activity
20172022
most citedEmpathic Conversations: A Multi-level Dataset of Contextualized Conversations

24 citations · 62 across the 6 of their papers we have counts for

collaborators

13 papers

cs.CL202224 cited

Empathic Conversations: A Multi-level Dataset of Contextualized Conversations

Damilola Omitaomu, Shabnam Tafreshi, Tingting Liu +5

Empathy is a cognitive and emotional reaction to an observed situation of others. Empathy has recently attracted interest because it has numerous applications in psychology and AI,…

cs.CL2019

Learning Word Ratings for Empathy and Distress from Document-Level User Responses

João Sedoc, Sven Buechel, Yehonathan Nachmany +2

Despite the excellent performance of black box approaches to modeling sentiment and emotion, lexica (sets of informative words and associated weights) that characterize different e…

cs.CL2019

Comparison of Diverse Decoding Methods from Conditional Language Models

Daphne Ippolito, Reno Kriz, Maria Kustikova +2

While conditional language models have greatly improved in their ability to output high-quality natural language, many NLP applications benefit from being able to generate a divers…

cs.CL2019

Conceptor Debiasing of Word Representations Evaluated on WEAT

Saket Karve, Lyle Ungar, João Sedoc

Bias in word embeddings such as Word2Vec has been widely investigated, and many efforts made to remove such bias. We show how to use conceptors debiasing to post-process both tradi…

cs.LG20197 cited

Continual Learning for Sentence Representations Using Conceptors

Tianlin Liu, Lyle Ungar, João Sedoc

Distributed representations of sentences have become ubiquitous in natural language processing tasks. In this paper, we consider a continual learning scenario for sentence represen…

cs.CL20195 cited

Complexity-Weighted Loss and Diverse Reranking for Sentence Simplification

Reno Kriz, João Sedoc, Marianna Apidianaki +4

Sentence simplification is the task of rewriting texts so they are easier to understand. Recent research has applied sequence-to-sequence (Seq2Seq) models to this task, focusing la…