Paper year
2025
Detect emerging, bridge-candidate, and undercited papers inside a curated audio-ML corpus, then expose the signals behind every recommendation.
Paper dossier
Review source metadata, abstract, authors, topics, and local similarity context before moving into explanation and ranking views.
Paper year
2025
Citations
0
Authors
4
Topic labels
2
Source readout
Journal of the Audio Engineering Society
jaes
Core corpus
Not available yet
Ranking readout
This block uses the same resolved ranking run as Recommended. Ranks here are materialized paper_scores ranks; live Emerging may be reordered by the bounded ML scorer. Family rank is global within each family, but rank is only shown when this paper lands inside the surfaced top 50.
Families present
3
Top 50
3
Run label
shadow-generalization-product-candidate-ranking-v1
Snapshot
source-snapshot-shadow-generalization-v1-20260521
Scope: family global | run rank-83787b91ef
Emerging
In top 50 at rank 23
Emerging: embedding slice fit vs included-corpus centroid (title+abstract), plus citation velocity and topic growth; not universal relevance. Bridge signal not used here.
Signals: semantic=0.8078, citation_velocity=0.0000, topic_growth=1.0000, diversity_penalty=0.0000
Embedding slice fit (corpus centroid): high; used in final ranking (contribution to score: 0.1616)
Recent attention: low; used in final ranking (contribution to score: 0.0000)
Topic momentum: high; used in final ranking (contribution to score: 0.3000)
Cross-cluster signal: not computed for this run
Similarity penalty: reduces score when non-zero (contribution to score: 0.0000)
Bridge
In top 50 at rank 16
Multi-topic paper in active topics; no cluster_version on this run so bridge_score was not computed.
Signals: citation_velocity=0.0000, topic_growth=1.0000, diversity_penalty=0.3333
Semantic match: not computed for this run
Recent attention: low; used in final ranking (contribution to score: 0.0000)
Topic momentum: high; used in final ranking (contribution to score: 0.6500)
Cross-cluster signal: not computed for this run
Topic breadth penalty: reduces score when non-zero (contribution to score: -0.0667)
Under-cited
In top 50 at rank 1
Low-cite candidate pool (see docs/candidate-pool-low-cite.md v0): core corpus, recency floor, citation ceiling, title+abstract gate; popularity penalty among pool members only. Semantic and bridge not yet modeled.
Signals: citation_velocity=0.0000, topic_growth=1.0000, diversity_penalty=0.0000
Semantic match: not computed for this run
Recent attention: low; used in final ranking (contribution to score: 0.0000)
Topic momentum: high; used in final ranking (contribution to score: 0.7000)
Cross-cluster signal: not computed for this run
Pool popularity penalty: reduces score when non-zero (contribution to score: 0.0000)
Recent years have witnessed an increasing interest from the academic and industrial research community toward software for dynamic auralization and six-degrees-of-freedom (6DoF) navigation of immersive audio environments. Some existing tools rely on the convolution of source sounds with Ambisonics impulse responses (IRs) recorded in real spaces. However, despite advancements in computing power of modern central processing units, convolution remains a demanding computation to perform, especially with many channels and in real time. Moreover, efficient computation schemes often used in single-IR matrix tools have not made their way into open-source 6DoF spatial audio plugins. This paper presents MCFX-6DoFconv, an open-source 6DoF convolution plugin combining the efficient convolution engine of the MCFX-Convolver plugin with the 6DoF navigation features of SPARTA 6DoFconv, along with functional and interface improvements. Compared with the original SPARTA 6DoFconv, the proposed plugin yields a considerable increase in computing efficiency throughout a wide range of IR lengths, number of channels, and audio buffer sizes, up to a 3.7-fold improvement. This enables real-time auralization with longer IRs and multiple source rendering with more plugin instances. Moreover, the proposed plugin enables instant listener-position updates, eliminating delays up to two buffer sizes and removing the audio latency caused by internal buffering.
Neighborhood labels
Topic labels are imported metadata and can be noisy; use them as coarse navigation hints, not authoritative classifications.
Advanced Vision and ImagingImage and Video Stabilization
Neighbor surface
Similar papers use a separately configured neighbor embedding; it may differ from the embedding version used by the current ranked run.
No embedding-backed neighbors available for this paper/version yet.
Next handoff
01
Use Recommended to see whether this paper behaves like an emerging or undercited signal in the current ranked feed, or how it appears on the bridge preview / diagnostics view.
02
Use Trends to understand whether its attached labels are heating up or cooling down inside the curated corpus.
03
Use Evaluation to compare the dossier readout against citation and recency baselines for the same resolved family run.