12 citations · 16 across the 9 of their papers we have counts for
9 papers
Mixtures of Unsupervised Lexicon Classification
Peratham Wiriyathammabhum
This paper presents a mixture version of the method-of-moment unsupervised lexicon classification by an incorporation of a Dirichlet process.
ClassBases at CASE-2022 Multilingual Protest Event Detection Tasks: Multilingual Protest News Detection and Automatically Replicating Manually Created Event Datasets
Peratham Wiriyathammabhum
In this report, we describe our ClassBases submissions to a shared task on multilingual protest event detection. For the multilingual protest news detection, we participated in sub…
PromptShots at the FinNLP-2022 ERAI Tasks: Pairwise Comparison and Unsupervised Ranking
Peratham Wiriyathammabhum
This report describes our PromptShots submissions to a shared task on Evaluating the Rationales of Amateur Investors (ERAI). We participated in both pairwise comparison and unsuper…
TEDB System Description to a Shared Task on Euphemism Detection 2022
Peratham Wiriyathammabhum
In this report, we describe our Transformers for euphemism detection baseline (TEDB) submissions to a shared task on euphemism detection 2022. We cast the task of predicting euphem…
Is Sluice Resolution really just Question Answering?
Peratham Wiriyathammabhum
Sluice resolution is a problem where a system needs to output the corresponding antecedents of wh-ellipses. The antecedents are elided contents behind the wh-words but are implicit…
SpotFast Networks with Memory Augmented Lateral Transformers for Lipreading
Peratham Wiriyathammabhum
This paper presents a novel deep learning architecture for word-level lipreading. Previous works suggest a potential for incorporating a pretrained deep 3D Convolutional Neural Net…
Referring to Objects in Videos using Spatio-Temporal Identifying Descriptions
Peratham Wiriyathammabhum, Abhinav Shrivastava, Vlad I. Morariu +1
This paper presents a new task, the grounding of spatio-temporal identifying descriptions in videos. Previous work suggests potential bias in existing datasets and emphasizes the n…
Robust Principal Component Analysis Using Statistical Estimators
Peratham Wiriyathammabhum, Boonserm Kijsirikul
Principal Component Analysis (PCA) finds a linear mapping and maximizes the variance of the data which makes PCA sensitive to outliers and may cause wrong eigendirection. In this p…
Applying Deep Belief Networks to Word Sense Disambiguation
Peratham Wiriyathammabhum, Boonserm Kijsirikul, Hiroya Takamura +1
In this paper, we applied a novel learning algorithm, namely, Deep Belief Networks (DBN) to word sense disambiguation (WSD). DBN is a probabilistic generative model composed of mul…