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ImCoref-CeS: An Improved Lightweight Pipeline for Coreference Resolution with LLM-based Checker-Splitter Refinement
Kangyang Luo, Yuzhuo Bai, Shuzheng Si +9
Coreference Resolution (CR) is a critical task in Natural Language Processing (NLP). Current research faces a key dilemma: whether to further explore the potential of supervised ne…
On LLM-Based Scientific Inductive Reasoning Beyond Equations
Brian S. Lin, Jiaxin Yuan, Zihan Zhou +8
As large language models (LLMs) increasingly exhibit human-like capabilities, a fundamental question emerges: How can we enable LLMs to learn the underlying patterns from limited e…
MiniCPM4: Ultra-Efficient LLMs on End Devices
MiniCPM Team, Chaojun Xiao, Yuxuan Li +80
This paper introduces MiniCPM4, a highly efficient large language model (LLM) designed explicitly for end-side devices. We achieve this efficiency through systematic innovation in…
GLTW: Joint Improved Graph Transformer and LLM via Three-Word Language for Knowledge Graph Completion
Kangyang Luo, Yuzhuo Bai, Cheng Gao +11
Knowledge Graph Completion (KGC), which aims to infer missing or incomplete facts, is a crucial task for KGs. However, integrating the vital structural information of KGs into Larg…
From the New World of Word Embeddings: A Comparative Study of Small-World Lexico-Semantic Networks in LLMs
Zhu Liu, Ying Liu, KangYang Luo +2
Lexico-semantic networks represent words as nodes and their semantic relatedness as edges. While such networks are traditionally constructed using embeddings from encoder-based mod…
A Top-down Graph-based Tool for Modeling Classical Semantic Maps: A Crosslinguistic Case Study of Supplementary Adverbs
Zhu Liu, Cunliang Kong, Ying Liu +1
Semantic map models (SMMs) construct a network-like conceptual space from cross-linguistic instances or forms, based on the connectivity hypothesis. This approach has been widely u…
Fantastic Semantics and Where to Find Them: Investigating Which Layers of Generative LLMs Reflect Lexical Semantics
Zhu Liu, Cunliang Kong, Ying Liu +1
Large language models have achieved remarkable success in general language understanding tasks. However, as a family of generative methods with the objective of next token predicti…