activity
20232026
most citedEnhancing Short-Term Wind Speed Forecasting using Graph Attention and Frequency-Enhanced Mechanisms

3 citations · 4 across the 6 of their papers we have counts for

collaborators

6 papers

cs.LG2026

Toward Robust Open-set Adaptation: Synapse Consolidation Inspired by Rac1/MAPK Pathways

Xiao Zhang, Tianyu Hu, Juntao Lyu +2

Large Language Models (LLMs) generalize across tasks through reusable representations and flexible reasoning, yet remain brittle in real deployment when faced with evolving tasks a…

cs.CL2025

Efficient Knowledge Transfer in Multi-Task Learning through Task-Adaptive Low-Rank Representation

Xiao Zhang, Kangsheng Wang, Tianyu Hu +1

Pre-trained language models (PLMs) demonstrate remarkable intelligence but struggle with emerging tasks unseen during training in real-world applications. Training separate models…

cs.AI2024★ 1 cited

CreDes: Causal Reasoning Enhancement and Dual-End Searching for Solving Long-Range Reasoning Problems using LLMs

Kangsheng Wang, Xiao Zhang, Hao Liu +3

Large language models (LLMs) have demonstrated limitations in handling combinatorial optimization problems involving long-range reasoning, partially due to causal hallucinations an…

cs.CL2024

CSCE: Boosting LLM Reasoning by Simultaneous Enhancing of Causal Significance and Consistency

Kangsheng Wang, Xiao Zhang, Juntao Lyu +2

Chain-based reasoning methods like chain of thought (CoT) play a rising role in solving reasoning tasks for large language models (LLMs). However, the causal hallucinations between…

cs.LG2023★ 3 cited

Enhancing Short-Term Wind Speed Forecasting using Graph Attention and Frequency-Enhanced Mechanisms

Hao Liu, Huimin Ma, Tianyu Hu

The safe and stable operation of power systems is greatly challenged by the high variability and randomness of wind power in large-scale wind-power-integrated grids. Wind power for…

cs.CV2023

Gestalt-Guided Image Understanding for Few-Shot Learning

Kun Song, Yuchen Wu, Jiansheng Chen +2

Due to the scarcity of available data, deep learning does not perform well on few-shot learning tasks. However, human can quickly learn the feature of a new category from very few…