Repairing the cracked foundation: A survey of obstacles in evaluation practices for generated text
Abstract Evaluation practices in natural language generation (NLG) have many known flaws,
but improved evaluation approaches are rarely widely adopted. This issue has become …
but improved evaluation approaches are rarely widely adopted. This issue has become …
Document-level machine translation with large language models
Large language models (LLMs) such as ChatGPT can produce coherent, cohesive, relevant,
and fluent answers for various natural language processing (NLP) tasks. Taking document …
and fluent answers for various natural language processing (NLP) tasks. Taking document …
P-transformer: Towards better document-to-document neural machine translation
Directly training a document-to-document (Doc2Doc) neural machine translation (NMT) via
Transformer from scratch, especially on small datasets, usually fails to converge. Our …
Transformer from scratch, especially on small datasets, usually fails to converge. Our …
Delta: An online document-level translation agent based on multi-level memory
Large language models (LLMs) have achieved reasonable quality improvements in
machine translation (MT). However, most current research on MT-LLMs still faces significant …
machine translation (MT). However, most current research on MT-LLMs still faces significant …
Enhancing document-level translation of large language model via translation mixed-instructions
Existing large language models (LLMs) for machine translation are typically fine-tuned on
sentence-level translation instructions and achieve satisfactory performance at the sentence …
sentence-level translation instructions and achieve satisfactory performance at the sentence …
DeMPT: Decoding-enhanced Multi-phase Prompt Tuning for Making LLMs Be Better Context-aware Translators
Generally, the decoder-only large language models (LLMs) are adapted to context-aware
neural machine translation (NMT) in a concatenating way, where LLMs take the …
neural machine translation (NMT) in a concatenating way, where LLMs take the …
Modeling consistency preference via lexical chains for document-level neural machine translation
In this paper we aim to relieve the issue of lexical translation inconsistency for document-
level neural machine translation (NMT) by modeling consistency preference for lexical …
level neural machine translation (NMT) by modeling consistency preference for lexical …
CoDoNMT: Modeling cohesion devices for document-level neural machine translation
Cohesion devices, eg, reiteration, coreference, are crucial for building cohesion links across
sentences. In this paper, we propose a document-level neural machine translation …
sentences. In this paper, we propose a document-level neural machine translation …
Refining History for Future-Aware Neural Machine Translation
Neural machine translation uses a decoder to generate target words auto-regressively by
predicting the next target word conditioned on a given source sentence and its previously …
predicting the next target word conditioned on a given source sentence and its previously …
Lexical Translation Inconsistency-Aware Document-Level Translation Repair
Following the idea of “one translation per discourse”, in this paper we aim to improve
translation consistency via document-level translation repair (DocRepair), ie, automatic post …
translation consistency via document-level translation repair (DocRepair), ie, automatic post …