Remedy: Learning Machine Translation Evaluation from Human Preferences with Reward Modeling
Fuente:
arXiv
Saved in:
| Main Authors: | Tan, Shaomu, Monz, Christof |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Remedy-R: Generative Reasoning for Machine Translation Evaluation without Error Annotations
by: Tan, Shaomu, et al.
Published: (2025)
by: Tan, Shaomu, et al.
Published: (2025)
Neuron Specialization: Leveraging intrinsic task modularity for multilingual machine translation
by: Tan, Shaomu, et al.
Published: (2024)
by: Tan, Shaomu, et al.
Published: (2024)
How Far Can 100 Samples Go? Unlocking Overall Zero-Shot Multilingual Translation via Tiny Multi-Parallel Data
by: Wu, Di, et al.
Published: (2024)
by: Wu, Di, et al.
Published: (2024)
On the Evaluation Practices in Multilingual NLP: Can Machine Translation Offer an Alternative to Human Translations?
by: Choenni, Rochelle, et al.
Published: (2024)
by: Choenni, Rochelle, et al.
Published: (2024)
Please Translate Again: Two Simple Experiments on Whether Human-Like Reasoning Helps Translation
by: Wu, Di, et al.
Published: (2025)
by: Wu, Di, et al.
Published: (2025)
Beyond Shared Vocabulary: Increasing Representational Word Similarities across Languages for Multilingual Machine Translation
by: Wu, Di, et al.
Published: (2023)
by: Wu, Di, et al.
Published: (2023)
Disentangling the Roles of Target-Side Transfer and Regularization in Multilingual Machine Translation
by: Meng, Yan, et al.
Published: (2024)
by: Meng, Yan, et al.
Published: (2024)
The Effect of Language Diversity When Fine-Tuning Large Language Models for Translation
by: Stap, David, et al.
Published: (2025)
by: Stap, David, et al.
Published: (2025)
Investigating Test-Time Scaling with Reranking for Machine Translation
by: Tan, Shaomu, et al.
Published: (2025)
by: Tan, Shaomu, et al.
Published: (2025)
How to Learn in a Noisy World? Self-Correcting the Real-World Data Noise in Machine Translation
by: Meng, Yan, et al.
Published: (2024)
by: Meng, Yan, et al.
Published: (2024)
IKUN for WMT24 General MT Task: LLMs Are here for Multilingual Machine Translation
by: Liao, Baohao, et al.
Published: (2024)
by: Liao, Baohao, et al.
Published: (2024)
Calibrating Translation Decoding with Quality Estimation on LLMs
by: Wu, Di, et al.
Published: (2025)
by: Wu, Di, et al.
Published: (2025)
Analyzing the Evaluation of Cross-Lingual Knowledge Transfer in Multilingual Language Models
by: Rajaee, Sara, et al.
Published: (2024)
by: Rajaee, Sara, et al.
Published: (2024)
Best-of-L: Cross-Lingual Reward Modeling for Mathematical Reasoning
by: Rajaee, Sara, et al.
Published: (2025)
by: Rajaee, Sara, et al.
Published: (2025)
Can LLMs Really Learn to Translate a Low-Resource Language from One Grammar Book?
by: Aycock, Seth, et al.
Published: (2024)
by: Aycock, Seth, et al.
Published: (2024)
Is It a Free Lunch for Removing Outliers during Pretraining?
by: Liao, Baohao, et al.
Published: (2024)
by: Liao, Baohao, et al.
Published: (2024)
The Fine-Tuning Paradox: Boosting Translation Quality Without Sacrificing LLM Abilities
by: Stap, David, et al.
Published: (2024)
by: Stap, David, et al.
Published: (2024)
Do Language Models Reason Across Languages?
by: Meng, Yan, et al.
Published: (2026)
by: Meng, Yan, et al.
Published: (2026)
3-in-1: 2D Rotary Adaptation for Efficient Finetuning, Efficient Batching and Composability
by: Liao, Baohao, et al.
Published: (2024)
by: Liao, Baohao, et al.
Published: (2024)
CRPO: Confidence-Reward Driven Preference Optimization for Machine Translation
by: Cui, Guofeng, et al.
Published: (2025)
by: Cui, Guofeng, et al.
Published: (2025)
Beyond Single-Reward: Multi-Pair, Multi-Perspective Preference Optimization for Machine Translation
by: Wang, Hao, et al.
Published: (2025)
by: Wang, Hao, et al.
Published: (2025)
ApiQ: Finetuning of 2-Bit Quantized Large Language Model
by: Liao, Baohao, et al.
Published: (2024)
by: Liao, Baohao, et al.
Published: (2024)
What Does LLM Refinement Actually Improve? A Systematic Study on Document-Level Literary Translation
by: Tan, Shaomu, et al.
Published: (2026)
by: Tan, Shaomu, et al.
Published: (2026)
On the Limits of Model Merging for Multilinguality in Pre-Training
by: Aycock, Seth, et al.
Published: (2026)
by: Aycock, Seth, et al.
Published: (2026)
Pragmatic Feature Preferences: Learning Reward-Relevant Preferences from Human Input
by: Peng, Andi, et al.
Published: (2024)
by: Peng, Andi, et al.
Published: (2024)
GRRM: Group Relative Reward Modeling for Machine Translation
by: Yang, Sen, et al.
Published: (2026)
by: Yang, Sen, et al.
Published: (2026)
Self-Hinting Language Models Enhance Reinforcement Learning
by: Liao, Baohao, et al.
Published: (2026)
by: Liao, Baohao, et al.
Published: (2026)
When Contextual Inference Fails: Cancelability in Interactive Instruction Following
by: Bila, Natalia, et al.
Published: (2026)
by: Bila, Natalia, et al.
Published: (2026)
Reward-Guided Speculative Decoding for Efficient LLM Reasoning
by: Liao, Baohao, et al.
Published: (2025)
by: Liao, Baohao, et al.
Published: (2025)
Communicating with Speakers and Listeners of Different Pragmatic Levels
by: Naszadi, Kata, et al.
Published: (2024)
by: Naszadi, Kata, et al.
Published: (2024)
VRM: Teaching Reward Models to Understand Authentic Human Preferences
by: Liu, Biao, et al.
Published: (2026)
by: Liu, Biao, et al.
Published: (2026)
SimulPL: Aligning Human Preferences in Simultaneous Machine Translation
by: Yu, Donglei, et al.
Published: (2025)
by: Yu, Donglei, et al.
Published: (2025)
Improving Machine Translation with Human Feedback: An Exploration of Quality Estimation as a Reward Model
by: He, Zhiwei, et al.
Published: (2024)
by: He, Zhiwei, et al.
Published: (2024)
AI-Assisted Human Evaluation of Machine Translation
by: Zouhar, Vilém, et al.
Published: (2024)
by: Zouhar, Vilém, et al.
Published: (2024)
Towards Reward Modeling for AI Tutors in Math Mistake Remediation
by: Petukhova, Kseniia, et al.
Published: (2026)
by: Petukhova, Kseniia, et al.
Published: (2026)
Tokenization Preference for Human and Machine Learning Model: An Annotation Study
by: Hiraoka, Tatsuya, et al.
Published: (2023)
by: Hiraoka, Tatsuya, et al.
Published: (2023)
Enhancing Human Evaluation in Machine Translation with Comparative Judgment
by: Song, Yixiao, et al.
Published: (2025)
by: Song, Yixiao, et al.
Published: (2025)
Contrastive Preference Optimization: Pushing the Boundaries of LLM Performance in Machine Translation
by: Xu, Haoran, et al.
Published: (2024)
by: Xu, Haoran, et al.
Published: (2024)
Learning Ordinal Probabilistic Reward from Preferences
by: Chen, Longze, et al.
Published: (2026)
by: Chen, Longze, et al.
Published: (2026)
Cross-Preference Learning for Sentence-Level and Context-Aware Machine Translation
by: Li, Ying, et al.
Published: (2026)
by: Li, Ying, et al.
Published: (2026)
Similar Items
-
Remedy-R: Generative Reasoning for Machine Translation Evaluation without Error Annotations
by: Tan, Shaomu, et al.
Published: (2025) -
Neuron Specialization: Leveraging intrinsic task modularity for multilingual machine translation
by: Tan, Shaomu, et al.
Published: (2024) -
How Far Can 100 Samples Go? Unlocking Overall Zero-Shot Multilingual Translation via Tiny Multi-Parallel Data
by: Wu, Di, et al.
Published: (2024) -
On the Evaluation Practices in Multilingual NLP: Can Machine Translation Offer an Alternative to Human Translations?
by: Choenni, Rochelle, et al.
Published: (2024) -
Please Translate Again: Two Simple Experiments on Whether Human-Like Reasoning Helps Translation
by: Wu, Di, et al.
Published: (2025)