no code implementations • 7 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.
1 code implementation • 16 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.
no code implementations • 12 Feb 2024 • Ashish Shenoy, Yichao Lu, Srihari Jayakumar, Debojeet Chatterjee, Mohsen Moslehpour, Pierce Chuang, Abhay Harpale, Vikas Bhardwaj, Di Xu, Shicong Zhao, Longfang Zhao, Ankit Ramchandani, Xin Luna Dong, Anuj Kumar
We introduce Lumos, the first end-to-end multimodal question-answering system with text understanding capabilities.
no code implementations • 27 Aug 2023 • Xin Luna Dong
Knowledge Graphs (KGs) have been used to support a wide range of applications, from web search to personal assistant.
no code implementations • 20 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.
1 code implementation • 29 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.
1 code implementation • 27 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.
no code implementations • EMNLP 2021 • Liqiang Xiao, Jun Ma2, Xin Luna Dong, Pascual Martinez-Gomez, Nasser Zalmout, Wei Chen, Tong Zhao, Hao He, Yaohui Jin
Successful conversational search systems can present natural, adaptive and interactive shopping experience for online shopping customers.
no code implementations • 8 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.
no code implementations • ACL 2021 • Jun Yan, Nasser Zalmout, Yan Liang, Christan Grant, Xiang Ren, Xin Luna Dong
However, this approach constrains knowledge sharing across different attributes.
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.
1 code implementation • 17 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.
no code implementations • 11 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.
no code implementations • 15 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.
Ranked #7 on Entity Resolution on Amazon-Google
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.
no code implementations • 24 Jun 2020 • Xin Luna Dong, Xiang He, Andrey Kan, Xi-An Li, Yan Liang, Jun Ma, Yifan Ethan Xu, Chenwei Zhang, Tong Zhao, Gabriel Blanco Saldana, Saurabh Deshpande, Alexandre Michetti Manduca, Jay Ren, Surender Pal Singh, Fan Xiao, Haw-Shiuan Chang, Giannis Karamanolakis, Yuning Mao, Yaqing Wang, Christos Faloutsos, Andrew McCallum, Jiawei Han
Can one build a knowledge graph (KG) for all products in the world?
no code implementations • 22 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.
no code implementations • 18 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.
no code implementations • 15 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.
no code implementations • 14 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.
1 code implementation • ACL 2020 • Giannis Karamanolakis, Jun Ma, Xin Luna Dong
Extracting structured knowledge from product profiles is crucial for various applications in e-Commerce.
no code implementations • AKBC 2020 • Varun Embar, Bunyamin Sisman, Hao Wei, Xin Luna Dong, Christos Faloutsos, Lise Getoor
However, this task is challenging as the variational attributes are often present as a part of unstructured text and are domain dependent.
1 code implementation • 7 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.
no code implementations • 23 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.
Databases
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.
no code implementations • 21 May 2019 • Namyong Park, Andrey Kan, Xin Luna Dong, Tong Zhao, Christos Faloutsos
How can we estimate the importance of nodes in a knowledge graph (KG)?
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).
no code implementations • ACL 2018 • Rakshit Trivedi, Bunyamin Sisman, Jun Ma, Christos Faloutsos, Hongyuan Zha, Xin Luna Dong
Knowledge graphs have emerged as an important model for studying complex multi-relational data.
2 code implementations • 1 Jun 2018 • Guineng Zheng, Subhabrata Mukherjee, Xin Luna Dong, Fei-Fei Li
We study this problem in the context of product catalogs that often have missing values for many attributes of interest.
no code implementations • 12 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.