9 citations · 11 across the 6 of their papers we have counts for
6 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…
FocusLLM: Precise Understanding of Long Context by Dynamic Condensing
Zhenyu Li, Yike Zhang, Tengyu Pan +6
Empowering LLMs with the ability to precisely understand long contexts is crucial for many downstream applications. However, handling long contexts with conventional transformer ar…
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…
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…
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…