collaborators

5 papers

cs.CV2026

Hard Labels In! Rethinking the Role of Hard Labels in Mitigating Local Semantic Drift

Jiacheng Cui, Bingkui Tong, Xinyue Bi +3

Soft labels from teacher models are a de facto practice for knowledge transfer and large-scale dataset distillation (e.g., SRe2L, LPLD). However, when we limit the number of crops…

cs.CV2026

Measuring Epistemic Humility in Multimodal Large Language Models

Bingkui Tong, Jiaer Xia, Sifeng Shang +1

Hallucinations in multimodal large language models (MLLMs) -- where the model generates content inconsistent with the input image -- pose significant risks in real-world applicatio…

cs.CV2026

HairOrbit: Multi-view Aware 3D Hair Modeling from Single Portraits

Leyang Jin, Yujian Zheng, Bingkui Tong +3

Reconstructing strand-level 3D hair from a single-view image is highly challenging, especially when preserving consistent and realistic attributes in unseen regions. Existing metho…

cs.CV2025

Mitigating Hallucination in Multimodal LLMs with Layer Contrastive Decoding

Bingkui Tong, Jiaer Xia, Kaiyang Zhou

Multimodal Large Language Models (MLLMs) have shown impressive perception and reasoning capabilities, yet they often suffer from hallucinations -- generating outputs that are lingu…

cs.CV2025

Bootstrapping Grounded Chain-of-Thought in Multimodal LLMs for Data-Efficient Model Adaptation

Jiaer Xia, Bingkui Tong, Yuhang Zang +2

Multimodal Large Language Models (MLLMs) have demonstrated remarkable capabilities in interpreting images using natural language. However, without using large-scale datasets for re…