2 citations · 7 across the 15 of their papers we have counts for
7 papers · 1 filter
Look, Compare, Decide: Alleviating Hallucination in Large Vision-Language Models via Multi-View Multi-Path Reasoning
Xiaoye Qu, Jiashuo Sun, Wei Wei +1
Recently, Large Vision-Language Models (LVLMs) have demonstrated impressive capabilities in multi-modal context comprehension. However, they still suffer from hallucination problem…
Alleviating Hallucination in Large Vision-Language Models with Active Retrieval Augmentation
Xiaoye Qu, Qiyuan Chen, Wei Wei +2
Despite the remarkable ability of large vision-language models (LVLMs) in image comprehension, these models frequently generate plausible yet factually incorrect responses, a pheno…
Mitigating Multilingual Hallucination in Large Vision-Language Models
Xiaoye Qu, Mingyang Song, Wei Wei +2
While Large Vision-Language Models (LVLMs) have exhibited remarkable capabilities across a wide range of tasks, they suffer from hallucination problems, where models generate plaus…
Mitigating Boundary Ambiguity and Inherent Bias for Text Classification in the Era of Large Language Models
Zhenyi Lu, Jie Tian, Wei Wei +4
Text classification is a crucial task encountered frequently in practical scenarios, yet it is still under-explored in the era of large language models (LLMs). This study shows tha…
On Giant's Shoulders: Effortless Weak to Strong by Dynamic Logits Fusion
Chenghao Fan, Zhenyi Lu, Wei Wei +4
Efficient fine-tuning of large language models for task-specific applications is imperative, yet the vast number of parameters in these models makes their training increasingly cha…
Twin-Merging: Dynamic Integration of Modular Expertise in Model Merging
Zhenyi Lu, Chenghao Fan, Wei Wei +3
In the era of large language models, model merging is a promising way to combine multiple task-specific models into a single multitask model without extra training. However, two ch…
Reinforcement Learning with Token-level Feedback for Controllable Text Generation
Wendi Li, Wei Wei, Kaihe Xu +3
To meet the requirements of real-world applications, it is essential to control generations of large language models (LLMs). Prior research has tried to introduce reinforcement lea…