activity
20192023
most citedChatIE: Zero-Shot Information Extraction via Chatting with ChatGPT

149 citations · 473 across the 27 of their papers we have counts for

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Showing 2023Show all

12 papers · 1 filter

cs.CV2023

Grounded Entity-Landmark Adaptive Pre-training for Vision-and-Language Navigation

Yibo Cui, Liang Xie, Yakun Zhang +3

Cross-modal alignment is one key challenge for Vision-and-Language Navigation (VLN). Most existing studies concentrate on mapping the global instruction or single sub-instruction t…

cs.CV2023★ 16 cited

Constructing Holistic Spatio-Temporal Scene Graph for Video Semantic Role Labeling

Yu Zhao, Hao Fei, Yixin Cao +5

Video Semantic Role Labeling (VidSRL) aims to detect the salient events from given videos, by recognizing the predict-argument event structures and the interrelationships between e…

cs.CL2023★ 66 cited

Towards General Text Embeddings with Multi-stage Contrastive Learning

Zehan Li, Xin Zhang, Yanzhao Zhang +3

We present GTE, a general-purpose text embedding model trained with multi-stage contrastive learning. In line with recent advancements in unifying various NLP tasks into a single f…

cs.CL2023★ 1 cited

XNLP: An Interactive Demonstration System for Universal Structured NLP

Hao Fei, Meishan Zhang, Min Zhang +1

Structured Natural Language Processing (XNLP) is an important subset of NLP that entails understanding the underlying semantic or syntactic structure of texts, which serves as a fo…

cs.CL2023

Holistic Exploration on Universal Decompositional Semantic Parsing: Architecture, Data Augmentation, and LLM Paradigm

Hexuan Deng, Xin Zhang, Meishan Zhang +2

In this paper, we conduct a holistic exploration of the Universal Decompositional Semantic (UDS) Parsing. We first introduce a cascade model for UDS parsing that decomposes the com…

cs.CL2023★ 2 cited

Constructing Code-mixed Universal Dependency Forest for Unbiased Cross-lingual Relation Extraction

Hao Fei, Meishan Zhang, Min Zhang +1

Latest efforts on cross-lingual relation extraction (XRE) aggressively leverage the language-consistent structural features from the universal dependency (UD) resource, while they…

cs.CL2023

A Pilot Study on Dialogue-Level Dependency Parsing for Chinese

Gongyao Jiang, Shuang Liu, Meishan Zhang +1

Dialogue-level dependency parsing has received insufficient attention, especially for Chinese. To this end, we draw on ideas from syntactic dependency and rhetorical structure theo…

cs.CL2023★ 20 cited

Scene Graph as Pivoting: Inference-time Image-free Unsupervised Multimodal Machine Translation with Visual Scene Hallucination

Hao Fei, Qian Liu, Meishan Zhang +2

In this work, we investigate a more realistic unsupervised multimodal machine translation (UMMT) setup, inference-time image-free UMMT, where the model is trained with source-text…

cs.CV2023★ 7 cited

Generating Visual Spatial Description via Holistic 3D Scene Understanding

Yu Zhao, Hao Fei, Wei Ji +4

Visual spatial description (VSD) aims to generate texts that describe the spatial relations of the given objects within images. Existing VSD work merely models the 2D geometrical v…

cs.CL2023★ 85 cited

On the Robustness of Aspect-based Sentiment Analysis: Rethinking Model, Data, and Training

Hao Fei, Tat-Seng Chua, Chenliang Li +3

Aspect-based sentiment analysis (ABSA) aims at automatically inferring the specific sentiment polarities toward certain aspects of products or services behind the social media text…

cs.CL2023★ 69 cited

LasUIE: Unifying Information Extraction with Latent Adaptive Structure-aware Generative Language Model

Hao Fei, Shengqiong Wu, Jingye Li +6

Universally modeling all typical information extraction tasks (UIE) with one generative language model (GLM) has revealed great potential by the latest study, where various IE pred…

cs.CL2023★ 149 cited

ChatIE: Zero-Shot Information Extraction via Chatting with ChatGPT

Xiang Wei, Xingyu Cui, Ning Cheng +9

Zero-shot information extraction (IE) aims to build IE systems from the unannotated text. It is challenging due to involving little human intervention. Challenging but worthwhile,…