Cover Image

Learning from others' mistakes: Finetuning machine translation models with span-level error annotations

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhang, Lily H., Dadkhahi, Hamid, Finkelstein, Mara, Trabelsi, Firas, Luo, Jiaming, Freitag, Markus
Format:	Preprint
Published:	2024
Subjects:	Computation and Language Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Efficient Minimum Bayes Risk Decoding using Low-Rank Matrix Completion Algorithms
by: Trabelsi, Firas, et al.
Published: (2024)

Distribution-Calibrated Inference time compute for Thinking LLM-as-a-Judge
by: Dadkhahi, Hamid, et al.
Published: (2025)

MBR and QE Finetuning: Training-time Distillation of the Best and Most Expensive Decoding Methods
by: Finkelstein, Mara, et al.
Published: (2023)

Introducing the NewsPaLM MBR and QE Dataset: LLM-Generated High-Quality Parallel Data Outperforms Traditional Web-Crawled Data
by: Finkelstein, Mara, et al.
Published: (2024)

MetricX-24: The Google Submission to the WMT 2024 Metrics Shared Task
by: Juraska, Juraj, et al.
Published: (2024)

Understanding the effects of word-level linguistic annotations in under-resourced neural machine translation
by: Sánchez-Cartagena, Víctor M., et al.
Published: (2024)

From Jack of All Trades to Master of One: Specializing LLM-based Autoraters to a Test Set
by: Finkelstein, Mara, et al.
Published: (2024)

Translating Step-by-Step: Decomposing the Translation Process for Improved Translation Quality of Long-Form Texts
by: Briakou, Eleftheria, et al.
Published: (2024)

Transfer Learning for Finetuning Large Language Models
by: Strangmann, Tobias, et al.
Published: (2024)

MQM Re-Annotation: A Technique for Collaborative Evaluation of Machine Translation
by: Riley, Parker, et al.
Published: (2025)

Generating Difficult-to-Translate Texts
by: Zouhar, Vilém, et al.
Published: (2025)

Exposing propaganda: an analysis of stylistic cues comparing human annotations and machine classification
by: Faye, Géraud, et al.
Published: (2024)

Learning Dynamics of LLM Finetuning
by: Ren, Yi, et al.
Published: (2024)

Don't Throw Away Data: Better Sequence Knowledge Distillation
by: Wang, Jun, et al.
Published: (2024)

Efficient Reinforcement Finetuning via Adaptive Curriculum Learning
by: Shi, Taiwei, et al.
Published: (2025)

KnowLA: Enhancing Parameter-efficient Finetuning with Knowledgeable Adaptation
by: Luo, Xindi, et al.
Published: (2024)

WMT24++: Expanding the Language Coverage of WMT24 to 55 Languages & Dialects
by: Deutsch, Daniel, et al.
Published: (2025)

When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method
by: Zhang, Biao, et al.
Published: (2024)

MetricX-25 and GemSpanEval: Google Translate Submissions to the WMT25 Evaluation Shared Task
by: Juraska, Juraj, et al.
Published: (2025)

Extractive Structures Learned in Pretraining Enable Generalization on Finetuned Facts
by: Feng, Jiahai, et al.
Published: (2024)

Sparse Memory Finetuning as a Low-Forgetting Alternative to LoRA and Full Finetuning
by: Gupta, Prakhar, et al.
Published: (2026)

Improving Sparse Memory Finetuning
by: Goyal, Satyam, et al.
Published: (2026)

Predicting Emergent Capabilities by Finetuning
by: Snell, Charlie, et al.
Published: (2024)

TeleDoCTR: Domain-Specific and Contextual Troubleshooting for Telecommunications
by: Trabelsi, Mohamed, et al.
Published: (2026)

Neural machine translation of clinical procedure codes for medical diagnosis and uncertainty quantification
by: Chung, Pei-Hung, et al.
Published: (2024)

Accurate LoRA-Finetuning Quantization of LLMs via Information Retention
by: Qin, Haotong, et al.
Published: (2024)

Preference learning made easy: Everything should be understood through win rate
by: Zhang, Lily H., et al.
Published: (2025)

A comparison of data filtering techniques for English-Polish LLM-based machine translation in the biomedical domain
by: Lérida, Jorge del Pozo, et al.
Published: (2025)

Quality-Aware Translation Models: Efficient Generation and Quality Estimation in a Single Model
by: Tomani, Christian, et al.
Published: (2023)

Sparse Upcycling: Inference Inefficient Finetuning
by: Doubov, Sasha, et al.
Published: (2024)

Understanding Finetuning for Factual Knowledge Extraction
by: Ghosal, Gaurav, et al.
Published: (2024)

Polynomial Regression as a Task for Understanding In-context Learning Through Finetuning and Alignment
by: Wilcoxson, Max, et al.
Published: (2024)

Order Independence With Finetuning
by: Brown, Katrina, et al.
Published: (2025)

Escaping the sentence-level paradigm in machine translation
by: Post, Matt, et al.
Published: (2023)

Transfer Learning of Tabular Data by Finetuning Large Language Models
by: Rabbani, Shourav B., et al.
Published: (2025)

Ensembling Finetuned Language Models for Text Classification
by: Arango, Sebastian Pineda, et al.
Published: (2024)

Finetune Once: Decoupling General & Domain Learning with Dynamic Boosted Annealing
by: Tang, Yang, et al.
Published: (2025)

Finetuning Language Models to Emit Linguistic Expressions of Uncertainty
by: Chaudhry, Arslan, et al.
Published: (2024)

LLMRefine: Pinpointing and Refining Large Language Models via Fine-Grained Actionable Feedback
by: Xu, Wenda, et al.
Published: (2023)

Time Series Language Model for Descriptive Caption Generation
by: Trabelsi, Mohamed, et al.
Published: (2025)