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20182022
most citedControlled Text Generation as Continuous Optimization with Multiple Constraints

2 citations · 4 across the 3 of their papers we have counts for

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cs.CL20221 cited

Referee: Reference-Free Sentence Summarization with Sharper Controllability through Symbolic Knowledge Distillation

Melanie Sclar, Peter West, Sachin Kumar +2

We present Referee, a novel framework for sentence summarization that can be trained reference-free (i.e., requiring no gold summaries for supervision), while allowing direct contr…

cs.CL20212 cited

Controlled Text Generation as Continuous Optimization with Multiple Constraints

Sachin Kumar, Eric Malmi, Aliaksei Severyn +1

As large-scale language model pretraining pushes the state-of-the-art in text generation, recent work has turned to controlling attributes of the text such models generate. While m…

cs.CL2021

Machine Translation into Low-resource Language Varieties

Sachin Kumar, Antonios Anastasopoulos, Shuly Wintner +1

State-of-the-art machine translation (MT) systems are typically trained to generate the "standard" target language; however, many languages have multiple varieties (regional variet…

cs.CL20201 cited

A Deep Reinforced Model for Zero-Shot Cross-Lingual Summarization with Bilingual Semantic Similarity Rewards

Zi-Yi Dou, Sachin Kumar, Yulia Tsvetkov

Cross-lingual text summarization aims at generating a document summary in one language given input in another language. It is a practically important but under-explored task, prima…

cs.CL2018

Von Mises-Fisher Loss for Training Sequence to Sequence Models with Continuous Outputs

Sachin Kumar, Yulia Tsvetkov

The Softmax function is used in the final layer of nearly all existing sequence-to-sequence models for language generation. However, it is usually the slowest layer to compute whic…