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Steven Y. Feng

4 accepted papers

2024

Is Child-Directed Speech Effective Training Data for Language Models?

EMNLP 2024main

While high-performing language models are typically trained on hundreds of billions of words, human children become fluent language users with a much smaller amount of data. What are the features of the data they receive, and how do these features support language modeling objectives? To investigate…

2022

NAREOR: The Narrative Reordering Problem

AAAI 2022technical

Many implicit inferences exist in text depending on how it is structured that can critically impact the text's interpretation and meaning. One such structural aspect present in text with chronology is the order of its presentation. For narratives or stories, this is known as the narrative order. Reo…

2022

PINEAPPLE: Personifying INanimate Entities by Acquiring Parallel Personification Data for Learning Enhanced Generation

COLING 2022main

A personification is a figure of speech that endows inanimate entities with properties and actions typically seen as requiring animacy. In this paper, we explore the task of personification generation. To this end, we propose PINEAPPLE: Personifying INanimate Entities by Acquiring Parallel Personifi…

2022

Retrieve, Caption, Generate: Visual Grounding for Enhancing Commonsense in Text Generation Models

AAAI 2022technical

We investigate the use of multimodal information contained in images as an effective method for enhancing the commonsense of Transformer models for text generation. We perform experiments using BART and T5 on concept-to-text generation, specifically the task of generative commonsense reasoning, or C…