Zobrazeno 1 - 10
of 659
pro vyhledávání: '"Zhu, DaWei"'
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 the inherent capability of instruction-tuned LLMs for document-level tra
Externí odkaz:
http://arxiv.org/abs/2410.20941
Autor:
Song, Yifan, Xiong, Weimin, Zhao, Xiutian, Zhu, Dawei, Wu, Wenhao, Wang, Ke, Li, Cheng, Peng, Wei, Li, Sujian
Fine-tuning on agent-environment interaction trajectory data holds significant promise for surfacing generalized agent capabilities in open-source large language models (LLMs). In this work, we introduce AgentBank, by far the largest trajectory tunin
Externí odkaz:
http://arxiv.org/abs/2410.07706
In recent years, multimodal large language models (MLLMs) have garnered significant attention from both industry and academia. However, there is still considerable debate on constructing MLLM architectures, particularly regarding the selection of app
Externí odkaz:
http://arxiv.org/abs/2410.06765
Reinforcement Learning from Human Feedback significantly enhances Natural Language Processing by aligning language models with human expectations. A critical factor in this alignment is the strength of reward models used during training. This study e
Externí odkaz:
http://arxiv.org/abs/2410.06554
To reduce the need for human annotations, large language models (LLMs) have been proposed as judges of the quality of other candidate models. LLM judges are typically evaluated by measuring the correlation with human judgments on generation tasks suc
Externí odkaz:
http://arxiv.org/abs/2409.04168
Retrieval-augmented generation has gained popularity as a framework to enhance large language models with external knowledge. However, its effectiveness hinges on the retrieval robustness of the model. If the model lacks retrieval robustness, its per
Externí odkaz:
http://arxiv.org/abs/2406.18134
Personality is a fundamental construct in psychology, reflecting an individual's behavior, thinking, and emotional patterns. Previous researches have made some progress in personality detection, primarily by utilizing the whole text to predict person
Externí odkaz:
http://arxiv.org/abs/2406.16079
Autor:
Fei, Zhiwei, Zhang, Songyang, Shen, Xiaoyu, Zhu, Dawei, Wang, Xiao, Cao, Maosong, Zhou, Fengzhe, Li, Yining, Zhang, Wenwei, Lin, Dahua, Chen, Kai, Ge, Jidong
While large language models (LLMs) have showcased impressive capabilities, they struggle with addressing legal queries due to the intricate complexities and specialized expertise required in the legal field. In this paper, we introduce InternLM-Law,
Externí odkaz:
http://arxiv.org/abs/2406.14887
Effectively handling instructions with extremely long context remains a challenge for Large Language Models (LLMs), typically necessitating high-quality long data and substantial computational resources. This paper introduces Step-Skipping Alignment
Externí odkaz:
http://arxiv.org/abs/2405.03939
Traditionally, success in multilingual machine translation can be attributed to three key factors in training data: large volume, diverse translation directions, and high quality. In the current practice of fine-tuning large language models (LLMs) fo
Externí odkaz:
http://arxiv.org/abs/2404.14122