Shen Gao

Meaningful Answer Generation of E-Commerce Question-Answering

2020 · arXiv (Cornell University)

In e-commerce portals, generating answers for product-related questions has become a crucial task. In this paper, we focus on the task of product-aware answer generation, which learns to generate an accurate and complete answer from …

BioGen: Generating Biography Summary under Table Guidance on Wikipedia

2021

Capturing the salient information from an input article has been a long-standing challenge for summarization. On Wikipedia, most of the wiki pages about people contain a factual table that lists the basic properties of the …

Contrastive Learning Reduces Hallucination in Conversations

2022 · arXiv (Cornell University)

Pre-trained language models (LMs) store knowledge in their parameters and can generate informative responses when used in conversational systems. However, LMs suffer from the problem of "hallucination:" they may generate plausible-looking statements that are irrelevant …

SSP: Self-Supervised Post-training for Conversational Search

2023

Conversational search has been regarded as the next-generation search paradigm.Constrained by data scarcity, most existing methods distill the well-trained ad-hoc retriever to the conversational retriever.However, these methods, which usually initialize parameters by query reformulation to …

VMSMO: Learning to Generate Multimodal Summary for Video-based News Articles

2020

A popular multimedia news format nowadays is providing users with a lively video and a corresponding news article, which is employed by influential news media including CNN, BBC, and social media including Twitter and Weibo. …