1 citations · 1 across the 6 of their papers we have counts for
7 papers
ReverseMath: Answer Inversion for Scalable and Verifiable Mathematical Problem Generation
Raoyuan Zhao, Yihong Liu, Yupei Du +2
Mathematical reasoning benchmarks are vital for evaluating large language models (LLMs), but many are static and repeatedly exposed through public evaluation and training pipelines…
GHI: Graphormer over Conditioned Hypergraph Incidence for Aspect-Based Sentiment Analysis
Yu Du, Wenlong Zhu, Xingze Li +3
Aspect-based sentiment analysis (ABSA) requires models to bind sentiment evidence to the correct aspect, making it a natural testbed for fine-grained structural reasoning. We intro…
On the Ability of Transformers to Verify Plans
Yash Sarrof, Yupei Du, Katharina Stein +3
Transformers have shown inconsistent success in AI planning tasks, and theoretical understanding of when generalization should be expected has been limited. We take important steps…
Disentangling the Roles of Representation and Selection in Data Pruning
Yupei Du, Yingjin Song, Hugh Mee Wong +3
Data pruning, selecting small but impactful subsets, offers a promising way to efficiently scale NLP model training. However, existing methods often involve many different design c…
Burn After Reading: Do Multimodal Large Language Models Truly Capture Order of Events in Image Sequences?
Yingjin Song, Yupei Du, Denis Paperno +1
This paper introduces the TempVS benchmark, which focuses on temporal grounding and reasoning capabilities of Multimodal Large Language Models (MLLMs) in image sequences. TempVS co…
Transforming Dutch: Debiasing Dutch Coreference Resolution Systems for Non-binary Pronouns
Goya van Boven, Yupei Du, Dong Nguyen
Gender-neutral pronouns are increasingly being introduced across Western languages. Recent evaluations have however demonstrated that English NLP systems are unable to correctly pr…
FTFT: Efficient and Robust Fine-Tuning by Transferring Training Dynamics
Yupei Du, Albert Gatt, Dong Nguyen
Despite the massive success of fine-tuning Pre-trained Language Models (PLMs), they remain susceptible to out-of-distribution input. Dataset cartography is a simple yet effective d…