18 citations · 41 across the 38 of their papers we have counts for
8 papers · 1 filter
Multilingual LLM Prompting Strategies for Medical English-Vietnamese Machine Translation
Nhu Vo, Nu-Uyen-Phuong Le, Dung D. Le +2
Medical English-Vietnamese machine translation (En-Vi MT) is essential for healthcare access and communication in Vietnam, yet Vietnamese remains a low-resource and under-studied l…
Logical Reasoning with Outcome Reward Models for Test-Time Scaling
Ramya Keerthy Thatikonda, Wray Buntine, Ehsan Shareghi
Logical reasoning is a critical benchmark for evaluating the capabilities of large language models (LLMs), as it reflects their ability to derive valid conclusions from given premi…
ALScope: A Unified Toolkit for Deep Active Learning
Chenkai Wu, Yuanyuan Qi, Xiaohao Yang +4
Deep Active Learning (DAL) reduces annotation costs by selecting the most informative unlabeled samples during training. As real-world applications become more complex, challenges…
Uncertainty-Based Methods for Automated Process Reward Data Construction and Output Aggregation in Mathematical Reasoning
Jiuzhou Han, Wray Buntine, Ehsan Shareghi
Large language models have demonstrated remarkable capabilities in complex mathematical reasoning tasks, but they inevitably generate errors throughout multi-step solutions. Proces…
MoTime: A Dataset Suite for Multimodal Time Series Forecasting
Xin Zhou, Weiqing Wang, Francisco J. Baldán +2
While multimodal data sources are increasingly available from real-world forecasting, most existing research remains on unimodal time series. In this work, we present MoTime, a sui…
DPL: Decoupled Prototype Learning for Enhancing Robustness of Vision-Language Transformers to Missing Modalities
Jueqing Lu, Yuanyuan Qi, Xiaohao Yang +8
The performance of Visio-Language Transformers drops sharply when an input modality (e.g., image) is missing, because the model is forced to make predictions using incomplete infor…
VerifiAgent: a Unified Verification Agent in Language Model Reasoning
Jiuzhou Han, Wray Buntine, Ehsan Shareghi
Large language models demonstrate remarkable reasoning capabilities but often produce unreliable or incorrect responses. Existing verification methods are typically model-specific…
Assessing the Sensitivity and Alignment of FOL Closeness Metrics
Ramya Keerthy Thatikonda, Wray Buntine, Ehsan Shareghi
The recent successful paradigm of solving logical reasoning problems with tool-augmented large language models (LLMs) leverages translation of natural language (NL) statements into…