2 citations · 7 across the 11 of their papers we have counts for
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cs.CL2023★ 2 cited
Extending Context Window of Large Language Models via Semantic Compression
Weizhi Fei, Xueyan Niu, Pingyi Zhou +4
Transformer-based Large Language Models (LLMs) often impose limitations on the length of the text input to ensure the generation of fluent and relevant responses. This constraint r…
cs.AI2023★ 2 cited
-CQA: Towards Knowledge Graph Complex Query Answering beyond Set Operation
Hang Yin, Zihao Wang, Weizhi Fei +1
To answer complex queries on knowledge graphs, logical reasoning over incomplete knowledge is required due to the open-world assumption. Learning-based methods are essential becaus…
cs.AI2023★ 1 cited
Wasserstein-Fisher-Rao Embedding: Logical Query Embeddings with Local Comparison and Global Transport
Zihao Wang, Weizhi Fei, Hang Yin +3
Answering complex queries on knowledge graphs is important but particularly challenging because of the data incompleteness. Query embedding methods address this issue by learning-b…