1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.MM2025
Contribution-Guided Asymmetric Learning for Robust Multimodal Fusion under Imbalance and Noise
Zijing Xu, Yunfeng Kou, Kunming Wu +1
Multimodal learning faces two major challenges: modality imbalance and data noise, which significantly affect the robustness and generalization ability of models. Existing methods…
cs.AI2025
GeoGR^2:Zero-Shot Geospatial Inference via Geostatistically-Guided Iterative Refinement with LLMs
Jinfan Tang, Kunming Wu, Xieruifeng Gong +4
Standard large language model prompting treats geospatial inference as independent, instance-wise prediction, ignoring the fundamental spatial dependencies that govern geographic r…
cs.CL2023★ 1 cited
ProSG: Using Prompt Synthetic Gradients to Alleviate Prompt Forgetting of RNN-like Language Models
Haotian Luo, Kunming Wu, Cheng Dai +2
RNN-like language models are getting renewed attention from NLP researchers in recent years and several models have made significant progress, which demonstrates performance compar…