activity
20172022
most citedQuantum oscillations and Dirac-Landau levels in Weyl superconductors

20 citations · 50 across the 11 of their papers we have counts for

collaborators

12 papers

cs.CL2022

Autoregressive Structured Prediction with Language Models

Tianyu Liu, Yuchen Jiang, Nicholas Monath +2

Recent years have seen a paradigm shift in NLP towards using pretrained language models ({PLM}) for a wide range of tasks. However, there are many difficult design decisions to rep…

cs.CL2022

A Bilingual Parallel Corpus with Discourse Annotations

Yuchen Eleanor Jiang, Tianyu Liu, Shuming Ma +3

Machine translation (MT) has almost achieved human parity at sentence-level translation. In response, the MT community has, in part, shifted its focus to document-level translation…

cs.CL2022

DialogUSR: Complex Dialogue Utterance Splitting and Reformulation for Multiple Intent Detection

Haoran Meng, Zheng Xin, Tianyu Liu +6

While interacting with chatbots, users may elicit multiple intents in a single dialogue utterance. Instead of training a dedicated multi-intent detection model, we propose DialogUS…

cs.CL20224 cited

Learning Robust Representations for Continual Relation Extraction via Adversarial Class Augmentation

Peiyi Wang, Yifan Song, Tianyu Liu +4

Continual relation extraction (CRE) aims to continually learn new relations from a class-incremental data stream. CRE model usually suffers from catastrophic forgetting problem, i.…

cs.CL20223 cited

Robust Fine-tuning via Perturbation and Interpolation from In-batch Instances

Shoujie Tong, Qingxiu Dong, Damai Dai +4

Fine-tuning pretrained language models (PLMs) on downstream tasks has become common practice in natural language processing. However, most of the PLMs are vulnerable, e.g., they ar…

cs.CL2022

A Two-Stream AMR-enhanced Model for Document-level Event Argument Extraction

Runxin Xu, Peiyi Wang, Tianyu Liu +3

Most previous studies aim at extracting events from a single sentence, while document-level event extraction still remains under-explored. In this paper, we focus on extracting eve…