5 citations · 13 across the 19 of their papers we have counts for
6 papers · 1 filter
SCOPE: Optimizing Key-Value Cache Compression in Long-context Generation
Jialong Wu, Zhenglin Wang, Linhai Zhang +3
Key-Value (KV) cache has become a bottleneck of LLMs for long-context generation. Despite the numerous efforts in this area, the optimization for the decoding phase is generally ig…
Fine-grainedly Synthesize Streaming Data Based On Large Language Models With Graph Structure Understanding For Data Sparsity
Xin Zhang, Linhai Zhang, Deyu Zhou +1
Due to the sparsity of user data, sentiment analysis on user reviews in e-commerce platforms often suffers from poor performance, especially when faced with extremely sparse user d…
Causal Walk: Debiasing Multi-Hop Fact Verification with Front-Door Adjustment
Congzhi Zhang, Linhai Zhang, Deyu Zhou
Conventional multi-hop fact verification models are prone to rely on spurious correlations from the annotation artifacts, leading to an obvious performance decline on unbiased data…
Causal Prompting: Debiasing Large Language Model Prompting based on Front-Door Adjustment
Congzhi Zhang, Linhai Zhang, Jialong Wu +2
Despite the notable advancements of existing prompting methods, such as In-Context Learning and Chain-of-Thought for Large Language Models (LLMs), they still face challenges relate…
DINER: Debiasing Aspect-based Sentiment Analysis with Multi-variable Causal Inference
Jialong Wu, Linhai Zhang, Deyu Zhou +1
Though notable progress has been made, neural-based aspect-based sentiment analysis (ABSA) models are prone to learn spurious correlations from annotation biases, resulting in poor…
STAR: Constraint LoRA with Dynamic Active Learning for Data-Efficient Fine-Tuning of Large Language Models
Linhai Zhang, Jialong Wu, Deyu Zhou +1
Though Large Language Models (LLMs) have demonstrated the powerful capabilities of few-shot learning through prompting methods, supervised training is still necessary for complex r…