A new 263k TTCW-annotated story dataset shows non-reasoning fine-tuning of Qwen3 models outperforms reasoning-supervised fine-tuning for fixed-format long-form literary review generation.
What Matters in Evaluating Book-Length Stories? A Systematic Study of Long Story Evaluation
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
cs.CL 2years
2026 2representative citing papers
A domain-agnostic framework extracts perspectives from book reviews showing LLMs underrepresent rarer viewpoints relative to human text.
citing papers explorer
-
When Reasoning Supervision Hurts: TTCW-Based Long-Form Literary Review Generation
A new 263k TTCW-annotated story dataset shows non-reasoning fine-tuning of Qwen3 models outperforms reasoning-supervised fine-tuning for fixed-format long-form literary review generation.
-
Evaluating Pluralism in LLMs through Latent Perspectives
A domain-agnostic framework extracts perspectives from book reviews showing LLMs underrepresent rarer viewpoints relative to human text.