CEV-LM: Controlled Edit Vector Language Model for Shaping Natural Language Generations (2024.eacl-long)
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| Challenge: | Existing control approaches primarily adjust the semantic (e.g., emotion, topics), structural (e-speech, parts-of-seech), and lexical (el-s-sp-s) properties of text, but are insufficient to accomplish complex objectives such as pacing which control the complexity and readability of the text. |
| Approach: | They propose a lightweight semi-autoregressive language model that uses edit vectors to control three complementary metrics that quantify the shape of text. |
| Outcome: | The proposed model provides significantly more targeted and precise control of speed, volume, and circuitousness while using less training data, and containing fewer parameters. |
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