2 citations · 2 across the 14 of their papers we have counts for
6 papers · 1 filter
The Accuracy Paradox in RLHF: When Better Reward Models Don't Yield Better Language Models
Yanjun Chen, Dawei Zhu, Yirong Sun +3
Reinforcement Learning from Human Feedback significantly enhances Natural Language Processing by aligning language models with human expectations. A critical factor in this alignme…
To Preserve or To Compress: An In-Depth Study of Connector Selection in Multimodal Large Language Models
Junyan Lin, Haoran Chen, Dawei Zhu +1
In recent years, multimodal large language models (MLLMs) have garnered significant attention from both industry and academia. However, there is still considerable debate on constr…
Fine-Grained and Multi-Dimensional Metrics for Document-Level Machine Translation
Yirong Sun, Dawei Zhu, Yanjun Chen +3
Large language models (LLMs) have excelled in various NLP tasks, including machine translation (MT), yet most studies focus on sentence-level translation. This work investigates th…
From Calculation to Adjudication: Examining LLM judges on Mathematical Reasoning Tasks
Andreas Stephan, Dawei Zhu, Matthias Aßenmacher +2
To reduce the need for human annotations, large language models (LLMs) have been proposed as judges of the quality of other candidate models. The performance of LLM judges is typic…
Assessing "Implicit" Retrieval Robustness of Large Language Models
Xiaoyu Shen, Rexhina Blloshmi, Dawei Zhu +2
Retrieval-augmented generation has gained popularity as a framework to enhance large language models with external knowledge. However, its effectiveness hinges on the retrieval rob…
InternLM-Law: An Open Source Chinese Legal Large Language Model
Zhiwei Fei, Songyang Zhang, Xiaoyu Shen +9
While large language models (LLMs) have showcased impressive capabilities, they struggle with addressing legal queries due to the intricate complexities and specialized expertise r…