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Tianyang Zhao

7 accepted papers

2026

PanoVGGT: Feed-Forward 3D Reconstruction from Panoramic Imagery

CVPR 2026

Panoramic imagery offers a full 360^\circ field of view and is increasingly common in consumer devices. However, it introduces non-pinhole distortions that challenge joint pose estimation and 3D reconstruction. Existing feed-forward models, built for perspective cameras, generalize poorly to this se

Cited by 0SourcecodeScholar
2025

On the Analysis and Distillation of Emergent Outlier Properties in Pre-trained Language Models

NAACL 2025long

A small subset of dimensions within language Transformers’ representation spaces emerge as “outliers” during pretraining, encoding critical knowledge sparsely. We extend previous findings on emergent outliers to Encoder-Decoder Transformers and instruction-finetuned models, and tackle the problem of…

2024

No Head Left Behind – Multi-Head Alignment Distillation for Transformers

AAAI 2024technical

Knowledge distillation aims at reducing model size without compromising much performance. Recent work has applied it to large vision-language (VL) Transformers, and has shown that attention maps in the multi-head attention modules of vision-language Transformers contain extensive intra-modal and cro…

Cited by 2SourcePDFScholar
2021

A Unified Multi-Task Learning Framework for Joint Extraction of Entities and Relations

AAAI 2021technical

Joint extraction of entities and relations focuses on detecting entity pairs and their relations simultaneously with a unified model. Based on the extraction order, previous works mainly solve this task through relation-last, relation-first and relation-middle manner. However, these methods still su…

2020

Asking Effective and Diverse Questions: A Machine Reading Comprehension based Framework for Joint Entity-Relation Extraction

IJCAI 2020poster

Recent advances cast the entity-relation extraction to a multi-turn question answering (QA) task and provide an effective solution based on the machine reading comprehension (MRC) models. However, they use a single question to characterize the meaning of entities and relations, which is intuitively…

2019

Multi-Agent Tensor Fusion for Contextual Trajectory Prediction

CVPR 2019poster

Accurate prediction of others' trajectories is essential for autonomous driving. Trajectory prediction is challenging because it requires reasoning about agents' past movements, social interactions among varying numbers and kinds of agents, constraints from the scene context, and the stochasticity o…

Cited by 554PDFScholar