Don't Rank, Combine! Combining Machine Translation Hypotheses Using Quality Estimation
Fuente:
arXiv
Saved in:
| Main Authors: | Vernikos, Giorgos, Popescu-Belis, Andrei |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Assessing the Importance of Frequency versus Compositionality for Subword-based Tokenization in NMT
by: Wolleb, Benoist, et al.
Published: (2023)
by: Wolleb, Benoist, et al.
Published: (2023)
Conversational Agents and the Understanding of Human Language: Reflections on AI, LLMs, and Cognitive Science
by: Popescu-Belis, Andrei
Published: (2026)
by: Popescu-Belis, Andrei
Published: (2026)
Small Language Models Improve Giants by Rewriting Their Outputs
by: Vernikos, Giorgos, et al.
Published: (2023)
by: Vernikos, Giorgos, et al.
Published: (2023)
Chain-of-Thought Reasoning Improves Context-Aware Translation with Large Language Models
by: Ataee, Shabnam, et al.
Published: (2025)
by: Ataee, Shabnam, et al.
Published: (2025)
Don't Pay Attention, PLANT It: Pretraining Attention via Learning-to-Rank
by: Roy, Debjyoti Saha, et al.
Published: (2024)
by: Roy, Debjyoti Saha, et al.
Published: (2024)
Speech-to-Speech Translation Pipelines for Conversations in Low-Resource Languages
by: Popescu-Belis, Andrei, et al.
Published: (2025)
by: Popescu-Belis, Andrei, et al.
Published: (2025)
If You Don't Understand It, Don't Use It: Eliminating Trojans with Filters Between Layers
by: Hernandez, Adriano
Published: (2024)
by: Hernandez, Adriano
Published: (2024)
Don't Walk the Line: Boundary Guidance for Filtered Generation
by: Ball, Sarah, et al.
Published: (2025)
by: Ball, Sarah, et al.
Published: (2025)
I Don't Know: Explicit Modeling of Uncertainty with an [IDK] Token
by: Cohen, Roi, et al.
Published: (2024)
by: Cohen, Roi, et al.
Published: (2024)
Reasoning Models Don't Just Think Longer, They Move Differently
by: Gjølbye, Anders, et al.
Published: (2026)
by: Gjølbye, Anders, et al.
Published: (2026)
Sample, Don't Search: Rethinking Test-Time Alignment for Language Models
by: Faria, Gonçalo, et al.
Published: (2025)
by: Faria, Gonçalo, et al.
Published: (2025)
Predict, Don't React: Value-Based Safety Forecasting for LLM Streaming
by: Kavumba, Pride, et al.
Published: (2026)
by: Kavumba, Pride, et al.
Published: (2026)
Don't Read Everything: A Curvature-Conditioned Query for Linear Attention
by: Le, Dong, et al.
Published: (2026)
by: Le, Dong, et al.
Published: (2026)
Domain-Specific Quality Estimation for Machine Translation in Low-Resource Scenarios
by: Gurav, Namrata Patil, et al.
Published: (2026)
by: Gurav, Namrata Patil, et al.
Published: (2026)
Don't Shoot The Breeze: Topic Continuity Model Using Nonlinear Naive Bayes With Attention
by: Pi, Shu-Ting, et al.
Published: (2026)
by: Pi, Shu-Ting, et al.
Published: (2026)
Optimizing the Training Schedule of Multilingual NMT using Reinforcement Learning
by: Allemann, Alexis, et al.
Published: (2024)
by: Allemann, Alexis, et al.
Published: (2024)
Reasoning Models Don't Always Say What They Think
by: Chen, Yanda, et al.
Published: (2025)
by: Chen, Yanda, et al.
Published: (2025)
Condense, Don't Just Prune: Enhancing Efficiency and Performance in MoE Layer Pruning
by: Cao, Mingyu, et al.
Published: (2024)
by: Cao, Mingyu, et al.
Published: (2024)
Don't Ignore the Tail: Decoupling top-K Probabilities for Efficient Language Model Distillation
by: Dasgupta, Sayantan, et al.
Published: (2026)
by: Dasgupta, Sayantan, et al.
Published: (2026)
Why Don't Prompt-Based Fairness Metrics Correlate?
by: Zayed, Abdelrahman, et al.
Published: (2024)
by: Zayed, Abdelrahman, et al.
Published: (2024)
Don't Trust: Verify -- Grounding LLM Quantitative Reasoning with Autoformalization
by: Zhou, Jin Peng, et al.
Published: (2024)
by: Zhou, Jin Peng, et al.
Published: (2024)
You Don't Need Prompt Engineering Anymore: The Prompting Inversion
by: Khan, Imran
Published: (2025)
by: Khan, Imran
Published: (2025)
QUEST: Quality-Aware Metropolis-Hastings Sampling for Machine Translation
by: Faria, Gonçalo R. A., et al.
Published: (2024)
by: Faria, Gonçalo R. A., et al.
Published: (2024)
Attention Is All You Need But You Don't Need All Of It For Inference of Large Language Models
by: Tyukin, Georgy, et al.
Published: (2024)
by: Tyukin, Georgy, et al.
Published: (2024)
Don't lie to your friends: Learning what you know from collaborative self-play
by: Eisenstein, Jacob, et al.
Published: (2025)
by: Eisenstein, Jacob, et al.
Published: (2025)
Don't Throw Away Your Beams: Improving Consistency-based Uncertainties in LLMs via Beam Search
by: Fadeeva, Ekaterina, et al.
Published: (2025)
by: Fadeeva, Ekaterina, et al.
Published: (2025)
Large Language Models Must Be Taught to Know What They Don't Know
by: Kapoor, Sanyam, et al.
Published: (2024)
by: Kapoor, Sanyam, et al.
Published: (2024)
Automatic Machine Translation Detection Using a Surrogate Multilingual Translation Model
by: García-Romero, Cristian, et al.
Published: (2025)
by: García-Romero, Cristian, et al.
Published: (2025)
Life Cycle-Aware Evaluation of Knowledge Distillation for Machine Translation: Environmental Impact and Translation Quality Trade-offs
by: Attieh, Joseph, et al.
Published: (2026)
by: Attieh, Joseph, et al.
Published: (2026)
Don't "Overthink" Passage Reranking: Is Reasoning Truly Necessary?
by: Jedidi, Nour, et al.
Published: (2025)
by: Jedidi, Nour, et al.
Published: (2025)
Attention Mechanisms Don't Learn Additive Models: Rethinking Feature Importance for Transformers
by: Leemann, Tobias, et al.
Published: (2024)
by: Leemann, Tobias, et al.
Published: (2024)
Don't Just Say "I don't know"! Self-aligning Large Language Models for Responding to Unknown Questions with Explanations
by: Deng, Yang, et al.
Published: (2024)
by: Deng, Yang, et al.
Published: (2024)
AQuA -- Combining Experts' and Non-Experts' Views To Assess Deliberation Quality in Online Discussions Using LLMs
by: Behrendt, Maike, et al.
Published: (2024)
by: Behrendt, Maike, et al.
Published: (2024)
The Compliance Gap: Why AI Systems Promise to Follow Process Instructions but Don't
by: Shin, Kwan Soo
Published: (2026)
by: Shin, Kwan Soo
Published: (2026)
LLMs Don't Know Their Own Decision Boundaries: The Unreliability of Self-Generated Counterfactual Explanations
by: Mayne, Harry, et al.
Published: (2025)
by: Mayne, Harry, et al.
Published: (2025)
LLM Cyber Evaluations Don't Capture Real-World Risk
by: Lukošiūtė, Kamilė, et al.
Published: (2025)
by: Lukošiūtė, Kamilė, et al.
Published: (2025)
Can the Variation of Model Weights be used as a Criterion for Self-Paced Multilingual NMT?
by: Atrio, Àlex R., et al.
Published: (2024)
by: Atrio, Àlex R., et al.
Published: (2024)
Don't Blame the Annotator: Bias Already Starts in the Annotation Instructions
by: Parmar, Mihir, et al.
Published: (2022)
by: Parmar, Mihir, et al.
Published: (2022)
Revisiting Padded Transformer Expressivity: Which Architectural Choices Matter and Which Don't
by: Svete, Anej, et al.
Published: (2026)
by: Svete, Anej, et al.
Published: (2026)
Don't Forget Imagination!
by: Vityaev, Evgenii E., et al.
Published: (2025)
by: Vityaev, Evgenii E., et al.
Published: (2025)
Similar Items
-
Assessing the Importance of Frequency versus Compositionality for Subword-based Tokenization in NMT
by: Wolleb, Benoist, et al.
Published: (2023) -
Conversational Agents and the Understanding of Human Language: Reflections on AI, LLMs, and Cognitive Science
by: Popescu-Belis, Andrei
Published: (2026) -
Small Language Models Improve Giants by Rewriting Their Outputs
by: Vernikos, Giorgos, et al.
Published: (2023) -
Chain-of-Thought Reasoning Improves Context-Aware Translation with Large Language Models
by: Ataee, Shabnam, et al.
Published: (2025) -
Don't Pay Attention, PLANT It: Pretraining Attention via Learning-to-Rank
by: Roy, Debjyoti Saha, et al.
Published: (2024)