Papers by Samraj Moorjani
Audience-Centric Natural Language Generation via Style Infusion (2022.findings-emnlp)
Copied to clipboard
| Challenge: | Existing approaches to text style transfer (TST) with large volumes of parallel or non-parallel data are limiting for two reasons: it is difficult to collect large volumes and some stylistic objectives are hard to define without audience feedback. |
| Approach: | They propose a task of style infusion - infusing stylistic preferences of audiences into pretrained language generation models by leveraging pairwise human judgments to bootstrap a style analysis model and augment a seed set of judgments. |
| Outcome: | The proposed method generates compelling stylized examples with generic text prompts while balancing fluency and style adoption. |
CEV-LM: Controlled Edit Vector Language Model for Shaping Natural Language Generations (2024.eacl-long)
Copied to clipboard
| 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. |