674 citations
- University of Illinois ChicagoUS13 papers
- Singapore Management UniversitySG11 papers
- Carnegie Mellon UniversityUS8 papers
- Georgia Institute of TechnologyUS7 papers
- Princeton UniversityUS7 papers
- Nanyang Technological UniversitySG6 papers
- University of Illinois Urbana-ChampaignUS6 papers
- Agency for Science, Technology and ResearchSG5 papers
- Chinese University of Hong KongHK5 papers
- University of Maryland, College ParkUS5 papers
- University of WashingtonUS5 papers
- Beihang UniversityCN4 papers
24 papers · 1 filter
Learning from Noisy Anchors for One-stage Object Detection
Hengduo Li, Zuxuan Wu, Chen Zhu +3
State-of-the-art object detectors rely on regressing and classifying an extensive list of possible anchors, which are divided into positive and negative samples based on their inte…
Wasserstein distances for evaluating cross-lingual embeddings
Georgios Balikas, Ioannis Partalas
Word embeddings are high dimensional vector representations of words that capture their semantic similarity in the vector space. There exist several algorithms for learning such em…
Learning to Retrieve Reasoning Paths over Wikipedia Graph for Question Answering
Akari Asai, Kazuma Hashimoto, Hannaneh Hajishirzi +2
Answering questions that require multi-hop reasoning at web-scale necessitates retrieving multiple evidence documents, one of which often has little lexical or semantic relationshi…
MKD: a Multi-Task Knowledge Distillation Approach for Pretrained Language Models
Linqing Liu, Huan Wang, Jimmy Lin +2
Pretrained language models have led to significant performance gains in many NLP tasks. However, the intensive computing resources to train such models remain an issue. Knowledge d…
Classification Calibration for Long-tail Instance Segmentation
Tao Wang, Yu Li, Bingyi Kang +5
Remarkable progress has been made in object instance detection and segmentation in recent years. However, existing state-of-the-art methods are mostly evaluated with fairly balance…
Find or Classify? Dual Strategy for Slot-Value Predictions on Multi-Domain Dialog State Tracking
Jian-Guo Zhang, Kazuma Hashimoto, Chien-Sheng Wu +4
Dialog state tracking (DST) is a core component in task-oriented dialog systems. Existing approaches for DST mainly fall into one of two categories, namely, ontology-based and onto…