99 citations · 756 across the 62 of their papers we have counts for
10 papers · 1 filter
Ladder-of-Thought: Using Knowledge as Steps to Elevate Stance Detection
Kairui Hu, Ming Yan, Joey Tianyi Zhou +3
Stance detection aims to identify the attitude expressed in a document towards a given target. Techniques such as Chain-of-Thought (CoT) prompting have advanced this task, enhancin…
Perceiving the World: Question-guided Reinforcement Learning for Text-based Games
Yunqiu Xu, Meng Fang, Ling Chen +3
Text-based games provide an interactive way to study natural language processing. While deep reinforcement learning has shown effectiveness in developing the game playing agent, th…
Parallel Attention Network with Sequence Matching for Video Grounding
Hao Zhang, Aixin Sun, Wei Jing +3
Given a video, video grounding aims to retrieve a temporal moment that semantically corresponds to a language query. In this work, we propose a Parallel Attention Network with Sequ…
Video Corpus Moment Retrieval with Contrastive Learning
Hao Zhang, Aixin Sun, Wei Jing +4
Given a collection of untrimmed and unsegmented videos, video corpus moment retrieval (VCMR) is to retrieve a temporal moment (i.e., a fraction of a video) that semantically corres…
Natural Language Video Localization: A Revisit in Span-based Question Answering Framework
Hao Zhang, Aixin Sun, Wei Jing +3
Natural Language Video Localization (NLVL) aims to locate a target moment from an untrimmed video that semantically corresponds to a text query. Existing approaches mainly solve th…
Hooks in the Headline: Learning to Generate Headlines with Controlled Styles
Di Jin, Zhijing Jin, Joey Tianyi Zhou +2
Current summarization systems only produce plain, factual headlines, but do not meet the practical needs of creating memorable titles to increase exposure. We propose a new task, S…
Span-based Localizing Network for Natural Language Video Localization
Hao Zhang, Aixin Sun, Wei Jing +1
Given an untrimmed video and a text query, natural language video localization (NLVL) is to locate a matching span from the video that semantically corresponds to the query. Existi…
A Simple Baseline to Semi-Supervised Domain Adaptation for Machine Translation
Di Jin, Zhijing Jin, Joey Tianyi Zhou +1
State-of-the-art neural machine translation (NMT) systems are data-hungry and perform poorly on new domains with no supervised data. As data collection is expensive and infeasible…
Unsupervised Domain Adaptation on Reading Comprehension
Yu Cao, Meng Fang, Baosheng Yu +1
Reading comprehension (RC) has been studied in a variety of datasets with the boosted performance brought by deep neural networks. However, the generalization capability of these m…
Is BERT Really Robust? A Strong Baseline for Natural Language Attack on Text Classification and Entailment
Di Jin, Zhijing Jin, Joey Tianyi Zhou +1
Machine learning algorithms are often vulnerable to adversarial examples that have imperceptible alterations from the original counterparts but can fool the state-of-the-art models…