Papers with beam-search algorithm

2 papers
Better Document-Level Machine Translation with Bayes’ Rule (2020.tacl-1)

Copied to clipboard

Challenge: Existing document translation models are based on autoregressive language models, but they are not able to be learned from monolingual documents.
Approach: They propose to use Bayes' rule to create document translation models that can be learned from only parallel sentences and monolingual documents.
Outcome: The proposed model outperforms existing document translation approaches and is based on a novel left-to-right beam-search algorithm.
Crake: Causal-Enhanced Table-Filler for Question Answering over Large Scale Knowledge Base (2022.findings-naacl)

Copied to clipboard

Challenge: Existing methods for knowledge base question answering lack causality modeling . previous work fails to model such causalities in their pipeline .
Approach: They propose a causal-enhanced table-filler to overcome sequence-modelling issues . they propose an efficient beam-search algorithm to scale complex queries on large-scale KBs.
Outcome: Experiments on LC-QuAD 1.0 show that the proposed method surpasses state-of-the-arts by a large margin while remaining time and space efficient.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations