18 citations · 21 across the 9 of their papers we have counts for
5 papers · 1 filter
Separate and Locate: Rethink the Text in Text-based Visual Question Answering
Chengyang Fang, Jiangnan Li, Liang Li +2
Text-based Visual Question Answering (TextVQA) aims at answering questions about the text in images. Most works in this field focus on designing network structures or pre-training…
CATS: A Pragmatic Chinese Answer-to-Sequence Dataset with Large Scale and High Quality
Liang Li, Ruiying Geng, Chengyang Fang +6
There are three problems existing in the popular data-to-text datasets. First, the large-scale datasets either contain noise or lack real application scenarios. Second, the dataset…
GPT-Sentinel: Distinguishing Human and ChatGPT Generated Content
Yutian Chen, Hao Kang, Vivian Zhai +3
This paper presents a novel approach for detecting ChatGPT-generated vs. human-written text using language models. To this end, we first collected and released a pre-processed data…
Protective Self-Adaptive Pruning to Better Compress DNNs
Liang Li, Pengfei Zhao
Adaptive network pruning approach has recently drawn significant attention due to its excellent capability to identify the importance and redundancy of layers and filters and custo…
Plan-then-Seam: Towards Efficient Table-to-Text Generation
Liang Li, Ruiying Geng, Chengyang Fang +4
Table-to-text generation aims at automatically generating text to help people conveniently obtain salient information in tables. Recent works explicitly decompose the generation pr…