4 citations · 6 across the 14 of their papers we have counts for
14 papers
Sigmoid Head for Quality Estimation under Language Ambiguity
Tu Anh Dinh, Jan Niehues
Language model (LM) probability is not a reliable quality estimator, as natural language is ambiguous. When multiple output options are valid, the model's probability distribution…
From Slides to Chatbots: Enhancing Large Language Models with University Course Materials
Tu Anh Dinh, Philipp Nicolas Schumacher, Jan Niehues
Large Language Models (LLMs) have advanced rapidly in recent years. One application of LLMs is to support student learning in educational settings. However, prior work has shown th…
COMET-poly: Machine Translation Metric Grounded in Other Candidates
Maike Züfle, Vilém Zouhar, Tu Anh Dinh +3
Automated metrics for machine translation attempt to replicate human judgment. Unlike humans, who often assess a translation in the context of multiple alternatives, these metrics…
Knockout LLM Assessment: Using Large Language Models for Evaluations through Iterative Pairwise Comparisons
Isik Baran Sandan, Tu Anh Dinh, Jan Niehues
Large Language Models (LLMs) have shown to be effective evaluators across various domains such as machine translations or the scientific domain. Current LLM-as-a-Judge approaches r…
KIT's Low-resource Speech Translation Systems for IWSLT2025: System Enhancement with Synthetic Data and Model Regularization
Zhaolin Li, Yining Liu, Danni Liu +6
This paper presents KIT's submissions to the IWSLT 2025 low-resource track. We develop both cascaded systems, consisting of Automatic Speech Recognition (ASR) and Machine Translati…
Are Generative Models Underconfident? Better Quality Estimation with Boosted Model Probability
Tu Anh Dinh, Jan Niehues
Quality Estimation (QE) is estimating quality of the model output during inference when the ground truth is not available. Deriving output quality from the models' output probabili…
SciEx: Benchmarking Large Language Models on Scientific Exams with Human Expert Grading and Automatic Grading
Tu Anh Dinh, Carlos Mullov, Leonard Bärmann +15
With the rapid development of Large Language Models (LLMs), it is crucial to have benchmarks which can evaluate the ability of LLMs on different domains. One common use of LLMs is…
Quality Estimation with -nearest Neighbors and Automatic Evaluation for Model-specific Quality Estimation
Tu Anh Dinh, Tobias Palzer, Jan Niehues
Providing quality scores along with Machine Translation (MT) output, so-called reference-free Quality Estimation (QE), is crucial to inform users about the reliability of the trans…
End-to-End Evaluation for Low-Latency Simultaneous Speech Translation
Christian Huber, Tu Anh Dinh, Carlos Mullov +10
The challenge of low-latency speech translation has recently draw significant interest in the research community as shown by several publications and shared tasks. Therefore, it is…
KIT's Multilingual Speech Translation System for IWSLT 2023
Danni Liu, Thai Binh Nguyen, Sai Koneru +7
Many existing speech translation benchmarks focus on native-English speech in high-quality recording conditions, which often do not match the conditions in real-life use-cases. In…
Perturbation-based QE: An Explainable, Unsupervised Word-level Quality Estimation Method for Blackbox Machine Translation
Tu Anh Dinh, Jan Niehues
Quality Estimation (QE) is the task of predicting the quality of Machine Translation (MT) system output, without using any gold-standard translation references. State-of-the-art QE…
E2EG: End-to-End Node Classification Using Graph Topology and Text-based Node Attributes
Tu Anh Dinh, Jeroen den Boef, Joran Cornelisse +1
Node classification utilizing text-based node attributes has many real-world applications, ranging from prediction of paper topics in academic citation graphs to classification of…
Tackling data scarcity in speech translation using zero-shot multilingual machine translation techniques
Tu Anh Dinh, Danni Liu, Jan Niehues
Recently, end-to-end speech translation (ST) has gained significant attention as it avoids error propagation. However, the approach suffers from data scarcity. It heavily depends o…
Zero-shot Speech Translation
Tu Anh Dinh
Speech Translation (ST) is the task of translating speech in one language into text in another language. Traditional cascaded approaches for ST, using Automatic Speech Recognition…