Search Results for author: Xin Luna Dong

Found 30 papers, 7 papers with code

SnapNTell: Enhancing Entity-Centric Visual Question Answering with Retrieval Augmented Multimodal LLM

no code implementations7 Mar 2024 JieLin Qiu, Andrea Madotto, Zhaojiang Lin, Paul A. Crook, Yifan Ethan Xu, Xin Luna Dong, Christos Faloutsos, Lei LI, Babak Damavandi, Seungwhan Moon

We have developed the \textbf{SnapNTell Dataset}, distinct from traditional VQA datasets: (1) It encompasses a wide range of categorized entities, each represented by images and explicitly named in the answers; (2) It features QA pairs that require extensive knowledge for accurate responses.

Question Answering Retrieval +1

Large Language Models as Zero-shot Dialogue State Tracker through Function Calling

no code implementations16 Feb 2024 Zekun Li, Zhiyu Zoey Chen, Mike Ross, Patrick Huber, Seungwhan Moon, Zhaojiang Lin, Xin Luna Dong, Adithya Sagar, Xifeng Yan, Paul A. Crook

We also show that by fine-tuning on a small collection of diverse task-oriented dialogues, we can equip modestly sized models, specifically a 13B parameter LLaMA2-Chat model, with function-calling capabilities and DST performance comparable to ChatGPT while maintaining their chat capabilities.

Avg Dialogue State Tracking +1

Generations of Knowledge Graphs: The Crazy Ideas and the Business Impact

no code implementations27 Aug 2023 Xin Luna Dong

Knowledge Graphs (KGs) have been used to support a wide range of applications, from web search to personal assistant.

Knowledge Graphs Question Answering

Head-to-Tail: How Knowledgeable are Large Language Models (LLMs)? A.K.A. Will LLMs Replace Knowledge Graphs?

no code implementations20 Aug 2023 Kai Sun, Yifan Ethan Xu, Hanwen Zha, Yue Liu, Xin Luna Dong

Since the recent prosperity of Large Language Models (LLMs), there have been interleaved discussions regarding how to reduce hallucinations from LLM responses, how to increase the factuality of LLMs, and whether Knowledge Graphs (KGs), which store the world knowledge in a symbolic form, will be replaced with LLMs.

Knowledge Graphs World Knowledge

OA-Mine: Open-World Attribute Mining for E-Commerce Products with Weak Supervision

1 code implementation29 Apr 2022 Xinyang Zhang, Chenwei Zhang, Xian Li, Xin Luna Dong, Jingbo Shang, Christos Faloutsos, Jiawei Han

Most prior works on this matter mine new values for a set of known attributes but cannot handle new attributes that arose from constantly changing data.

Attribute Language Modelling

Deep Transfer Learning for Multi-source Entity Linkage via Domain Adaptation

1 code implementation27 Oct 2021 Di Jin, Bunyamin Sisman, Hao Wei, Xin Luna Dong, Danai Koutra

AdaMEL models the attribute importance that is used to match entities through an attribute-level self-attention mechanism, and leverages the massive unlabeled data from new data sources through domain adaptation to make it generic and data-source agnostic.

Attribute Domain Adaptation +1

PAM: Understanding Product Images in Cross Product Category Attribute Extraction

no code implementations8 Jun 2021 Rongmei Lin, Xiang He, Jie Feng, Nasser Zalmout, Yan Liang, Li Xiong, Xin Luna Dong

Understanding product attributes plays an important role in improving online shopping experience for customers and serves as an integral part for constructing a product knowledge graph.

Attribute Attribute Extraction +4

CoRI: Collective Relation Integration with Data Augmentation for Open Information Extraction

no code implementations ACL 2021 Zhengbao Jiang, Jialong Han, Bunyamin Sisman, Xin Luna Dong

We propose a two-stage Collective Relation Integration (CoRI) model, where the first stage independently makes candidate predictions, and the second stage employs a collective model that accesses all candidate predictions to make globally coherent predictions.

Data Augmentation Knowledge Graphs +3

TCN: Table Convolutional Network for Web Table Interpretation

1 code implementation17 Feb 2021 Daheng Wang, Prashant Shiralkar, Colin Lockard, Binxuan Huang, Xin Luna Dong, Meng Jiang

Existing work linearize table cells and heavily rely on modifying deep language models such as BERT which only captures related cells information in the same table.

Representation Learning Table annotation +1

J-Recs: Principled and Scalable Recommendation Justification

no code implementations11 Nov 2020 Namyong Park, Andrey Kan, Christos Faloutsos, Xin Luna Dong

Online recommendation is an essential functionality across a variety of services, including e-commerce and video streaming, where items to buy, watch, or read are suggested to users.


CorDEL: A Contrastive Deep Learning Approach for Entity Linkage

no code implementations15 Sep 2020 Zhengyang Wang, Bunyamin Sisman, Hao Wei, Xin Luna Dong, Shuiwang Ji

We evaluate CorDEL with extensive experiments conducted on both public benchmark datasets and a real-world dataset.

Entity Resolution

Multi-modal Information Extraction from Text, Semi-structured, and Tabular Data on the Web

no code implementations ACL 2020 Xin Luna Dong, Hannaneh Hajishirzi, Colin Lockard, Prashant Shiralkar

In this tutorial we take a holistic view toward information extraction, exploring the commonalities in the challenges and solutions developed to address these different forms of text.

document understanding Entity Linking

MultiImport: Inferring Node Importance in a Knowledge Graph from Multiple Input Signals

no code implementations22 Jun 2020 Namyong Park, Andrey Kan, Xin Luna Dong, Tong Zhao, Christos Faloutsos

MultiImport is a latent variable model that captures the relation between node importance and input signals, and effectively learns from multiple signals with potential conflicts.

Octet: Online Catalog Taxonomy Enrichment with Self-Supervision

no code implementations18 Jun 2020 Yuning Mao, Tong Zhao, Andrey Kan, Chenwei Zhang, Xin Luna Dong, Christos Faloutsos, Jiawei Han

We propose to distantly train a sequence labeling model for term extraction and employ graph neural networks (GNNs) to capture the taxonomy structure as well as the query-item-taxonomy interactions for term attachment.

Term Extraction

Automatic Validation of Textual Attribute Values in E-commerce Catalog by Learning with Limited Labeled Data

no code implementations15 Jun 2020 Yaqing Wang, Yifan Ethan Xu, Xi-An Li, Xin Luna Dong, Jing Gao

(1) We formalize the problem of validating the textual attribute values of products from a variety of categories as a natural language inference task in the few-shot learning setting, and propose a meta-learning latent variable model to jointly process the signals obtained from product profiles and textual attribute values.

Attribute Few-Shot Learning +1

ZeroShotCeres: Zero-Shot Relation Extraction from Semi-Structured Webpages

no code implementations14 May 2020 Colin Lockard, Prashant Shiralkar, Xin Luna Dong, Hannaneh Hajishirzi

In this work, we propose a solution for "zero-shot" open-domain relation extraction from webpages with a previously unseen template, including from websites with little overlap with existing sources of knowledge for distant supervision and websites in entirely new subject verticals.

Relation Relation Extraction

AutoBlock: A Hands-off Blocking Framework for Entity Matching

1 code implementation7 Dec 2019 Wei Zhang, Hao Wei, Bunyamin Sisman, Xin Luna Dong, Christos Faloutsos, David Page

Entity matching seeks to identify data records over one or multiple data sources that refer to the same real-world entity.

Blocking Representation Learning

Efficient Knowledge Graph Accuracy Evaluation

no code implementations23 Jul 2019 Junyang Gao, Xi-An Li, Yifan Ethan Xu, Bunyamin Sisman, Xin Luna Dong, Jun Yang

To address the problem, this paper proposes an efficient sampling and evaluation framework, which aims to provide quality accuracy evaluation with strong statistical guarantee while minimizing human efforts.


OpenCeres: When Open Information Extraction Meets the Semi-Structured Web

no code implementations NAACL 2019 Colin Lockard, Prashant Shiralkar, Xin Luna Dong

In this paper, we define the problem of OpenIE from semi-structured websites to extract such facts, and present an approach for solving it.

Open Information Extraction Relation Extraction

OpenKI: Integrating Open Information Extraction and Knowledge Bases with Relation Inference

1 code implementation NAACL 2019 Dongxu Zhang, Subhabrata Mukherjee, Colin Lockard, Xin Luna Dong, Andrew McCallum

In this paper, we consider advancing web-scale knowledge extraction and alignment by integrating OpenIE extractions in the form of (subject, predicate, object) triples with Knowledge Bases (KB).

Open Information Extraction Relation

CERES: Distantly Supervised Relation Extraction from the Semi-Structured Web

no code implementations12 Apr 2018 Colin Lockard, Xin Luna Dong, Arash Einolghozati, Prashant Shiralkar

In this paper we present a new method for automatic extraction from semi-structured websites based on distant supervision.

Relation Relation Extraction

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