1 citations · 1 across the 5 of their papers we have counts for
5 papers
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…
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…
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…
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…
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…