Search Results for author:
Found 30 papers, 15 papers with code
Tackling Zero Pronoun Resolution and Non-Zero Coreference Resolution Jointly
Zero pronoun resolution aims at recognizing dropped pronouns and pointing out their anaphoric mentions, while non-zero coreference resolution targets at clustering mentions referring to the same entity.
AutoCrawler: A Progressive Understanding Web Agent for Web Crawler Generation
We propose AutoCrawler, a two-stage framework that leverages the hierarchical structure of HTML for progressive understanding.
Is There a One-Model-Fits-All Approach to Information Extraction? Revisiting Task Definition Biases
Definition bias is a negative phenomenon that can mislead models.
Flickr30K-CFQ: A Compact and Fragmented Query Dataset for Text-image Retrieval
Text-image retrieval research is needed to realize high-quality and efficient retrieval between different modalities.
OVEL: Large Language Model as Memory Manager for Online Video Entity Linking
In this paper, we propose a task called Online Video Entity Linking OVEL, aiming to establish connections between mentions in online videos and a knowledge base with high accuracy and timeliness.
Improving the Robustness of Knowledge-Grounded Dialogue via Contrastive Learning
Knowledge-grounded dialogue (KGD) learns to generate an informative response based on a given dialogue context and external knowledge (\emph{e. g.}, knowledge graphs; KGs).
M2ConceptBase: A Fine-grained Aligned Multi-modal Conceptual Knowledge Base
To collect concept-image and concept-description alignments, we propose a context-aware multi-modal symbol grounding approach that considers context information in existing large-scale image-text pairs with respect to each concept.
A Contrastive Compositional Benchmark for Text-to-Image Synthesis: A Study with Unified Text-to-Image Fidelity Metrics
We use Winoground-T2I with a dual objective: to evaluate the performance of T2I models and the metrics used for their evaluation.
AspectMMKG: A Multi-modal Knowledge Graph with Aspect-aware Entities
Multi-modal knowledge graphs (MMKGs) combine different modal data (e. g., text and image) for a comprehensive understanding of entities.
Adaptive Ordered Information Extraction with Deep Reinforcement Learning
Information extraction (IE) has been studied extensively.
Snowman: A Million-scale Chinese Commonsense Knowledge Graph Distilled from Foundation Model
Constructing commonsense knowledge graphs (CKGs) has attracted wide research attention due to its significant importance in cognitive intelligence.
Towards Unifying Multi-Lingual and Cross-Lingual Summarization
In this paper, we aim to unify MLS and CLS into a more general setting, i. e., many-to-many summarization (M2MS), where a single model could process documents in any language and generate their summaries also in any language.
GANTEE: Generative Adversatial Network for Taxonomy Entering Evaluation
The previous methods suffer from low-efficiency since they waste much time when most of the new coming concepts are indeed noisy concepts.
Is ChatGPT a Good NLG Evaluator? A Preliminary Study
In detail, we regard ChatGPT as a human evaluator and give task-specific (e. g., summarization) and aspect-specific (e. g., relevance) instruction to prompt ChatGPT to evaluate the generated results of NLG models.
Zero-Shot Cross-Lingual Summarization via Large Language Models
Given a document in a source language, cross-lingual summarization (CLS) aims to generate a summary in a different target language.
Understanding Translationese in Cross-Lingual Summarization
In detail, we find that (1) the translationese in documents or summaries of test sets might lead to the discrepancy between human judgment and automatic evaluation; (2) the translationese in training sets would harm model performance in real-world applications; (3) though machine-translated documents involve translationese, they are very useful for building CLS systems on low-resource languages under specific training strategies.
Long-Document Cross-Lingual Summarization
Cross-Lingual Summarization (CLS) aims at generating summaries in one language for the given documents in another language.
Generative Entity Typing with Curriculum Learning
To overcome these drawbacks, we propose a novel generative entity typing (GET) paradigm: given a text with an entity mention, the multiple types for the role that the entity plays in the text are generated with a pre-trained language model (PLM).
RT-KGD: Relation Transition Aware Knowledge-Grounded Dialogue Generation
Nevertheless, the correlations between knowledge implied in the multi-turn context and the transition regularities between relations in KGs are under-explored.
WikiDiverse: A Multimodal Entity Linking Dataset with Diversified Contextual Topics and Entity Types
In this paper, we present WikiDiverse, a high-quality human-annotated MEL dataset with diversified contextual topics and entity types from Wikinews, which uses Wikipedia as the corresponding knowledge base.
A Survey on Cross-Lingual Summarization
Cross-lingual summarization is the task of generating a summary in one language (e. g., English) for the given document(s) in a different language (e. g., Chinese).
Can Pre-trained Language Models Interpret Similes as Smart as Human?
In this paper, we investigate the ability of PLMs in simile interpretation by designing a novel task named Simile Property Probing, i. e., to let the PLMs infer the shared properties of similes.
ClidSum: A Benchmark Dataset for Cross-Lingual Dialogue Summarization
We present ClidSum, a benchmark dataset for building cross-lingual summarization systems on dialogue documents.
Multi-Modal Knowledge Graph Construction and Application: A Survey
In this survey on MMKGs constructed by texts and images, we first give definitions of MMKGs, followed with the preliminaries on multi-modal tasks and techniques.
Incorporating Commonsense Knowledge into Story Ending Generation via Heterogeneous Graph Networks
Story ending generation is an interesting and challenging task, which aims to generate a coherent and reasonable ending given a story context.
Knowledge Enhanced Sports Game Summarization
Additionally, we also introduce a knowledge-enhanced summarizer that utilizes both live commentaries and the knowledge to generate sports news.
SportsSum2.0: Generating High-Quality Sports News from Live Text Commentary
Sports game summarization aims to generate news articles from live text commentaries.
Multi-Modal Chorus Recognition for Improving Song Search
In addition, our approach also helps to improve the accuracy of its downstream task - song search by more than 10. 6%.
Overcoming Data Sparsity in Group Recommendation
Specifically, we first extend BGEM to model group-item interactions, and then in order to overcome the limitation and sparsity of the interaction data generated by occasional groups, we propose a self-attentive mechanism to represent groups based on the group members.
Where to Go Next: A Spatio-temporal LSTM model for Next POI Recommendation
Furthermore, to reduce the number of parameters and improve efficiency, we further integrate coupled input and forget gates with our proposed model.
