Analyzing the Attention Heads for Pronoun Disambiguation in Context-aware Machine Translation Models
Fuente:
arXiv
Saved in:
| Main Authors: | Mąka, Paweł, Semerci, Yusuf Can, Scholtes, Jan, Spanakis, Gerasimos |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
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)
Sequence Shortening for Context-Aware Machine Translation
by: Mąka, Paweł, et al.
Published: (2024)
by: Mąka, Paweł, et al.
Published: (2024)
Fixed and Adaptive Simultaneous Machine Translation Strategies Using Adapters
by: Issam, Abderrahmane, et al.
Published: (2024)
by: Issam, Abderrahmane, et al.
Published: (2024)
Cross-Modal Robustness Transfer (CMRT): Training Robust Speech Translation Models Using Adversarial Text
by: Issam, Abderrahmane, et al.
Published: (2026)
by: Issam, Abderrahmane, et al.
Published: (2026)
DTW-Align: Bridging the Modality Gap in End-to-End Speech Translation with Dynamic Time Warping Alignment
by: Issam, Abderrahmane, et al.
Published: (2025)
by: Issam, Abderrahmane, et al.
Published: (2025)
Language Models as Artificial Learners: Investigating Crosslinguistic Influence
by: Issam, Abderrahmane, et al.
Published: (2026)
by: Issam, Abderrahmane, et al.
Published: (2026)
A Representation Level Analysis of NMT Model Robustness to Grammatical Errors
by: Issam, Abderrahmane, et al.
Published: (2025)
by: Issam, Abderrahmane, et al.
Published: (2025)
Which Attention Heads Matter for In-Context Learning?
by: Yin, Kayo, et al.
Published: (2025)
by: Yin, Kayo, et al.
Published: (2025)
Mixture of Attentions For Speculative Decoding
by: Zimmer, Matthieu, et al.
Published: (2024)
by: Zimmer, Matthieu, et al.
Published: (2024)
Navigating WebAI: Training Agents to Complete Web Tasks with Large Language Models and Reinforcement Learning
by: Thil, Lucas-Andreï, et al.
Published: (2024)
by: Thil, Lucas-Andreï, et al.
Published: (2024)
Active Task Disambiguation with LLMs
by: Kobalczyk, Katarzyna, et al.
Published: (2025)
by: Kobalczyk, Katarzyna, et al.
Published: (2025)
EvoMU: Evolutionary Machine Unlearning
by: Batorski, Pawel, et al.
Published: (2026)
by: Batorski, Pawel, et al.
Published: (2026)
DHA: Learning Decoupled-Head Attention from Transformer Checkpoints via Adaptive Heads Fusion
by: Chen, Yilong, et al.
Published: (2024)
by: Chen, Yilong, et al.
Published: (2024)
Steering Large Language Models for Machine Translation Personalization
by: Scalena, Daniel, et al.
Published: (2025)
by: Scalena, Daniel, et al.
Published: (2025)
On Translating Technical Terminology: A Translation Workflow for Machine-Translated Acronyms
by: Yue, Richard, et al.
Published: (2024)
by: Yue, Richard, et al.
Published: (2024)
The Anxiety of Influence: Bloom Filters in Transformer Attention Heads
by: Balogh, Peter
Published: (2026)
by: Balogh, Peter
Published: (2026)
Reference-less Analysis of Context Specificity in Translation with Personalised Language Models
by: Vincent, Sebastian, et al.
Published: (2023)
by: Vincent, Sebastian, et al.
Published: (2023)
Divide (Text) and Conquer (Sentiment): Improved Sentiment Classification by Constituent Conflict Resolution
by: Kościałkowski, Jan, et al.
Published: (2025)
by: Kościałkowski, Jan, et al.
Published: (2025)
Cost-Optimal Grouped-Query Attention for Long-Context Modeling
by: Chen, Yingfa, et al.
Published: (2025)
by: Chen, Yingfa, et al.
Published: (2025)
Integrating Pre-trained Language Model into Neural Machine Translation
by: Hwang, Soon-Jae, et al.
Published: (2023)
by: Hwang, Soon-Jae, et al.
Published: (2023)
Many-to-English Machine Translation Tools, Data, and Pretrained Models
by: Gowda, Thamme, et al.
Published: (2021)
by: Gowda, Thamme, et al.
Published: (2021)
RecurFormer: Not All Transformer Heads Need Self-Attention
by: Yan, Ruiqing, et al.
Published: (2024)
by: Yan, Ruiqing, et al.
Published: (2024)
APTQ: Attention-aware Post-Training Mixed-Precision Quantization for Large Language Models
by: Guan, Ziyi, et al.
Published: (2024)
by: Guan, Ziyi, et al.
Published: (2024)
Predicting Task Performance with Context-aware Scaling Laws
by: Montgomery, Kyle, et al.
Published: (2025)
by: Montgomery, Kyle, et al.
Published: (2025)
DynaSpec: Context-aware Dynamic Speculative Sampling for Large-Vocabulary Language Models
by: Zhang, Jinbin, et al.
Published: (2025)
by: Zhang, Jinbin, et al.
Published: (2025)
Investigating Multi-Pivot Ensembling with Massively Multilingual Machine Translation Models
by: Mohammadshahi, Alireza, et al.
Published: (2023)
by: Mohammadshahi, Alireza, et al.
Published: (2023)
On the Role of Attention Heads in Large Language Model Safety
by: Zhou, Zhenhong, et al.
Published: (2024)
by: Zhou, Zhenhong, et al.
Published: (2024)
Aligning Pre-trained Models for Spoken Language Translation
by: Sedláček, Šimon, et al.
Published: (2024)
by: Sedláček, Šimon, et al.
Published: (2024)
Decomposing Attention To Find Context-Sensitive Neurons
by: Gibson, Alex
Published: (2025)
by: Gibson, Alex
Published: (2025)
Confidence-aware Self-Semantic Distillation on Knowledge Graph Embedding
by: Liu, Yichen, et al.
Published: (2022)
by: Liu, Yichen, et al.
Published: (2022)
CERM: Context-aware Literature-based Discovery via Sentiment Analysis
by: Young, Julio Christian, et al.
Published: (2024)
by: Young, Julio Christian, et al.
Published: (2024)
MiniCPM-SALA: Hybridizing Sparse and Linear Attention for Efficient Long-Context Modeling
by: MiniCPM Team, et al.
Published: (2026)
by: MiniCPM Team, et al.
Published: (2026)
Can General-Purpose Large Language Models Generalize to English-Thai Machine Translation ?
by: Chiaranaipanich, Jirat, et al.
Published: (2024)
by: Chiaranaipanich, Jirat, et al.
Published: (2024)
Feeding Two Birds or Favoring One? Adequacy-Fluency Tradeoffs in Evaluation and Meta-Evaluation of Machine Translation
by: Shayegh, Behzad, et al.
Published: (2025)
by: Shayegh, Behzad, et al.
Published: (2025)
SEAL: Scaling to Emphasize Attention for Long-Context Retrieval
by: Lee, Changhun, et al.
Published: (2025)
by: Lee, Changhun, et al.
Published: (2025)
Predicting Anchored Text from Translation Memories for Machine Translation Using Deep Learning Methods
by: Yue, Richard, et al.
Published: (2024)
by: Yue, Richard, et al.
Published: (2024)
Emergent Communication Pretraining for Few-Shot Machine Translation
by: Li, Yaoyiran, et al.
Published: (2020)
by: Li, Yaoyiran, et al.
Published: (2020)
Ladder: A Model-Agnostic Framework Boosting LLM-based Machine Translation to the Next Level
by: Feng, Zhaopeng, et al.
Published: (2024)
by: Feng, Zhaopeng, et al.
Published: (2024)
Disambiguation-Centric Finetuning Makes Enterprise Tool-Calling LLMs More Realistic and Less Risky
by: Hathidara, Ashutosh, et al.
Published: (2025)
by: Hathidara, Ashutosh, et al.
Published: (2025)
TrICy: Trigger-guided Data-to-text Generation with Intent aware Attention-Copy
by: Agarwal, Vibhav, et al.
Published: (2024)
by: Agarwal, Vibhav, et al.
Published: (2024)
Similar Items
-
You Are What You Train: Effects of Data Composition on Training Context-aware Machine Translation Models
by: Mąka, Paweł, et al.
Published: (2025) -
Sequence Shortening for Context-Aware Machine Translation
by: Mąka, Paweł, et al.
Published: (2024) -
Fixed and Adaptive Simultaneous Machine Translation Strategies Using Adapters
by: Issam, Abderrahmane, et al.
Published: (2024) -
Cross-Modal Robustness Transfer (CMRT): Training Robust Speech Translation Models Using Adversarial Text
by: Issam, Abderrahmane, et al.
Published: (2026) -
DTW-Align: Bridging the Modality Gap in End-to-End Speech Translation with Dynamic Time Warping Alignment
by: Issam, Abderrahmane, et al.
Published: (2025)