Search Results for author:
Found 19 papers, 8 papers with code
Coupled Hierarchical Transformer for Stance-Aware Rumor Verification in Social Media Conversations
The prevalent use of social media enables rapid spread of rumors on a massive scale, which leads to the emerging need of automatic rumor verification (RV).
Co-training for Commit Classification
In this paper, we apply co-training, a semi-supervised learning method, to take advantage of the two views available – the commit message (natural language) and the code changes (programming language) – to improve commit classification.
Intrinsic evaluation of language models for code-switching
Underlying such an evaluation is the assumption that the generated sentences are linguistically incorrect.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Measuring and Enhancing Trustworthiness of LLMs in RAG through Grounded Attributions and Learning to Refuse
LLMs are an integral component of retrieval-augmented generation (RAG) systems.
Multi-label and Multi-target Sampling of Machine Annotation for Computational Stance Detection
Data collection from manual labeling provides domain-specific and task-aligned supervision for data-driven approaches, and a critical mass of well-annotated resources is required to achieve reasonable performance in natural language processing tasks.
Guiding Computational Stance Detection with Expanded Stance Triangle Framework
Stance detection determines whether the author of a piece of text is in favor of, against, or neutral towards a specified target, and can be used to gain valuable insights into social media.
Cross-Topic Rumor Detection using Topic-Mixtures
After deriving a vector representation for each topic, given an instance, we derive a {``}topic mixture{''} vector for the instance based on its topic distribution.
Meta Auxiliary Labels with Constituent-based Transformer for Aspect-based Sentiment Analysis
Previous work exploit dependency parses to improve performance on the task, but this requires the existence of good dependency parsers.
Aspect-Based Sentiment Analysis
Aspect-Based Sentiment Analysis (ABSA)
+1
Interpretable Rumor Detection in Microblogs by Attending to User Interactions
We propose a post-level attention model (PLAN) to model long distance interactions between tweets with the multi-head attention mechanism in a transformer network.
Twitter Homophily: Network Based Prediction of User's Occupation
In this paper, we investigate the importance of social network information compared to content information in the prediction of a Twitter user{'}s occupational class.
Chemical Structure Elucidation from Mass Spectrometry by Matching Substructures
We take a data driven approach to rank these structures by using neural networks to predict the presence of substructures given the mass spectrum, and matching these substructures to the candidate structures.
Can Syntax Help? Improving an LSTM-based Sentence Compression Model for New Domains
In this paper, we study how to improve the domain adaptability of a deletion-based Long Short-Term Memory (LSTM) neural network model for sentence compression.
Ranked #6 on
Sentence Compression
on Google Dataset
Universal Dependencies Parsing for Colloquial Singaporean English
Singlish can be interesting to the ACL community both linguistically as a major creole based on English, and computationally for information extraction and sentiment analysis of regional social media.
Relaxed Survey Propagation for The Weighted Maximum Satisfiability Problem
In this paper, we formulate the relaxed survey propagation (RSP) algorithm, which extends the SP algorithm to apply to the weighted Max-SAT problem.
Active Learning for Probabilistic Hypotheses Using the Maximum Gibbs Error Criterion
We introduce a new objective function for pool-based Bayesian active learning with probabilistic hypotheses.
