Researcher Evidence Record
Shaozhe Hao
This bounded record lists 13 Pith paper rows and 0 imported work rows attributed to this corpus identity. The enumerated, non-disputed paper rows include cs.CV work dated 2022 to 2025. The record describes sources and coverage; it makes no judgment about the person.
Compiled coverage vector
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.
-
2025 Pith paper
NTIRE 2025 Challenge on UGC Video Enhancement: Methods and Results
paper paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Shaozhe Hao
- Author position
- 12
- Identity state
- provisional
- Source confidence
- 0.7
- Review coverage
- Measured: a current Pith review exists.
- Citation counts
- No source count is attached to this work row.
-
2025 Pith paper
Se\~norita-2M: A High-Quality Instruction-based Dataset for General Video Editing by Video Specialists
paper citation record paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Shaozhe Hao
- Author position
- 5
- Identity state
- provisional
- Source confidence
- 0.7
- Review coverage
- Measured: a current Pith review exists.
- Citation counts
-
- 12 pith inbound references from cited_work_pith_inbound_counts
-
2024 Pith paper
Elucidating the design space of language models for image generation
paper citation record paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Shaozhe Hao
- Author position
- 2
- Identity state
- provisional
- Source confidence
- 0.7
- Review coverage
- Measured: no current Pith review exists.
- Citation counts
-
- 1 pith inbound references from cited_work_pith_inbound_counts
-
2024 Pith paper
BiGR: Harnessing Binary Latent Codes for Image Generation and Improved Visual Representation Capabilities
paper citation record paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Shaozhe Hao
- Author position
- 1
- Identity state
- provisional
- Source confidence
- 0.7
- Review coverage
- Measured: no current Pith review exists.
- Citation counts
-
- 1 pith inbound references from cited_work_pith_inbound_counts
-
2024 Pith paper
CusConcept: Customized Visual Concept Decomposition with Diffusion Models
paper citation record paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Shaozhe Hao
- Author position
- 2
- Identity state
- provisional
- Source confidence
- 0.7
- Review coverage
- Measured: no current Pith review exists.
- Citation counts
-
- 1 pith inbound references from cited_work_pith_inbound_counts
-
2024 Pith paper
ArtiFade: Learning to Generate High-quality Subject from Blemished Images
paper paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Shaozhe Hao
- Author position
- 2
- 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.
-
2024 Pith paper
ConceptExpress: Harnessing Diffusion Models for Single-image Unsupervised Concept Extraction
paper paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Shaozhe Hao
- Author position
- 1
- 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.
-
2024 Pith paper
Bridging Different Language Models and Generative Vision Models for Text-to-Image Generation
paper citation record paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Shaozhe Hao
- Author position
- 2
- Identity state
- provisional
- Source confidence
- 0.7
- Review coverage
- Measured: no current Pith review exists.
- Citation counts
-
- 1 pith inbound references from cited_work_pith_inbound_counts
-
2023 Pith paper
ViCo: Plug-and-play Visual Condition for Personalized Text-to-image Generation
paper citation record paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Shaozhe Hao
- Author position
- 1
- Identity state
- provisional
- Source confidence
- 0.7
- Review coverage
- Measured: no current Pith review exists.
- Citation counts
-
- 3 pith inbound references from cited_work_pith_inbound_counts
-
2023 Pith paper
Uni-ControlNet: All-in-One Control to Text-to-Image Diffusion Models
paper citation record paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Shaozhe Hao
- Author position
- 5
- Identity state
- provisional
- Source confidence
- 0.7
- Review coverage
- Measured: no current Pith review exists.
- Citation counts
-
- 2 pith inbound references from cited_work_pith_inbound_counts
-
2023 Pith paper
CiPR: An Efficient Framework with Cross-instance Positive Relations for Generalized Category Discovery
paper citation record paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Shaozhe Hao
- Author position
- 1
- Identity state
- provisional
- Source confidence
- 0.7
- Review coverage
- Measured: no current Pith review exists.
- Citation counts
-
- 1 pith inbound references from cited_work_pith_inbound_counts
-
2023 Pith paper
Learning Attention as Disentangler for Compositional Zero-shot Learning
paper paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Shaozhe Hao
- Author position
- 1
- 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.
-
2022 Pith paper
A Unified Framework for Masked and Mask-Free Face Recognition via Feature Rectification
paper paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Shaozhe Hao
- Author position
- 1
- 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.
| Lane | State | Observed | Boundary and source |
|---|---|---|---|
| identity | Measured | 2 | Canonical identity row plus public typed identifiers. source=authors, author_identifiers |
| papers | Measured | 13 of 13 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 | 2 of 13 bounded rows | Coverage count only. No review outcome is projected onto the person. source=current_verdicts |
| citations | Measured | 8 of 13 bounded rows | Counts remain itemized by work and source. source=cited_works |
| coauthors | Measured | 50 of 13 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
Shaozhe Hao
Enumerated research scope
- cs.CV13 rows
- 20221 rows
- 20234 rows
- 20246 rows
- 20252 rows
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.
Self-published account annex
Linked Pith account
Unavailable No public Pith account is linked to this corpus identity.
The account lane is self-published. Linking proves account control only and changes no corpus fact.