Shrimai Prabhumoye

Linguistic Markers of Influence in Informal Interactions

2017

There has been a long standing interest in understanding 'Social Influence' both in Social Sciences and in Computational Linguistics. In this paper, we present a novel approach to study and measure interpersonal influence in daily …

EIGEN: Event Influence GENeration using Pre-trained Language Models

2020 · arXiv (Cornell University)

Reasoning about events and tracking their influences is fundamental to understanding processes. In this paper, we present EIGEN - a method to leverage pre-trained language models to generate event influences conditioned on a context, nature …

I love your chain mail! Making knights smile in a fantasy game world:\n Open-domain goal-oriented dialogue agents

2020 · arXiv (Cornell University)

Dialogue research tends to distinguish between chit-chat and goal-oriented\ntasks. While the former is arguably more naturalistic and has a wider use of\nlanguage, the latter has clearer metrics and a straightforward learning signal.\nHumans effortlessly combine the …

Style Transfer Through Back-Translation

2018

Style transfer is the task of rephrasing the text to contain specific stylistic properties without changing the intent or affect within the context. This paper introduces a new method for automatic style transfer. We first …

A Dataset for Document Grounded Conversations

2018

This paper introduces a document grounded dataset for conversations. We define "Document Grounded Conversations" as conversations that are about the contents of a specified document. In this dataset the specified documents were Wikipedia articles about …

Using DeepSpeed and Megatron to Train Megatron-Turing NLG 530B, A Large-Scale Generative Language Model

2022 · arXiv (Cornell University)

Pretrained general-purpose language models can achieve state-of-the-art accuracies in various natural language processing domains by adapting to downstream tasks via zero-shot, few-shot and fine-tuning techniques. Because of their success, the size of these models has …

Self-Refine: Iterative Refinement with Self-Feedback

2023 · arXiv (Cornell University)

Like humans, large language models (LLMs) do not always generate the best output on their first try. Motivated by how humans refine their written text, we introduce Self-Refine, an approach for improving initial outputs from …