29 citations · 36 across the 7 of their papers we have counts for
7 papers
Character-level White-Box Adversarial Attacks against Transformers via Attachable Subwords Substitution
Aiwei Liu, Honghai Yu, Xuming Hu +5
We propose the first character-level white-box adversarial attack method against transformer models. The intuition of our method comes from the observation that words are split int…
Semantic Enhanced Text-to-SQL Parsing via Iteratively Learning Schema Linking Graph
Aiwei Liu, Xuming Hu, Li Lin +1
The generalizability to new databases is of vital importance to Text-to-SQL systems which aim to parse human utterances into SQL statements. Existing works achieve this goal by lev…
A Multi-level Supervised Contrastive Learning Framework for Low-Resource Natural Language Inference
Shu'ang Li, Xuming Hu, Li Lin +3
Natural Language Inference (NLI) is a growingly essential task in natural language understanding, which requires inferring the relationship between the sentence pairs (premise and…
Pair-Level Supervised Contrastive Learning for Natural Language Inference
Shu'ang Li, Xuming Hu, Li Lin +1
Natural language inference (NLI) is an increasingly important task for natural language understanding, which requires one to infer the relationship between the sentence pair (premi…
What Makes the Story Forward? Inferring Commonsense Explanations as Prompts for Future Event Generation
Li Lin, Yixin Cao, Lifu Huang +4
Prediction over event sequences is critical for many real-world applications in Information Retrieval and Natural Language Processing. Future Event Generation (FEG) is a challengin…
Gradient Imitation Reinforcement Learning for Low Resource Relation Extraction
Xuming Hu, Chenwei Zhang, Yawen Yang +4
Low-resource Relation Extraction (LRE) aims to extract relation facts from limited labeled corpora when human annotation is scarce. Existing works either utilize self-training sche…
An Approach for Process Model Extraction By Multi-Grained Text Classification
Chen Qian, Lijie Wen, Akhil Kumar +5
Process model extraction (PME) is a recently emerged interdiscipline between natural language processing (NLP) and business process management (BPM), which aims to extract process…