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Found 8 papers, 7 papers with code
Prediction Difference Regularization against Perturbation for Neural Machine Translation
Regularization methods applying input perturbation have drawn considerable attention and have been frequently explored for NMT tasks in recent years.
SiLLM: Large Language Models for Simultaneous Machine Translation
We propose SiLLM, which delegates the two sub-tasks to separate agents, thereby incorporating LLM into SiMT.
Non-autoregressive Streaming Transformer for Simultaneous Translation
Simultaneous machine translation (SiMT) models are trained to strike a balance between latency and translation quality.
BayLing: Bridging Cross-lingual Alignment and Instruction Following through Interactive Translation for Large Language Models
To minimize human workload, we propose to transfer the capabilities of language generation and instruction following from English to other languages through an interactive translation task.
Fuzzy Alignments in Directed Acyclic Graph for Non-Autoregressive Machine Translation
Non-autoregressive translation (NAT) reduces the decoding latency but suffers from performance degradation due to the multi-modality problem.
Viterbi Decoding of Directed Acyclic Transformer for Non-Autoregressive Machine Translation
Non-autoregressive models achieve significant decoding speedup in neural machine translation but lack the ability to capture sequential dependency.
Smoothed Multi-View Subspace Clustering
In recent years, multi-view subspace clustering has achieved impressive performance due to the exploitation of complementary imformation across multiple views.
Towards Clustering-friendly Representations: Subspace Clustering via Graph Filtering
The success of subspace clustering depends on the assumption that the data can be separated into different subspaces.
