10 citations · 45 across the 14 of their papers we have counts for
15 papers
Uncertainty in Natural Language Generation: From Theory to Applications
Joris Baan, Nico Daheim, Evgenia Ilia +7
Recent advances of powerful Language Models have allowed Natural Language Generation (NLG) to emerge as an important technology that can not only perform traditional tasks like sum…
Structural Persistence in Language Models: Priming as a Window into Abstract Language Representations
Arabella Sinclair, Jaap Jumelet, Willem Zuidema +1
We investigate the extent to which modern, neural language models are susceptible to structural priming, the phenomenon whereby the structure of a sentence makes the same structure…
Words are the Window to the Soul: Language-based User Representations for Fake News Detection
Marco Del Tredici, Raquel Fernández
Cognitive and social traits of individuals are reflected in language use. Moreover, individuals who are prone to spread fake news online often share common traits. Building on thes…
Generating Image Descriptions via Sequential Cross-Modal Alignment Guided by Human Gaze
Ece Takmaz, Sandro Pezzelle, Lisa Beinborn +1
When speakers describe an image, they tend to look at objects before mentioning them. In this paper, we investigate such sequential cross-modal alignment by modelling the image des…
You Shall Know a User by the Company It Keeps: Dynamic Representations for Social Media Users in NLP
Marco Del Tredici, Diego Marcheggiani, Sabine Schulte im Walde +1
Information about individuals can help to better understand what they say, particularly in social media where texts are short. Current approaches to modelling social media users pa…
The PhotoBook Dataset: Building Common Ground through Visually-Grounded Dialogue
Janosch Haber, Tim Baumgärtner, Ece Takmaz +3
This paper introduces the PhotoBook dataset, a large-scale collection of visually-grounded, task-oriented dialogues in English designed to investigate shared dialogue history accum…
Psycholinguistics meets Continual Learning: Measuring Catastrophic Forgetting in Visual Question Answering
Claudio Greco, Barbara Plank, Raquel Fernández +1
We study the issue of catastrophic forgetting in the context of neural multimodal approaches to Visual Question Answering (VQA). Motivated by evidence from psycholinguistics, we de…
Automatic Evaluation of Neural Personality-based Chatbots
Yujie Xing, Raquel Fernández
Stylistic variation is critical to render the utterances generated by conversational agents natural and engaging. In this paper, we focus on sequence-to-sequence models for open-do…
Beyond task success: A closer look at jointly learning to see, ask, and GuessWhat
Ravi Shekhar, Aashish Venkatesh, Tim Baumgärtner +4
We propose a grounded dialogue state encoder which addresses a foundational issue on how to integrate visual grounding with dialogue system components. As a test-bed, we focus on t…
Analysing the potential of seq-to-seq models for incremental interpretation in task-oriented dialogue
Dieuwke Hupkes, Sanne Bouwmeester, Raquel Fernández
We investigate how encoder-decoder models trained on a synthetic dataset of task-oriented dialogues process disfluencies, such as hesitations and self-corrections. We find that, co…
Semantic Variation in Online Communities of Practice
Marco Del Tredici, Raquel Fernández
We introduce a framework for quantifying semantic variation of common words in Communities of Practice and in sets of topic-related communities. We show that while some meaning shi…
The Road to Success: Assessing the Fate of Linguistic Innovations in Online Communities
Marco Del Tredici, Raquel Fernández
We investigate the birth and diffusion of lexical innovations in a large dataset of online social communities. We build on sociolinguistic theories and focus on the relation betwee…
Ask No More: Deciding when to guess in referential visual dialogue
Ravi Shekhar, Tim Baumgartner, Aashish Venkatesh +3
Our goal is to explore how the abilities brought in by a dialogue manager can be included in end-to-end visually grounded conversational agents. We make initial steps towards this…
Examining a hate speech corpus for hate speech detection and popularity prediction
Filip Klubička, Raquel Fernández
As research on hate speech becomes more and more relevant every day, most of it is still focused on hate speech detection. By attempting to replicate a hate speech detection experi…
The LAMBADA dataset: Word prediction requiring a broad discourse context
Denis Paperno, Germán Kruszewski, Angeliki Lazaridou +6
We introduce LAMBADA, a dataset to evaluate the capabilities of computational models for text understanding by means of a word prediction task. LAMBADA is a collection of narrative…