activity
20182024
most citedMatrix Product Operators for Sequence to Sequence Learning

49 citations · 72 across the 12 of their papers we have counts for

collaborators
Showing cs.CLShow all

11 papers · 1 filter

cs.CL2024

ThinK: Thinner Key Cache by Query-Driven Pruning

Yuhui Xu, Zhanming Jie, Hanze Dong +6

Large Language Models (LLMs) have revolutionized the field of natural language processing, achieving unprecedented performance across a variety of applications. However, their incr…

cs.CL2023★ 2 cited

Design of Chain-of-Thought in Math Problem Solving

Zhanming Jie, Trung Quoc Luong, Xinbo Zhang +2

Chain-of-Thought (CoT) plays a crucial role in reasoning for math problem solving. We conduct a comprehensive examination of methods for designing CoT, comparing conventional natur…

cs.CL2023★ 1 cited

Leveraging Training Data in Few-Shot Prompting for Numerical Reasoning

Zhanming Jie, Wei Lu

Chain-of-thought (CoT) prompting with large language models has proven effective in numerous natural language processing tasks, but designing prompts that generalize well to divers…

cs.CL2023★ 1 cited

Sequence-to-Sequence Pre-training with Unified Modality Masking for Visual Document Understanding

Shuwei Feng, Tianyang Zhan, Zhanming Jie +2

This paper presents GenDoc, a general sequence-to-sequence document understanding model pre-trained with unified masking across three modalities: text, image, and layout. The propo…

cs.CL2022★ 1 cited

Learning to Reason Deductively: Math Word Problem Solving as Complex Relation Extraction

Zhanming Jie, Jierui Li, Wei Lu

Solving math word problems requires deductive reasoning over the quantities in the text. Various recent research efforts mostly relied on sequence-to-sequence or sequence-to-tree m…

cs.CL2021

To be Closer: Learning to Link up Aspects with Opinions

Yuxiang Zhou, Lejian Liao, Yang Gao +2

Dependency parse trees are helpful for discovering the opinion words in aspect-based sentiment analysis (ABSA). However, the trees obtained from off-the-shelf dependency parsers ar…

cs.CL2021★ 2 cited

Better Feature Integration for Named Entity Recognition

Lu Xu, Zhanming Jie, Wei Lu +1

It has been shown that named entity recognition (NER) could benefit from incorporating the long-distance structured information captured by dependency trees. We believe this is bec…

cs.CL2020★ 2 cited

ENT-DESC: Entity Description Generation by Exploring Knowledge Graph

Liying Cheng, Dekun Wu, Lidong Bing +4

Previous works on knowledge-to-text generation take as input a few RDF triples or key-value pairs conveying the knowledge of some entities to generate a natural language descriptio…

cs.CL2019★ 6 cited

Dependency-Guided LSTM-CRF for Named Entity Recognition

Zhanming Jie, Wei Lu

Dependency tree structures capture long-distance and syntactic relationships between words in a sentence. The syntactic relations (e.g., nominal subject, object) can potentially in…

cs.CL2018★ 6 cited

Efficient Dependency-Guided Named Entity Recognition

Zhanming Jie, Aldrian Obaja Muis, Wei Lu

Named entity recognition (NER), which focuses on the extraction of semantically meaningful named entities and their semantic classes from text, serves as an indispensable component…

cs.CL2018★ 2 cited

Dependency-based Hybrid Trees for Semantic Parsing

Zhanming Jie, Wei Lu

We propose a novel dependency-based hybrid tree model for semantic parsing, which converts natural language utterance into machine interpretable meaning representations. Unlike pre…