23 citations · 116 across the 34 of their papers we have counts for
13 papers · 1 filter
Oasis: Data Curation and Assessment System for Pretraining of Large Language Models
Tong Zhou, Yubo Chen, Pengfei Cao +3
Data is one of the most critical elements in building a large language model. However, existing systems either fail to customize a corpus curation pipeline or neglect to leverage c…
Query2Triple: Unified Query Encoding for Answering Diverse Complex Queries over Knowledge Graphs
Yao Xu, Shizhu He, Cunguang Wang +3
Complex Query Answering (CQA) is a challenge task of Knowledge Graph (KG). Due to the incompleteness of KGs, query embedding (QE) methods have been proposed to encode queries and e…
Interpreting Sentiment Composition with Latent Semantic Tree
Zhongtao Jiang, Yuanzhe Zhang, Cao Liu +3
As the key to sentiment analysis, sentiment composition considers the classification of a constituent via classifications of its contained sub-constituents and rules operated on th…
Prompting Vision Language Model with Knowledge from Large Language Model for Knowledge-Based VQA
Yang Zhou, Pengfei Cao, Yubo Chen +2
Knowledge-based visual question answering is a very challenging and widely concerned task. Previous methods adopts the implicit knowledge in large language models (LLM) to achieve…
ZhuJiu: A Multi-dimensional, Multi-faceted Chinese Benchmark for Large Language Models
Baoli Zhang, Haining Xie, Pengfan Du +6
The unprecedented performance of large language models (LLMs) requires comprehensive and accurate evaluation. We argue that for LLMs evaluation, benchmarks need to be comprehensive…
LMTuner: An user-friendly and highly-integrable Training Framework for fine-tuning Large Language Models
Yixuan Weng, Zhiqi Wang, Huanxuan Liao +4
With the burgeoning development in the realm of large language models (LLMs), the demand for efficient incremental training tailored to specific industries and domains continues to…