When Abel Kills Cain: What Machine Translation Cannot Capture
Fuente:
arXiv
Saved in:
| Main Authors: | Bénel, Aurélien, Falip, Joris, Lacour, Philippe |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Empathy and the Right to Be an Exception: What LLMs Can and Cannot Do
by: Kidder, William, et al.
Published: (2024)
by: Kidder, William, et al.
Published: (2024)
Can LLMs Evaluate What They Cannot Annotate? Revisiting LLM Reliability in Hate Speech Detection
by: Piot, Paloma, et al.
Published: (2025)
by: Piot, Paloma, et al.
Published: (2025)
Robust Guidance for Unsupervised Data Selection: Capturing Perplexing Named Entities for Domain-Specific Machine Translation
by: Ji, Seunghyun, et al.
Published: (2024)
by: Ji, Seunghyun, et al.
Published: (2024)
Learning When to Translate for Multilingual Reasoning
by: Kang, Deokhyung, et al.
Published: (2026)
by: Kang, Deokhyung, et al.
Published: (2026)
Only Send What You Need: Learning to Communicate Efficiently in Federated Multilingual Machine Translation
by: Chu, Yun-Wei, et al.
Published: (2024)
by: Chu, Yun-Wei, et al.
Published: (2024)
Large Language Models Cannot Self-Correct Reasoning Yet
by: Huang, Jie, et al.
Published: (2023)
by: Huang, Jie, et al.
Published: (2023)
Sociotechnical Effects of Machine Translation
by: Moorkens, Joss, et al.
Published: (2025)
by: Moorkens, Joss, et al.
Published: (2025)
Translation of Multifaceted Data without Re-Training of Machine Translation Systems
by: Moon, Hyeonseok, et al.
Published: (2024)
by: Moon, Hyeonseok, et al.
Published: (2024)
Transformer-Encoder Trees for Efficient Multilingual Machine Translation and Speech Translation
by: Guan, Yiwen, et al.
Published: (2025)
by: Guan, Yiwen, et al.
Published: (2025)
Navigating the OverKill in Large Language Models
by: Shi, Chenyu, et al.
Published: (2024)
by: Shi, Chenyu, et al.
Published: (2024)
Generating Gender Alternatives in Machine Translation
by: Garg, Sarthak, et al.
Published: (2024)
by: Garg, Sarthak, et al.
Published: (2024)
Word Alignment as Preference for Machine Translation
by: Wu, Qiyu, et al.
Published: (2024)
by: Wu, Qiyu, et al.
Published: (2024)
Interplay of Machine Translation, Diacritics, and Diacritization
by: Chen, Wei-Rui, et al.
Published: (2024)
by: Chen, Wei-Rui, et al.
Published: (2024)
Glancing Future for Simultaneous Machine Translation
by: Guo, Shoutao, et al.
Published: (2023)
by: Guo, Shoutao, et al.
Published: (2023)
What is the Best Way for ChatGPT to Translate Poetry?
by: Wang, Shanshan, et al.
Published: (2024)
by: Wang, Shanshan, et al.
Published: (2024)
Soft Token Attacks Cannot Reliably Audit Unlearning in Large Language Models
by: Chen, Haokun, et al.
Published: (2025)
by: Chen, Haokun, et al.
Published: (2025)
GPT-4V Cannot Generate Radiology Reports Yet
by: Jiang, Yuyang, et al.
Published: (2024)
by: Jiang, Yuyang, et al.
Published: (2024)
When, What, and How: Rethinking Retrieval-Enhanced Speculative Decoding
by: Fang, Min, et al.
Published: (2025)
by: Fang, Min, et al.
Published: (2025)
Retrieval-Augmented Machine Translation with Unstructured Knowledge
by: Wang, Jiaan, et al.
Published: (2024)
by: Wang, Jiaan, et al.
Published: (2024)
On the Shortcut Learning in Multilingual Neural Machine Translation
by: Wang, Wenxuan, et al.
Published: (2024)
by: Wang, Wenxuan, et al.
Published: (2024)
On Instruction-Finetuning Neural Machine Translation Models
by: Raunak, Vikas, et al.
Published: (2024)
by: Raunak, Vikas, et al.
Published: (2024)
An Interdisciplinary Approach to Human-Centered Machine Translation
by: Carpuat, Marine, et al.
Published: (2025)
by: Carpuat, Marine, et al.
Published: (2025)
Span-Level Machine Translation Meta-Evaluation
by: Perrella, Stefano, et al.
Published: (2026)
by: Perrella, Stefano, et al.
Published: (2026)
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)
A Single Model Ensemble Framework for Neural Machine Translation using Pivot Translation
by: Oh, Seokjin, et al.
Published: (2025)
by: Oh, Seokjin, et al.
Published: (2025)
Should I Share this Translation? Evaluating Quality Feedback for User Reliance on Machine Translation
by: Ki, Dayeon, et al.
Published: (2025)
by: Ki, Dayeon, et al.
Published: (2025)
Cannot See the Forest for the Trees: Invoking Heuristics and Biases to Elicit Irrational Choices of LLMs
by: Yang, Haoming, et al.
Published: (2025)
by: Yang, Haoming, et al.
Published: (2025)
CANTONMT: Investigating Back-Translation and Model-Switch Mechanisms for Cantonese-English Neural Machine Translation
by: Hong, Kung Yin, et al.
Published: (2024)
by: Hong, Kung Yin, et al.
Published: (2024)
EcoAct: Economic Agent Determines When to Register What Action
by: Zhang, Shaokun, et al.
Published: (2024)
by: Zhang, Shaokun, et al.
Published: (2024)
Learning When to Retrieve, What to Rewrite, and How to Respond in Conversational QA
by: Roy, Nirmal, et al.
Published: (2024)
by: Roy, Nirmal, et al.
Published: (2024)
What Layers When: Learning to Skip Compute in LLMs with Residual Gates
by: Laitenberger, Filipe, et al.
Published: (2025)
by: Laitenberger, Filipe, et al.
Published: (2025)
Mem-$π$: Adaptive Memory through Learning When and What to Generate
by: Wang, Xiaoqiang, et al.
Published: (2026)
by: Wang, Xiaoqiang, et al.
Published: (2026)
Beyond Correlation: Interpretable Evaluation of Machine Translation Metrics
by: Perrella, Stefano, et al.
Published: (2024)
by: Perrella, Stefano, et al.
Published: (2024)
Design of an Open-Source Architecture for Neural Machine Translation
by: Lankford, Séamus, et al.
Published: (2024)
by: Lankford, Séamus, et al.
Published: (2024)
Evaluation of Machine Translation Based on Semantic Dependencies and Keywords
by: Yuan, Kewei, et al.
Published: (2024)
by: Yuan, Kewei, et al.
Published: (2024)
Round-Trip Translation Reveals What Frontier Multilingual Benchmarks Miss
by: Skorobogat, Ronald, et al.
Published: (2026)
by: Skorobogat, Ronald, et al.
Published: (2026)
Text Style Transfer with Machine Translation for Graphic Designs
by: Budhauria, Deergh Singh, et al.
Published: (2026)
by: Budhauria, Deergh Singh, et al.
Published: (2026)
Perplexity Cannot Always Tell Right from Wrong
by: Veličković, Petar, et al.
Published: (2026)
by: Veličković, Petar, et al.
Published: (2026)
FairTranslate: An English-French Dataset for Gender Bias Evaluation in Machine Translation by Overcoming Gender Binarity
by: Jourdan, Fanny, et al.
Published: (2025)
by: Jourdan, Fanny, et al.
Published: (2025)
You Are What You Train: Effects of Data Composition on Training Context-aware Machine Translation Models
by: Mąka, Paweł, et al.
Published: (2025)
by: Mąka, Paweł, et al.
Published: (2025)
Similar Items
-
Empathy and the Right to Be an Exception: What LLMs Can and Cannot Do
by: Kidder, William, et al.
Published: (2024) -
Can LLMs Evaluate What They Cannot Annotate? Revisiting LLM Reliability in Hate Speech Detection
by: Piot, Paloma, et al.
Published: (2025) -
Robust Guidance for Unsupervised Data Selection: Capturing Perplexing Named Entities for Domain-Specific Machine Translation
by: Ji, Seunghyun, et al.
Published: (2024) -
Learning When to Translate for Multilingual Reasoning
by: Kang, Deokhyung, et al.
Published: (2026) -
Only Send What You Need: Learning to Communicate Efficiently in Federated Multilingual Machine Translation
by: Chu, Yun-Wei, et al.
Published: (2024)