94 citations · 206 across the 53 of their papers we have counts for
14 papers · 1 filter
RADAR: Reasoning as Discrimination with Aligned Representations for LLM-based Knowledge Graph Reasoning
Bo Xue, Yuan Jin, Luoyi Fu +2
Knowledge graph reasoning (KGR) infers missing facts, with recent advances increasingly harnessing the semantic priors and reasoning abilities of Large Language Models (LLMs). Howe…
<SOG_k>: One LLM Token for Explicit Graph Structural Understanding
Jingyao Wu, Bin Lu, Zijun Di +5
Large language models show great potential in unstructured data understanding, but still face significant challenges with graphs due to their structural hallucination. Existing app…
Structured In-context Environment Scaling for Large Language Model Reasoning
Peng Yu, Zeyuan Zhao, Shao Zhang +3
Large language models (LLMs) have achieved significant advancements in reasoning capabilities through reinforcement learning (RL) via environmental exploration. As the intrinsic pr…
Good Idea or Not, Representation of LLM Could Tell
Yi Xu, Bo Xue, Shuqian Sheng +6
In the ever-expanding landscape of academic research, the proliferation of ideas presents a significant challenge for researchers: discerning valuable ideas from the less impactful…
AceParse: A Comprehensive Dataset with Diverse Structured Texts for Academic Literature Parsing
Huawei Ji, Cheng Deng, Bo Xue +6
With the development of data-centric AI, the focus has shifted from model-driven approaches to improving data quality. Academic literature, as one of the crucial types, is predomin…
AutoFAIR : Automatic Data FAIRification via Machine Reading
Tingyan Ma, Wei Liu, Bin Lu +4
The explosive growth of data fuels data-driven research, facilitating progress across diverse domains. The FAIR principles emerge as a guiding standard, aiming to enhance the finda…