7 citations · 9 across the 4 of their papers we have counts for
7 papers
InternLM2 Technical Report
Zheng Cai, Maosong Cao, Haojiong Chen +97
The evolution of Large Language Models (LLMs) like ChatGPT and GPT-4 has sparked discussions on the advent of Artificial General Intelligence (AGI). However, replicating such advan…
LongWanjuan: Towards Systematic Measurement for Long Text Quality
Kai Lv, Xiaoran Liu, Qipeng Guo +4
The quality of training data are crucial for enhancing the long-text capabilities of foundation models. Despite existing efforts to refine data quality through heuristic rules and…
Code Needs Comments: Enhancing Code LLMs with Comment Augmentation
Demin Song, Honglin Guo, Yunhua Zhou +8
The programming skill is one crucial ability for Large Language Models (LLMs), necessitating a deep understanding of programming languages (PLs) and their correlation with natural…
An AMR-based Link Prediction Approach for Document-level Event Argument Extraction
Yuqing Yang, Qipeng Guo, Xiangkun Hu +3
Recent works have introduced Abstract Meaning Representation (AMR) for Document-level Event Argument Extraction (Doc-level EAE), since AMR provides a useful interpretation of compl…
Do Large Language Models Know What They Don't Know?
Zhangyue Yin, Qiushi Sun, Qipeng Guo +3
Large language models (LLMs) have a wealth of knowledge that allows them to excel in various Natural Language Processing (NLP) tasks. Current research focuses on enhancing their pe…
Exploiting Abstract Meaning Representation for Open-Domain Question Answering
Cunxiang Wang, Zhikun Xu, Qipeng Guo +4
The Open-Domain Question Answering (ODQA) task involves retrieving and subsequently generating answers from fine-grained relevant passages within a database. Current systems levera…