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Hao Zhang

12 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • sole author1
  • first author1
  • middle author5
  • last author3

Across the 10 of 12 papers where every author was matched, so the position is known.

fields
  • cs.CL4
  • cs.CV2
  • cs.RO2
  • cs.LG1
  • cs.SI1
  • eess.SP1
ORCID 0000-0002-2058-7123
same name
  • Hao Zhang — 23 papers
  • Hao Zhang — 17 papers
  • Hao Zhang — 12 papers
  • Hao Zhang — 12 papers, h 4
  • Hao Zhang — 11 papers, h 38
  • Hao Zhang — 11 papers, h 30

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20202025
most citedSimultaneous View and Feature Selection for Collaborative Multi-Robot Perception

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

collaborators
Showing cs.CLShow all

4 papers · 1 filter

cs.CL2024

Multi-view Content-aware Indexing for Long Document Retrieval

Kuicai Dong, Derrick Goh Xin Deik, Yi Quan Lee +4

Long document question answering (DocQA) aims to answer questions from long documents over 10k words. They usually contain content structures such as sections, sub-sections, and pa…

cs.CL2023★ 1 cited

SpanRE: Entities and Overlapping Relations Extraction Based on Spans and Entity Attention

Hao Zhang

Extracting entities and relations is an essential task of information extraction. Triplets extracted from a sentence might overlap with each other. Previous methods either did not…

cs.CL2022

FF2: A Feature Fusion Two-Stream Framework for Punctuation Restoration

Yangjun Wu, Kebin Fang, Yao Zhao +3

To accomplish punctuation restoration, most existing methods focus on introducing extra information (e.g., part-of-speech) or addressing the class imbalance problem. Recently, larg…

cs.CL2022★ 2 cited

UKP-SQuARE v2: Explainability and Adversarial Attacks for Trustworthy QA

Rachneet Sachdeva, Haritz Puerto, Tim Baumgärtner +6

Question Answering (QA) systems are increasingly deployed in applications where they support real-world decisions. However, state-of-the-art models rely on deep neural networks, wh…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.