Search Results for author:
Found 32 papers, 15 papers with code
DepecheMood: a Lexicon for Emotion Analysis from Crowd-Annotated News
While many lexica annotated with words polarity are available for sentiment analysis, very few tackle the harder task of emotion analysis and are usually quite limited in coverage.
Deep Feelings: A Massive Cross-Lingual Study on the Relation between Emotions and Virality
This article provides a comprehensive investigation on the relations between virality of news articles and the emotions they are found to evoke.
SALSA: A Novel Dataset for Multimodal Group Behavior Analysis
Studying free-standing conversational groups (FCGs) in unstructured social settings (e. g., cocktail party ) is gratifying due to the wealth of information available at the group (mining social networks) and individual (recognizing native behavioral and personality traits) levels.
The Death and Life of Great Italian Cities: A Mobile Phone Data Perspective
This is mainly because it is hard to collect data about "city life".
Computers and Society Social and Information Networks Physics and Society
Fortia-FBK at SemEval-2017 Task 5: Bullish or Bearish? Inferring Sentiment towards Brands from Financial News Headlines
In this paper, we describe a methodology to infer Bullish or Bearish sentiment towards companies/brands.
DepecheMood++: a Bilingual Emotion Lexicon Built Through Simple Yet Powerful Techniques
Several lexica for sentiment analysis have been developed and made available in the NLP community.
Self-Attention Architectures for Answer-Agnostic Neural Question Generation
Neural architectures based on self-attention, such as Transformers, recently attracted interest from the research community, and obtained significant improvements over the state of the art in several tasks.
Answers Unite! Unsupervised Metrics for Reinforced Summarization Models
Abstractive summarization approaches based on Reinforcement Learning (RL) have recently been proposed to overcome classical likelihood maximization.
Ask to Learn: A Study on Curiosity-driven Question Generation
We propose a novel text generation task, namely Curiosity-driven Question Generation.
Conversational Question Answering
Machine Reading Comprehension
+3
Discriminative Adversarial Search for Abstractive Summarization
We introduce a novel approach for sequence decoding, Discriminative Adversarial Search (DAS), which has the desirable properties of alleviating the effects of exposure bias without requiring external metrics.
What BERT Sees: Cross-Modal Transfer for Visual Question Generation
Pre-trained language models have recently contributed to significant advances in NLP tasks.
MLSUM: The Multilingual Summarization Corpus
We present MLSUM, the first large-scale MultiLingual SUMmarization dataset.
ColdGANs: Taming Language GANs with Cautious Sampling Strategies
Training regimes based on Maximum Likelihood Estimation (MLE) suffer from known limitations, often leading to poorly generated text sequences.
Project PIAF: Building a Native French Question-Answering Dataset
Motivated by the lack of data for non-English languages, in particular for the evaluation of downstream tasks such as Question Answering, we present a participatory effort to collect a native French Question Answering Dataset.
Ranked #4 on
Question Answering
on FQuAD
(using extra training data)
Toward Stance-based Personas for Opinionated Dialogues
In the context of chit-chat dialogues it has been shown that endowing systems with a persona profile is important to produce more coherent and meaningful conversations.
Synthetic Data Augmentation for Zero-Shot Cross-Lingual Question Answering
Coupled with the availability of large scale datasets, deep learning architectures have enabled rapid progress on the Question Answering task.
QuestEval: Summarization Asks for Fact-based Evaluation
Summarization evaluation remains an open research problem: current metrics such as ROUGE are known to be limited and to correlate poorly with human judgments.
Rethinking Automatic Evaluation in Sentence Simplification
In the context of Sentence Simplification, this is particularly challenging: the task requires by nature to replace complex words with simpler ones that shares the same meaning.
Data-QuestEval: A Referenceless Metric for Data-to-Text Semantic Evaluation
QuestEval is a reference-less metric used in text-to-text tasks, that compares the generated summaries directly to the source text, by automatically asking and answering questions.
To Beam Or Not To Beam: That is a Question of Cooperation for Language GANs
Due to the discrete nature of words, language GANs require to be optimized from rewards provided by discriminator networks, via reinforcement learning methods.
Skim-Attention: Learning to Focus via Document Layout
Motivated by human reading strategies, this paper presents Skim-Attention, a new attention mechanism that takes advantage of the structure of the document and its layout.
Generative Cooperative Networks for Natural Language Generation
Generative Adversarial Networks (GANs) have known a tremendous success for many continuous generation tasks, especially in the field of image generation.
Which Discriminator for Cooperative Text Generation?
Language models generate texts by successively predicting probability distributions for next tokens given past ones.
LoRaLay: A Multilingual and Multimodal Dataset for Long Range and Layout-Aware Summarization
Text Summarization is a popular task and an active area of research for the Natural Language Processing community.
Let's ViCE! Mimicking Human Cognitive Behavior in Image Generation Evaluation
Research in Image Generation has recently made significant progress, particularly boosted by the introduction of Vision-Language models which are able to produce high-quality visual content based on textual inputs.
Glitter or Gold? Deriving Structured Insights from Sustainability Reports via Large Language Models
This poses a challenge in efficiently gathering and aligning the data into a unified framework to derive insights related to Corporate Social Responsibility (CSR).
Countering Misinformation via Emotional Response Generation
The proliferation of misinformation on social media platforms (SMPs) poses a significant danger to public health, social cohesion and ultimately democracy.
The Garden of Forking Paths: Observing Dynamic Parameters Distribution in Large Language Models
A substantial gap persists in understanding the reasons behind the exceptional performance of the Transformer architecture in NLP.
Can LLMs Correct Physicians, Yet? Investigating Effective Interaction Methods in the Medical Domain
We explore the potential of Large Language Models (LLMs) to assist and potentially correct physicians in medical decision-making tasks.
Unveiling LLMs: The Evolution of Latent Representations in a Temporal Knowledge Graph
We propose an end-to-end framework that jointly decodes the factual knowledge embedded in the latent space of LLMs from a vector space to a set of ground predicates and represents its evolution across the layers using a temporal knowledge graph.
Choisir le bon co-équipier pour la génération coopérative de texte (Choosing The Right Teammate For Cooperative Text Generation)
Nous évaluons leurs avantages et inconvénients, en explorant leur précision respective sur des tâches de classification, ainsi que leur impact sur la génération coopérative et leur coût de calcul, dans le cadre d’une stratégie de décodage état de l’art, basée sur une recherche arborescente de Monte-Carlo (MCTS).
