Papers with naive prompting-based control

1 papers
Funny or Persuasive, but Not Both: Evaluating Fine-Grained Multi-Concept Control in LLMs (2026.eacl-short)

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Challenge: Large Language Models (LLMs) provide strong generative capabilities, but many applications require explicit and fine-grained control over specific textual concepts.
Approach: They propose a framework for fine-grained controllability for single- and dual-concept scenarios . they find performance drops in the dual-constituency setting, even though chosen concepts should be separable .
Outcome: The proposed framework shows that models struggle with compositionality even when concepts are intuitively independent.

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