Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-17T21:58:23.177065Z
Paper Citation Record · LEDGER
3DAlign-DAER: Dynamic Attention Policy and Efficient Retrieval Strategy for Fine-grained 3D-Text Alignment at Scale
As of 5 August 2026, this Paper Citation Record lists 3 of 3 outbound references and 0 inbound Pith citation observations for arXiv:2511.13211.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
3 of 3 outbound references displayed
- verified exact3
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation c72341cf-b0f1-4cae-9051-e59d17bdf181 · outbound
This paper cites Y^2Seq2Seq: Cross-Modal Representation Learning for 3D Shape and Text by Joint Reconstruction and Prediction of View and Word Sequences.
3DAlign-DAER: Dynamic Attention Policy and Efficient Retrieval Strategy for Fine-grained 3D-Text Alignment at Scale Y^2Seq2Seq: Cross-Modal Representation Learning for 3D Shape and Text by Joint Reconstruction and Prediction of View and Word Sequences
Reference 1
- Resolution
- verified exact
- local_arxiv, observed 2026-05-17T22:00:21.190730Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation c93091a3-c489-47d9-8aa8-952cfb276c74 · outbound
This paper cites CLIP goes 3D: Leveraging Prompt Tuning for Language Grounded 3D Recognition.
3DAlign-DAER: Dynamic Attention Policy and Efficient Retrieval Strategy for Fine-grained 3D-Text Alignment at Scale CLIP goes 3D: Leveraging Prompt Tuning for Language Grounded 3D Recognition
Reference 2
- Resolution
- verified exact
- arxiv_id, observed 2026-05-17T22:00:21.181536Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation adcb1a6e-91cf-4a18-82eb-546fdc3ff1bf · outbound
This paper cites RoBERTa: A Robustly Optimized BERT Pretraining Approach.
3DAlign-DAER: Dynamic Attention Policy and Efficient Retrieval Strategy for Fine-grained 3D-Text Alignment at Scale RoBERTa: A Robustly Optimized BERT Pretraining Approach
Reference 3
- Resolution
- verified exact
- local_arxiv, observed 2026-05-17T22:00:21.185985Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Pith citing papers
No inbound Pith citation observations are available.