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Tao Zhu

6 accepted papers

2026

ASSESS: A Semantic and Structural Evaluation Framework for Statement Similarity

ICLR 2026poster

Despite significant strides in statement autoformalization, a critical gap remains in the development of automated evaluation metrics capable of assessing formal translation quality. Existing metrics often fail to balance semantic and structural information: string-based methods neglect semantics, w…

Cited by 0SourcecodeScholar
2024

A Framework for Real-time Generation of Multi-directional Traversability Maps in Unstructured Environments

ICRA 2024poster

In complex unstructured environments, accurate terrain traversability analysis is a fundamental requirement for the successful execution of any movements of ground robots, especially given that terrain traversability often exhibits anisotropy. However, the difficulty in obtaining multi-directional t…

Cited by 1SourceScholar
2024

IG Captioner: Information Gain Captioners are Strong Zero-shot Classifiers

ECCV 2024poster

"Generative training has been demonstrated to be powerful for building visual-language models. However, on zero-shot discriminative benchmarks, there is still a performance gap between models trained with generative and discriminative objectives. In this paper, we aim to narrow this gap by improving…

Cited by 3SourcePDFScholar
2022

A Simple and Effective Method to Improve Zero-Shot Cross-Lingual Transfer Learning

COLING 2022main

Existing zero-shot cross-lingual transfer methods rely on parallel corpora or bilingual dictionaries, which are expensive and impractical for low-resource languages. To disengage from these dependencies, researchers have explored training multilingual models on English-only resources and transferrin…

2022

Parameter-efficient Continual Learning Framework in Industrial Real-time Text Classification System

NAACL 2022industry

Catastrophic forgetting is a challenge for model deployment in industrial real-time systems, which requires the model to quickly master a new task without forgetting the old one. Continual learning aims to solve this problem; however, it usually updates all the model parameters, resulting in extensi…

2019

Shape Constraints for Set Functions

ICML 2019oral

Set functions predict a label from a permutation-invariant variable-size collection of feature vectors. We propose making set functions more understandable and regularized by capturing domain knowledge through shape constraints. We show how prior work in monotonic constraints can be adapted to set f…

Cited by 25SourcePDFScholar