most citedSometimes We Want Translationese

4 citations · 8 across the 4 of their papers we have counts for

collaborators

5 papers

cs.LG20214 cited

OptiDICE: Offline Policy Optimization via Stationary Distribution Correction Estimation

Jongmin Lee, Wonseok Jeon, Byung-Jun Lee +2

We consider the offline reinforcement learning (RL) setting where the agent aims to optimize the policy solely from the data without further environment interactions. In offline RL…

cs.CL2021

Do Encoder Representations of Generative Dialogue Models Encode Sufficient Information about the Task ?

Prasanna Parthasarathi, Joelle Pineau, Sarath Chandar

Predicting the next utterance in dialogue is contingent on encoding of users' input text to generate appropriate and relevant response in data-driven approaches. Although the seman…

cs.CL2021

A Brief Study on the Effects of Training Generative Dialogue Models with a Semantic loss

Prasanna Parthasarathi, Mohamed Abdelsalam, Joelle Pineau +1

Neural models trained for next utterance generation in dialogue task learn to mimic the n-gram sequences in the training set with training objectives like negative log-likelihood (…

cs.CL20214 cited

Sometimes We Want Translationese

Prasanna Parthasarathi, Koustuv Sinha, Joelle Pineau +1

Rapid progress in Neural Machine Translation (NMT) systems over the last few years has been driven primarily towards improving translation quality, and as a secondary focus, improv…

cs.CL2021

Masked Language Modeling and the Distributional Hypothesis: Order Word Matters Pre-training for Little

Koustuv Sinha, Robin Jia, Dieuwke Hupkes +3

A possible explanation for the impressive performance of masked language model (MLM) pre-training is that such models have learned to represent the syntactic structures prevalent i…