28 citations · 45 across the 7 of their papers we have counts for
6 papers · 1 filter
Speaker-Oriented Latent Structures for Dialogue-Based Relation Extraction
Guoshun Nan, Guoqing Luo, Sicong Leng +2
Dialogue-based relation extraction (DiaRE) aims to detect the structural information from unstructured utterances in dialogues. Existing relation extraction models may be unsatisfa…
Uncovering Main Causalities for Long-tailed Information Extraction
Guoshun Nan, Jiaqi Zeng, Rui Qiao +2
Information Extraction (IE) aims to extract structural information from unstructured texts. In practice, long-tailed distributions caused by the selection bias of a dataset, may le…
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…
Integrating Subgraph-aware Relation and DirectionReasoning for Question Answering
Xu Wang, Shuai Zhao, Bo Cheng +5
Question Answering (QA) models over Knowledge Bases (KBs) are capable of providing more precise answers by utilizing relation information among entities. Although effective, most o…
Modeling Topical Relevance for Multi-Turn Dialogue Generation
Hainan Zhang, Yanyan Lan, Liang Pang +3
Topic drift is a common phenomenon in multi-turn dialogue. Therefore, an ideal dialogue generation models should be able to capture the topic information of each context, detect th…
Reasoning with Latent Structure Refinement for Document-Level Relation Extraction
Guoshun Nan, Zhijiang Guo, Ivan Sekulić +1
Document-level relation extraction requires integrating information within and across multiple sentences of a document and capturing complex interactions between inter-sentence ent…