activity
20162023
most citedUsing millions of emoji occurrences to learn any-domain representations for detecting sentiment, emotion and sarcasm

431 citations · 857 across the 69 of their papers we have counts for

collaborators
Showing 2019Show all

13 papers · 1 filter

cs.CL2019

What Do You Mean `Why?': Resolving Sluices in Conversations

Victor Petrén Bach Hansen, Anders Søgaard

In conversation, we often ask one-word questions such as `Why?' or `Who?'. Such questions are typically easy for humans to answer, but can be hard for computers, because their reso…

cs.CL2019★ 2 cited

Retrieval-based Goal-Oriented Dialogue Generation

Ana Valeria Gonzalez, Isabelle Augenstein, Anders Søgaard

Most research on dialogue has focused either on dialogue generation for openended chit chat or on state tracking for goal-directed dialogue. In this work, we explore a hybrid appro…

cs.CL2019★ 1 cited

Lost in Evaluation: Misleading Benchmarks for Bilingual Dictionary Induction

Yova Kementchedjhieva, Mareike Hartmann, Anders Søgaard

The task of bilingual dictionary induction (BDI) is commonly used for intrinsic evaluation of cross-lingual word embeddings. The largest dataset for BDI was generated automatically…

cs.CL2019★ 2 cited

Domain Transfer in Dialogue Systems without Turn-Level Supervision

Joachim Bingel, Victor Petrén Bach Hansen, Ana Valeria Gonzalez +3

Task oriented dialogue systems rely heavily on specialized dialogue state tracking (DST) modules for dynamically predicting user intent throughout the conversation. State-of-the-ar…

cs.CL2019

Higher-order Comparisons of Sentence Encoder Representations

Mostafa Abdou, Artur Kulmizev, Felix Hill +2

Representational Similarity Analysis (RSA) is a technique developed by neuroscientists for comparing activity patterns of different measurement modalities (e.g., fMRI, electrophysi…

cs.CL2019★ 5 cited

Rewarding Coreference Resolvers for Being Consistent with World Knowledge

Rahul Aralikatte, Heather Lent, Ana Valeria Gonzalez +5

Unresolved coreference is a bottleneck for relation extraction, and high-quality coreference resolvers may produce an output that makes it a lot easier to extract knowledge triples…