32 citations · 115 across the 23 of their papers we have counts for
20 papers · 1 filter
Semi-supervised News Discourse Profiling with Contrastive Learning
Ming Li, Ruihong Huang
News Discourse Profiling seeks to scrutinize the event-related role of each sentence in a news article and has been proven useful across various downstream applications. Specifical…
RST-style Discourse Parsing Guided by Document-level Content Structures
Ming Li, Ruihong Huang
Rhetorical Structure Theory based Discourse Parsing (RST-DP) explores how clauses, sentences, and large text spans compose a whole discourse and presents the rhetorical structure a…
Composition-contrastive Learning for Sentence Embeddings
Sachin J. Chanchani, Ruihong Huang
Vector representations of natural language are ubiquitous in search applications. Recently, various methods based on contrastive learning have been proposed to learn textual repres…
Modeling Document-level Temporal Structures for Building Temporal Dependency Graphs
Prafulla Kumar Choubey, Ruihong Huang
We propose to leverage news discourse profiling to model document-level temporal structures for building temporal dependency graphs. Our key observation is that the functional role…
Less is More: A Lightweight and Robust Neural Architecture for Discourse Parsing
Ming Li, Ruihong Huang
Complex feature extractors are widely employed for text representation building. However, these complex feature extractors make the NLP systems prone to overfitting especially when…
PARADE: A New Dataset for Paraphrase Identification Requiring Computer Science Domain Knowledge
Yun He, Zhuoer Wang, Yin Zhang +2
We present a new benchmark dataset called PARADE for paraphrase identification that requires specialized domain knowledge. PARADE contains paraphrases that overlap very little at t…
Weakly-supervised Fine-grained Event Recognition on Social Media Texts for Disaster Management
Wenlin Yao, Cheng Zhang, Shiva Saravanan +2
People increasingly use social media to report emergencies, seek help or share information during disasters, which makes social networks an important tool for disaster management.…
In Plain Sight: Media Bias Through the Lens of Factual Reporting
Lisa Fan, Marshall White, Eva Sharma +4
The increasing prevalence of political bias in news media calls for greater public awareness of it, as well as robust methods for its detection. While prior work in NLP has primari…
Improving Dialogue State Tracking by Discerning the Relevant Context
Sanuj Sharma, Prafulla Kumar Choubey, Ruihong Huang
A typical conversation comprises of multiple turns between participants where they go back-and-forth between different topics. At each user turn, dialogue state tracking (DST) aims…
Building Context-aware Clause Representations for Situation Entity Type Classification
Zeyu Dai, Ruihong Huang
Capabilities to categorize a clause based on the type of situation entity (e.g., events, states and generic statements) the clause introduces to the discourse can benefit many NLP…
Temporal Event Knowledge Acquisition via Identifying Narratives
Wenlin Yao, Ruihong Huang
Inspired by the double temporality characteristic of narrative texts, we propose a novel approach for acquiring rich temporal "before/after" event knowledge across sentences in nar…
Improving Implicit Discourse Relation Classification by Modeling Inter-dependencies of Discourse Units in a Paragraph
Zeyu Dai, Ruihong Huang
We argue that semantic meanings of a sentence or clause can not be interpreted independently from the rest of a paragraph, or independently from all discourse relations and the ove…
TAMU at KBP 2017: Event Nugget Detection and Coreference Resolution
Prafulla Kumar Choubey, Ruihong Huang
In this paper, we describe TAMU's system submitted to the TAC KBP 2017 event nugget detection and coreference resolution task. Our system builds on the statistical and empirical ob…
Using Context Events in Neural Network Models for Event Temporal Status Identification
Zeyu Dai, Wenlin Yao, Ruihong Huang
Focusing on the task of identifying event temporal status, we find that events directly or indirectly governing the target event in a dependency tree are most important contexts. T…
Detecting Online Hate Speech Using Context Aware Models
Lei Gao, Ruihong Huang
In the wake of a polarizing election, the cyber world is laden with hate speech. Context accompanying a hate speech text is useful for identifying hate speech, which however has be…
Recognizing Explicit and Implicit Hate Speech Using a Weakly Supervised Two-path Bootstrapping Approach
Lei Gao, Alexis Kuppersmith, Ruihong Huang
In the wake of a polarizing election, social media is laden with hateful content. To address various limitations of supervised hate speech classification methods including corpus b…
A Weakly Supervised Approach to Train Temporal Relation Classifiers and Acquire Regular Event Pairs Simultaneously
Wenlin Yao, Saipravallika Nettyam, Ruihong Huang
Capabilities of detecting temporal relations between two events can benefit many applications. Most of existing temporal relation classifiers were trained in a supervised manner. I…
Online Deception Detection Refueled by Real World Data Collection
Wenlin Yao, Zeyu Dai, Ruihong Huang +1
The lack of large realistic datasets presents a bottleneck in online deception detection studies. In this paper, we apply a data collection method based on social network analysis…
Event Coreference Resolution by Iteratively Unfolding Inter-dependencies among Events
Prafulla Kumar Choubey, Ruihong Huang
We introduce a novel iterative approach for event coreference resolution that gradually builds event clusters by exploiting inter-dependencies among event mentions within the same…
A Sequential Model for Classifying Temporal Relations between Intra-Sentence Events
Prafulla Kumar Choubey, Ruihong Huang
We present a sequential model for temporal relation classification between intra-sentence events. The key observation is that the overall syntactic structure and compositional mean…