9 citations · 21 across the 9 of their papers we have counts for
9 papers
Negative Matters: Multi-Granularity Hard-Negative Synthesis and Anchor-Token-Aware Pooling for Enhanced Text Embeddings
Tengyu Pan, Zhichao Duan, Zhenyu Li +4
Text embedding models are essential for various natural language processing tasks, enabling the effective encoding of semantic information into dense vector representations. These…
COMM:Concentrated Margin Maximization for Robust Document-Level Relation Extraction
Zhichao Duan, Tengyu Pan, Zhenyu Li +2
Document-level relation extraction (DocRE) is the process of identifying and extracting relations between entities that span multiple sentences within a document. Due to its realis…
TROI: Cross-Subject Pretraining with Sparse Voxel Selection for Enhanced fMRI Visual Decoding
Ziyu Wang, Tengyu Pan, Zhenyu Li +3
fMRI (functional Magnetic Resonance Imaging) visual decoding involves decoding the original image from brain signals elicited by visual stimuli. This often relies on manually label…
FlexKBQA: A Flexible LLM-Powered Framework for Few-Shot Knowledge Base Question Answering
Zhenyu Li, Sunqi Fan, Yu Gu +5
Knowledge base question answering (KBQA) is a critical yet challenging task due to the vast number of entities within knowledge bases and the diversity of natural language question…
Can LLMs like GPT-4 outperform traditional AI tools in dementia diagnosis? Maybe, but not today
Zhuo Wang, Rongzhen Li, Bowen Dong +8
Recent investigations show that large language models (LLMs), specifically GPT-4, not only have remarkable capabilities in common Natural Language Processing (NLP) tasks but also e…
Bridging the Language Gap: Knowledge Injected Multilingual Question Answering
Zhichao Duan, Xiuxing Li, Zhengyan Zhang +3
Question Answering (QA) is the task of automatically answering questions posed by humans in natural languages. There are different settings to answer a question, such as abstractiv…
Optimization Techniques for Unsupervised Complex Table Reasoning via Self-Training Framework
Zhenyu Li, Xiuxing Li, Sunqi Fan +1
Structured tabular data is a fundamental data type in numerous fields, and the capacity to reason over tables is crucial for answering questions and validating hypotheses. However,…
Not Just Plain Text! Fuel Document-Level Relation Extraction with Explicit Syntax Refinement and Subsentence Modeling
Zhichao Duan, Xiuxing Li, Zhenyu Li +2
Document-level relation extraction (DocRE) aims to identify semantic labels among entities within a single document. One major challenge of DocRE is to dig decisive details regardi…
Effective Few-Shot Named Entity Linking by Meta-Learning
Xiuxing Li, Zhenyu Li, Zhengyan Zhang +5
Entity linking aims to link ambiguous mentions to their corresponding entities in a knowledge base, which is significant and fundamental for various downstream applications, e.g.,…