41 citations · 85 across the 21 of their papers we have counts for
26 papers
Towards End-to-End Embodied Decision Making via Multi-modal Large Language Model: Explorations with GPT4-Vision and Beyond
Liang Chen, Yichi Zhang, Shuhuai Ren +6
In this study, we explore the potential of Multimodal Large Language Models (MLLMs) in improving embodied decision-making processes for agents. While Large Language Models (LLMs) h…
Query Your Model with Definitions in FrameNet: An Effective Method for Frame Semantic Role Labeling
Ce Zheng, Yiming Wang, Baobao Chang
Frame Semantic Role Labeling (FSRL) identifies arguments and labels them with frame semantic roles defined in FrameNet. Previous researches tend to divide FSRL into argument identi…
A Two-Stage Method for Chinese AMR Parsing
Liang Chen, Bofei Gao, Baobao Chang
In this paper, we provide a detailed description of our system at CAMRP-2022 evaluation. We firstly propose a two-stage method to conduct Chinese AMR Parsing with alignment generat…
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…
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…
ATP: AMRize Then Parse! Enhancing AMR Parsing with PseudoAMRs
Liang Chen, Peiyi Wang, Runxin Xu +3
As Abstract Meaning Representation (AMR) implicitly involves compound semantic annotations, we hypothesize auxiliary tasks which are semantically or formally related can better enh…