17 citations · 23 across the 18 of their papers we have counts for
6 papers · 1 filter
Enhancing SPARQL Generation by Triplet-order-sensitive Pre-training
Chang Su, Jiexing Qi, He Yan +2
Semantic parsing that translates natural language queries to SPARQL is of great importance for Knowledge Graph Question Answering (KGQA) systems. Although pre-trained language mode…
Mirror-Consistency: Harnessing Inconsistency in Majority Voting
Siyuan Huang, Zhiyuan Ma, Jintao Du +3
Self-Consistency, a widely-used decoding strategy, significantly boosts the reasoning capabilities of Large Language Models (LLMs). However, it depends on the plurality voting rule…
Cluster-wise Graph Transformer with Dual-granularity Kernelized Attention
Siyuan Huang, Yunchong Song, Jiayue Zhou +1
In the realm of graph learning, there is a category of methods that conceptualize graphs as hierarchical structures, utilizing node clustering to capture broader structural informa…
Graph Parsing Networks
Yunchong Song, Siyuan Huang, Xinbing Wang +2
Graph pooling compresses graph information into a compact representation. State-of-the-art graph pooling methods follow a hierarchical approach, which reduces the graph size step-b…
SH2: Self-Highlighted Hesitation Helps You Decode More Truthfully
Jushi Kai, Tianhang Zhang, Hai Hu +1
Large language models (LLMs) demonstrate great performance in text generation. However, LLMs are still suffering from hallucinations. In this work, we propose an inference-time met…
GeoGalactica: A Scientific Large Language Model in Geoscience
Zhouhan Lin, Cheng Deng, Le Zhou +18
Large language models (LLMs) have achieved huge success for their general knowledge and ability to solve a wide spectrum of tasks in natural language processing (NLP). Due to their…