22 citations · 77 across the 28 of their papers we have counts for
23 papers · 1 filter
Probing the Geometry of Color Representations in Multilingual Language Models
Pablo Loyola, Edison Marrese-Taylor, Andrés Hoyos-Idrobo
Do multilingual language models learn a universal internal geometry for color, and is it perceptually grounded or primarily linguistic? We decompose color representations into two…
On the Role of Unobserved Sequences on Sample-based Uncertainty Quantification for LLMs
Lucie Kunitomo-Jacquin, Edison Marrese-Taylor, Ken Fukuda
Quantifying uncertainty in large language models (LLMs) is important for safety-critical applications because it helps spot incorrect answers, known as hallucinations. One major tr…
Image-Text Relation Prediction for Multilingual Tweets
Matīss Rikters, Edison Marrese-Taylor
Various social networks have been allowing media uploads for over a decade now. Still, it has not always been clear what is their relation with the posted text or even if there is…
Annotations for Exploring Food Tweets From Multiple Aspects
Matīss Rikters, Edison Marrese-Taylor, Rinalds Vīksna
This research builds upon the Latvian Twitter Eater Corpus (LTEC), which is focused on the narrow domain of tweets related to food, drinks, eating and drinking. LTEC has been colle…
KG-Rank: Enhancing Large Language Models for Medical QA with Knowledge Graphs and Ranking Techniques
Rui Yang, Haoran Liu, Edison Marrese-Taylor +8
Large language models (LLMs) have demonstrated impressive generative capabilities with the potential to innovate in medicine. However, the application of LLMs in real clinical sett…
Perceptual Structure in the Absence of Grounding for LLMs: The Impact of Abstractedness and Subjectivity in Color Language
Pablo Loyola, Edison Marrese-Taylor, Andres Hoyos-Idobro
The need for grounding in language understanding is an active research topic. Previous work has suggested that color perception and color language appear as a suitable test bed to…
Integrating UMLS Knowledge into Large Language Models for Medical Question Answering
Rui Yang, Edison Marrese-Taylor, Yuhe Ke +3
Large language models (LLMs) have demonstrated powerful text generation capabilities, bringing unprecedented innovation to the healthcare field. While LLMs hold immense promise for…
Target-Aware Contextual Political Bias Detection in News
Iffat Maab, Edison Marrese-Taylor, Yutaka Matsuo
Media bias detection requires comprehensive integration of information derived from multiple news sources. Sentence-level political bias detection in news is no exception, and has…
Subformer: Exploring Weight Sharing for Parameter Efficiency in Generative Transformers
Machel Reid, Edison Marrese-Taylor, Yutaka Matsuo
Transformers have shown improved performance when compared to previous architectures for sequence processing such as RNNs. Despite their sizeable performance gains, as recently sug…
VCDM: Leveraging Variational Bi-encoding and Deep Contextualized Word Representations for Improved Definition Modeling
Machel Reid, Edison Marrese-Taylor, Yutaka Matsuo
In this paper, we tackle the task of definition modeling, where the goal is to learn to generate definitions of words and phrases. Existing approaches for this task are discriminat…
A Multi-modal Approach to Fine-grained Opinion Mining on Video Reviews
Edison Marrese-Taylor, Cristian Rodriguez-Opazo, Jorge A. Balazs +2
Despite the recent advances in opinion mining for written reviews, few works have tackled the problem on other sources of reviews. In light of this issue, we propose a multi-modal…
Combining Pretrained High-Resource Embeddings and Subword Representations for Low-Resource Languages
Machel Reid, Edison Marrese-Taylor, Yutaka Matsuo
The contrast between the need for large amounts of data for current Natural Language Processing (NLP) techniques, and the lack thereof, is accentuated in the case of African langua…
Variational Inference for Learning Representations of Natural Language Edits
Edison Marrese-Taylor, Machel Reid, Yutaka Matsuo
Document editing has become a pervasive component of the production of information, with version control systems enabling edits to be efficiently stored and applied. In light of th…
An Edit-centric Approach for Wikipedia Article Quality Assessment
Edison Marrese-Taylor, Pablo Loyola, Yutaka Matsuo
We propose an edit-centric approach to assess Wikipedia article quality as a complementary alternative to current full document-based techniques. Our model consists of a main class…
Deep contextualized word representations for detecting sarcasm and irony
Suzana Ilić, Edison Marrese-Taylor, Jorge A. Balazs +1
Predicting context-dependent and non-literal utterances like sarcastic and ironic expressions still remains a challenging task in NLP, as it goes beyond linguistic patterns, encomp…
IIIDYT at IEST 2018: Implicit Emotion Classification With Deep Contextualized Word Representations
Jorge A. Balazs, Edison Marrese-Taylor, Yutaka Matsuo
In this paper we describe our system designed for the WASSA 2018 Implicit Emotion Shared Task (IEST), which obtained 2 place out of 26 teams with a test macro F1 scor…
Learning to Automatically Generate Fill-In-The-Blank Quizzes
Edison Marrese-Taylor, Ai Nakajima, Yutaka Matsuo +1
In this paper we formalize the problem automatic fill-in-the-blank question generation using two standard NLP machine learning schemes, proposing concrete deep learning models for…
IIIDYT at SemEval-2018 Task 3: Irony detection in English tweets
Edison Marrese-Taylor, Suzana Ilic, Jorge A. Balazs +2
In this paper we introduce our system for the task of Irony detection in English tweets, a part of SemEval 2018. We propose representation learning approach that relies on a multi-…
EmoAtt at EmoInt-2017: Inner attention sentence embedding for Emotion Intensity
Edison Marrese-Taylor, Yutaka Matsuo
In this paper we describe a deep learning system that has been designed and built for the WASSA 2017 Emotion Intensity Shared Task. We introduce a representation learning approach…
Mining fine-grained opinions on closed captions of YouTube videos with an attention-RNN
Edison Marrese-Taylor, Jorge A. Balazs, Yutaka Matsuo
Video reviews are the natural evolution of written product reviews. In this paper we target this phenomenon and introduce the first dataset created from closed captions of YouTube…
Refining Raw Sentence Representations for Textual Entailment Recognition via Attention
Jorge A. Balazs, Edison Marrese-Taylor, Pablo Loyola +1
In this paper we present the model used by the team Rivercorners for the 2017 RepEval shared task. First, our model separately encodes a pair of sentences into variable-length repr…
A Neural Architecture for Generating Natural Language Descriptions from Source Code Changes
Pablo Loyola, Edison Marrese-Taylor, Yutaka Matsuo
We propose a model to automatically describe changes introduced in the source code of a program using natural language. Our method receives as input a set of code commits, which co…
Replication issues in syntax-based aspect extraction for opinion mining
Edison Marrese-Taylor, Yutaka Matsuo
Reproducing experiments is an important instrument to validate previous work and build upon existing approaches. It has been tackled numerous times in different areas of science. I…