• Should ChatGPT be Biased? Challenges and Risks of Bias in Large Language Models
• Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages
• AI-generated stories favour stability over change: homogeneity and cultural stereotyping in narratives generated by gpt-4o-mini

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