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Researcher Evidence Record

Yaou Liu

This bounded record lists 8 Pith paper rows and 0 imported work rows attributed to this corpus identity. The enumerated, non-disputed paper rows include cs.CV, eess.IV, q-bio.QM work dated 2018 to 2024. The record describes sources and coverage; it makes no judgment about the person.

Compiled coverage vector

Measured lane counts only. Not a trust score or person verdict.

Enumerated paper scope: 3 fields (cs.CV, eess.IV, q-bio.QM) · 2018-2024 sources: authors, author_identifiers · paper_authors · author_works · current_verdicts · cited_works

A sourced case file for attributed work. It is neither a profile score nor a verdict about this researcher.

Attributed works

A bounded ledger from the Pith paper and imported-work queries. Counts and source confidence stay with each work.

  1. 2024 Pith paper

    A Foundation Model for Brain Lesion Segmentation with Mixture of Modality Experts

    eess.IV provisional measured, no current review

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Yaou Liu
    Author position
    8
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    No source count is attached to this work row.
  2. 2024 Pith paper

    Pathology-genomic fusion via biologically informed cross-modality graph learning for survival analysis

    q-bio.QM provisional measured, no current review

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Yaou Liu
    Author position
    4
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    No source count is attached to this work row.
  3. 2023 Pith paper

    Unsupervised Brain Tumor Segmentation with Image-based Prompts

    cs.CV provisional measured, no current review

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Yaou Liu
    Author position
    5
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    No source count is attached to this work row.
  4. 2023 Pith paper

    One-Shot Segmentation of Novel White Matter Tracts via Extensive Data Augmentation

    cs.CV provisional measured, no current review

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Yaou Liu
    Author position
    4
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    No source count is attached to this work row.
  5. 2023 Pith paper

    Positive-unlabeled learning for binary and multi-class cell detection in histopathology images with incomplete annotations

    cs.CV provisional measured, no current review

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Yaou Liu
    Author position
    3
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    No source count is attached to this work row.
  6. 2021 Pith paper

    Benefits of Linear Conditioning with Metadata for Image Segmentation

    cs.CV provisional measured, no current review

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Yaou Liu
    Author position
    4
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    No source count is attached to this work row.
  7. 2020 Pith paper

    Multiclass Spinal Cord Tumor Segmentation on MRI with Deep Learning

    eess.IV provisional measured, no current review

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Yaou Liu
    Author position
    7
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    No source count is attached to this work row.
  8. 2018 Pith paper

    Automatic segmentation of the spinal cord and intramedullary multiple sclerosis lesions with convolutional neural networks

    cs.CV provisional measured, no current review

    Sources and evidence
    Authorship source
    arxiv_oai
    Printed name
    Yaou Liu
    Author position
    9
    Identity state
    provisional
    Source confidence
    0.7
    Review coverage
    Measured: no current Pith review exists.
    Citation counts
    No source count is attached to this work row.

Evidence apparatus

The machinery behind this record. Every lane states whether Pith measured it, did not query it, could not reach it, or withheld it.

LaneStateObservedBoundary and source
identity Measured 2 Canonical identity row plus public typed identifiers.
source=authors, author_identifiers
papers Measured 8 of 8 bounded rows Rows attributed to this author UUID in the Pith corpus.
source=paper_authors
works Measured zero 0 of 0 bounded rows Imported works not duplicated by the paper ledger.
source=author_works
reviews Measured zero 0 of 8 bounded rows Coverage count only. No review outcome is projected onto the person.
source=current_verdicts
citations Measured zero 0 of 8 bounded rows Counts remain itemized by work and source.
source=cited_works
coauthors Measured 50 of 8 bounded rows Shared-work edges from admitted paper rows.
source=paper_authors
account Unavailable No public count of 1 bounded rows Account metadata is separate from corpus evidence.
source=users.author_id
Public identity sources
  • name variant
    Yaou Liu
    backfill
    confidence 0.6
Enumerated research scope

Fields and dates come only from enumerated, non-disputed Pith paper rows. They do not claim career completeness.

  • cs.CV5 rows
  • eess.IV2 rows
  • q-bio.QM1 rows
  • 20181 rows
  • 20201 rows
  • 20211 rows
  • 20233 rows
  • 20242 rows
Shared-work index
Record scope

The work queries are bounded. Missing rows may mean measured zero, an unavailable source, a query that did not run, or private data that Pith withheld. The lane table keeps those cases separate.

Paper findings remain attached to papers. They do not become findings about this researcher.