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Bang Yang

9 accepted papers

2026

Not All Tokens and Heads Are Equally Important: Dual-Level Attention Intervention for Hallucination Mitigation

AAAI 2026technical

Large vision-language models (LVLMs) have demonstrated impressive capabilities across diverse multimodal tasks, yet they remain highly susceptible to visual hallucinations (VH), often producing confident but inaccurate descriptions of visual content. Building on the insight that not all tokens and a

Cited by 0SourcePDFScholar
2024

Cyclical Contrastive Learning Based on Geodesic for Zero-shot Cross-lingual Spoken Language Understanding

ACL 2024findings

Owing to the scarcity of labeled training data, Spoken Language Understanding (SLU) is still a challenging task in low-resource languages. Therefore, zero-shot cross-lingual SLU attracts more and more attention. Contrastive learning is widely applied to explicitly align representations of similar se…

2024

Embracing Language Inclusivity and Diversity in CLIP through Continual Language Learning

AAAI 2024technical

While vision-language pre-trained models (VL-PTMs) have advanced multimodal research in recent years, their mastery in a few languages like English restricts their applicability in broader communities. To this end, there is an increasing interest in developing multilingual VL models via a joint-lear…

2024

KC-Prompt: End-To-End Knowledge-Complementary Prompting for Rehearsal-Free Continual Learning

ICASSP 2024accepted

Continuous learning requires adapting quickly to incoming tasks while avoiding catastrophic forgetting. Typical solutions resort to a rehearsal buffer to replay old data, which is intractable to apply in real-world scenarios with limited memory and inaccessible privacy. Recently, with the emergence…

Cited by 0SourceScholar
2023

MultiCapCLIP: Auto-Encoding Prompts for Zero-Shot Multilingual Visual Captioning

ACL 2023long

Supervised visual captioning models typically require a large scale of images or videos paired with descriptions in a specific language (i.e., the vision-caption pairs) for training. However, collecting and labeling large-scale datasets is time-consuming and expensive for many scenarios and language…

2023

Multimodal Prompt Learning for Product Title Generation with Extremely Limited Labels

ACL 2023findings

Generating an informative and attractive title for the product is a crucial task for e-commerce. Most existing works follow the standard multimodal natural language generation approaches, e.g., image captioning, and employ the large scale of human-labelled datasets to train desirable models. However…

Cited by 6SourcePDFScholar
2023

Unify, Align and Refine: Multi-Level Semantic Alignment for Radiology Report Generation

ICCV 2023poster

Automatic radiology report generation has attracted enormous research interest due to its practical value in reducing the workload of radiologists. However, simultaneously establishing global correspondences between the image (e.g., Chest X-ray) and its related report and local alignments between im…

Cited by 42PDFScholar
2022

Retrieve, Reason, and Refine: Generating Accurate and Faithful Patient Instructions

NeurIPS 2022accept

The "Patient Instruction" (PI), which contains critical instructional information provided both to carers and to the patient at the time of discharge, is essential for the patient to manage their condition outside hospital. An accurate and easy-to-follow PI can improve the self-management of patient…