Researcher Evidence Record
Lixiang Ru
This bounded record lists 17 Pith paper rows and 0 imported work rows attributed to this corpus identity. The enumerated, non-disputed paper rows include cs.CV, cs.AI work dated 2018 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
CasP: Improving Semi-Dense Feature Matching Pipeline Leveraging Cascaded Correspondence Priors for Guidance
paper paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Lixiang Ru
- Author position
- 8
- 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
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing
paper citation record paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Lixiang Ru
- Author position
- 2
- Identity state
- provisional
- Source confidence
- 0.7
- Review coverage
- Measured: a current Pith review exists.
- Citation counts
-
- 2 pith inbound references from cited_work_pith_inbound_counts
-
2025 Pith paper
M2-Reasoning: Empowering MLLMs with Unified General and Spatial Reasoning
paper citation record paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Lixiang Ru
- Author position
- 6
- Identity state
- provisional
- Source confidence
- 0.7
- Review coverage
- Measured: a current Pith review exists.
- Citation counts
-
- 4 pith inbound references from cited_work_pith_inbound_counts
-
2025 Pith paper
Ming-Omni: A Unified Multimodal Model for Perception and Generation
paper citation record paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Lixiang Ru
- Author position
- 23
- Identity state
- provisional
- Source confidence
- 0.7
- Review coverage
- Measured: a current Pith review exists.
- Citation counts
-
- 0 external cited by from arxiv_reference
- 24 pith inbound references from cited_work_pith_inbound_counts
-
2025 Pith paper
Ming-Lite-Uni: Advancements in Unified Architecture for Natural Multimodal Interaction
paper citation record paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Lixiang Ru
- Author position
- 11
- Identity state
- provisional
- Source confidence
- 0.7
- Review coverage
- Measured: a current Pith review exists.
- Citation counts
-
- 2 pith inbound references from cited_work_pith_inbound_counts
-
2025 Pith paper
Plug-and-Play DISep: Separating Dense Instances for Scene-to-Pixel Weakly-Supervised Change Detection in High-Resolution Remote Sensing Images
paper paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Lixiang Ru
- Author position
- 3
- 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.
-
2024 Pith paper
Cross-View Geo-Localization with Street-View and VHR Satellite Imagery in Decentrality Settings
paper citation record paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Lixiang Ru
- Author position
- 10
- Identity state
- provisional
- Source confidence
- 0.7
- Review coverage
- Measured: a current Pith review exists.
- Citation counts
-
- 1 pith inbound references from cited_work_pith_inbound_counts
-
2024 Pith paper
HomoMatcher: Dense Feature Matching Results with Semi-Dense Efficiency by Homography Estimation
paper citation record paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Lixiang Ru
- Author position
- 5
- 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
POA: Pre-training Once for Models of All Sizes
paper paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Lixiang Ru
- 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.
-
2023 Pith paper
SkySense: A Multi-Modal Remote Sensing Foundation Model Towards Universal Interpretation for Earth Observation Imagery
paper citation record paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Lixiang Ru
- Author position
- 6
- Identity state
- provisional
- Source confidence
- 0.7
- Review coverage
- Measured: no current Pith review exists.
- Citation counts
-
- 6 external cited by from arxiv_reference
- 1 pith inbound references from cited_work_pith_inbound_counts
-
2023 Pith paper
Exploring Effective Priors and Efficient Models for Weakly-Supervised Change Detection
paper citation record paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Lixiang Ru
- 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
Token Contrast for Weakly-Supervised Semantic Segmentation
paper citation record paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Lixiang Ru
- 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
-
2022 Pith paper
Learning Affinity from Attention: End-to-End Weakly-Supervised Semantic Segmentation with Transformers
paper citation record paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Lixiang Ru
- 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
-
2022 Pith paper
Weakly-Supervised Semantic Segmentation with Visual Words Learning and Hybrid Pooling
paper paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Lixiang Ru
- 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.
-
2020 Pith paper
An Investigation of Traffic Density Changes inside Wuhan during the COVID-19 Epidemic with GF-2 Time-Series Images
paper paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Lixiang Ru
- 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.
-
2020 Pith paper
Multi-Temporal Scene Classification and Scene Change Detection with Correlation based Fusion
paper paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Lixiang Ru
- 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.
-
2018 Pith paper
Unsupervised Deep Slow Feature Analysis for Change Detection in Multi-Temporal Remote Sensing Images
paper paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Lixiang Ru
- 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.
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 | 17 of 17 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 | 7 of 17 bounded rows | Coverage count only. No review outcome is projected onto the person. source=current_verdicts |
| citations | Measured | 10 of 17 bounded rows | Counts remain itemized by work and source. source=cited_works |
| coauthors | Measured | 50 of 17 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
Lixiang Ru
Enumerated research scope
- cs.CV15 rows
- cs.AI2 rows
- 20181 rows
- 20202 rows
- 20222 rows
- 20233 rows
- 20243 rows
- 20256 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.