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Paper Citation Record · LEDGER

Steering dense music retrieval with open-vocabulary concept discovery

As of 16 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 1 inbound Pith citation observation for arXiv:2608.08757.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2608.08757 v1

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T04:29:55.471193Z

measured 46 of 46 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T04:29:54.869853Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-14T04:29:56.530380Z

Reference resolution

45 of 45 outbound references displayed

  • verified exact2
  • verified fuzzy30
  • unresolved12
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 43e98c51-84ce-445b-90a6-2187d66a315a · outbound

This paper cites Steering dense music retrieval with open-vocabulary concept discovery.

Steering dense music retrieval with open-vocabulary concept discovery Steering dense music retrieval with open-vocabulary concept discovery

Reference 1

Resolution
metadata mismatch
local_arxiv, observed 2026-08-14T04:29:56.545267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 3d82224f-d404-4d9d-b143-619ab3218138 · outbound

This paper cites an unresolved cited work.

Steering dense music retrieval with open-vocabulary concept discovery Unresolved cited work

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 2d4fc4f5-3b0e-49bf-8ed8-4bee2ceee47b · outbound

This paper cites Audio clips are encoded with the audio towers fA of CLAP [28] and MuQ [33]; from each 10-second frame we extract an embeddingz a ∈R 512.

Steering dense music retrieval with open-vocabulary concept discovery Audio clips are encoded with the audio towers fA of CLAP [28] and MuQ [33]; from each 10-second frame we extract an embeddingz a ∈R 512

Reference 3

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 0374edb9-3e0b-41d1-bf85-6e6ae0bba63f · outbound

This paper cites piano”.Starting from an audio embeddingz, we navigate on the hypersphere by amplifying the concept “piano.

Steering dense music retrieval with open-vocabulary concept discovery piano”.Starting from an audio embeddingz, we navigate on the hypersphere by amplifying the concept “piano

Reference 4

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verified fuzzy
raw_fallback, observed 2026-08-14T04:29:58.093485Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 0c330b2d-9fdf-4bb1-8a04-0ea64771a433 · outbound

This paper cites I want similar songs without the guitar.

Steering dense music retrieval with open-vocabulary concept discovery I want similar songs without the guitar

Reference 5

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T04:29:54.905285Z digest=sha256:de335f4c0f3bbda03244c1ec34665f0c6d8e7daf243be4841b7b41783d75802c

Observation 6b419c32-56fb-4de1-ba56-c689f7de66f9 · outbound

This paper cites an unresolved cited work.

Steering dense music retrieval with open-vocabulary concept discovery Unresolved cited work

Reference 6

Resolution
unresolved
raw_fallback, observed 2026-08-14T04:29:58.056825Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation b8d86907-d1ab-4633-9679-1d2b6eee2074 · outbound

This paper cites an unresolved cited work.

Steering dense music retrieval with open-vocabulary concept discovery Unresolved cited work

Reference 7

Resolution
unresolved
raw_fallback, observed 2026-08-14T04:29:58.019397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 4ea433af-ca36-4b7c-ab77-a98d9f88076c · outbound

This paper cites AI assistance was also used sparingly in writing this paper to tighten phrasing, reword for conci- sion, and smooth out mathematical notation consistency.

Steering dense music retrieval with open-vocabulary concept discovery AI assistance was also used sparingly in writing this paper to tighten phrasing, reword for conci- sion, and smooth out mathematical notation consistency

Reference 8

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verified fuzzy
raw_fallback, observed 2026-08-14T04:29:57.995059Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T04:29:54.963187Z digest=sha256:f924c3815049c23dde202aabad5d6aece97fea754459247ec19ee6ceffe4e75b

Observation fb6daf74-d417-4f72-b507-475b6ae0b98b · outbound

This paper cites Jumping Ahead: Improving Reconstruction Fidelity with JumpReLU Sparse Autoencoders.

Steering dense music retrieval with open-vocabulary concept discovery Jumping Ahead: Improving Reconstruction Fidelity with JumpReLU Sparse Autoencoders

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-14T04:29:54.968718Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T04:29:54.968718Z digest=sha256:4376bbcef872fe1fb4566d91fc5d9a3a8e12d54472bb98ac1e847bc424cd7ad8

Observation ede3c7ac-c22b-4506-a03a-9a08f92965df · outbound

This paper cites Batchtopk sparse autoencoders,.

Steering dense music retrieval with open-vocabulary concept discovery Batchtopk sparse autoencoders,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:29:57.973879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T04:29:54.973585Z digest=sha256:77915015dafde41d86c40d22acd9a982210d6eb5e23871175896b88746a94c4c

Observation 91e0ef97-772f-48d1-b173-6993f62e3d3a · outbound

This paper cites Learning multi-level features with ma- tryoshka sparse autoencoders,.

Steering dense music retrieval with open-vocabulary concept discovery Learning multi-level features with ma- tryoshka sparse autoencoders,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:29:57.924437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T04:29:54.978773Z digest=sha256:0054b8de8912128308d1da1c4c5cc43d7b3361bab9b125fa7d626558eba71f7c

Observation 2837e108-d8e9-4387-a783-f7aa8a254f32 · outbound

This paper cites From flat to hierarchical: Extracting sparse representations with matching pursuit,.

Steering dense music retrieval with open-vocabulary concept discovery From flat to hierarchical: Extracting sparse representations with matching pursuit,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:29:57.845378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T04:29:54.986395Z digest=sha256:9245f69c8f3900894f6ce728c18a615bb6cc0686485373aea5810d468cf17e58

Observation fbae0c3c-d0f6-49a2-aeef-fbbd30918f69 · outbound

This paper cites Scal- ing and evaluating sparse autoencoders,.

Steering dense music retrieval with open-vocabulary concept discovery Scal- ing and evaluating sparse autoencoders,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:29:57.811516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 7923a380-b829-4a1a-8f66-98e6cd99bed2 · outbound

This paper cites Gemma scope: Open sparse autoen- coders everywhere all at once on gemma 2,.

Steering dense music retrieval with open-vocabulary concept discovery Gemma scope: Open sparse autoen- coders everywhere all at once on gemma 2,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:29:57.778546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 73e33e3c-f325-466f-8cf5-7f9e2eed8608 · outbound

This paper cites Sparse autoencoders learn monosemantic features in vision-language models,.

Steering dense music retrieval with open-vocabulary concept discovery Sparse autoencoders learn monosemantic features in vision-language models,

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-14T04:29:55.020537Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T04:29:55.020537Z digest=sha256:b02476471811027579f6b46e6b44ac2db22427c0ee8f07261eedd33d37ac620f

Observation f4836c59-a028-439d-bc0c-9736ae4d75ef · outbound

This paper cites Interpreting clip with hierarchical sparse autoencoders,.

Steering dense music retrieval with open-vocabulary concept discovery Interpreting clip with hierarchical sparse autoencoders,

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:29:57.746076Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T04:29:55.026680Z digest=sha256:ca0afa702843fb72477aa96f1eda4e24e37ddc0ec65df03f4493c2bc5d49ec8a

Observation dc995cbb-4082-4e91-b3eb-7c839894ae7c · outbound

This paper cites Eval- uating sparse autoencoders for controlling open-ended text generation,.

Steering dense music retrieval with open-vocabulary concept discovery Eval- uating sparse autoencoders for controlling open-ended text generation,

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:29:57.705793Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T04:29:55.034450Z digest=sha256:3829e1a5a005308bbbf36366ba7df6423bbe94b68aa65562f921eb12a7c79faa

Observation 43ba2f96-a5c6-4735-86fe-6cae3d525ce5 · outbound

This paper cites Improving Steering Vectors by Targeting Sparse Autoencoder Features.

Steering dense music retrieval with open-vocabulary concept discovery Improving Steering Vectors by Targeting Sparse Autoencoder Features

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-14T04:29:55.042128Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 4544b7d5-68c6-40e0-aea1-e0f0ef2ee445 · outbound

This paper cites Denoising concept vectors with sparse autoencoders for improved language model steering,.

Steering dense music retrieval with open-vocabulary concept discovery Denoising concept vectors with sparse autoencoders for improved language model steering,

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:29:57.681103Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 5ea960f9-ec0c-41d5-814c-e36f8cb977f0 · outbound

This paper cites In- terpreting and steering llms with mutual information- based explanations on sparse autoencoders,.

Steering dense music retrieval with open-vocabulary concept discovery In- terpreting and steering llms with mutual information- based explanations on sparse autoencoders,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:29:57.649570Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation d641a75b-0779-4001-8e32-6f339d22205c · outbound

This paper cites Concept steerers: Lever- aging k-sparse autoencoders for test-time controllable generations,.

Steering dense music retrieval with open-vocabulary concept discovery Concept steerers: Lever- aging k-sparse autoencoders for test-time controllable generations,

Reference 21

Resolution
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no resolver link, observed 2026-08-14T04:29:55.082168Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation c06be5fb-c643-4ee7-a999-64e552100fc6 · outbound

This paper cites Interpret and control dense retrieval with sparse latent features,.

Steering dense music retrieval with open-vocabulary concept discovery Interpret and control dense retrieval with sparse latent features,

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:29:57.628501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation c96e8ab7-3c8b-4f80-926c-f1ad43d6a265 · outbound

This paper cites Decoding dense embed- dings: Sparse autoencoders for interpreting and dis- cretizing dense retrieval,.

Steering dense music retrieval with open-vocabulary concept discovery Decoding dense embed- dings: Sparse autoencoders for interpreting and dis- cretizing dense retrieval,

Reference 23

Resolution
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raw_fallback, observed 2026-08-14T04:29:57.597024Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 2294b1e4-9b33-4c05-952c-9b86f88dde06 · outbound

This paper cites Discovering and steering interpretable concepts in large generative mu- sic models,.

Steering dense music retrieval with open-vocabulary concept discovery Discovering and steering interpretable concepts in large generative mu- sic models,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:29:57.565394Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T04:29:55.116328Z digest=sha256:e0902f4e5b3c3eecabe070cb7bfcef069f28ff154ad65071364dbf29c90c870b

Observation d2b2cb65-261b-44d9-9397-ec22bd89b24b · outbound

This paper cites Universal sparse autoencoders: In- terpretable cross-model concept alignment,.

Steering dense music retrieval with open-vocabulary concept discovery Universal sparse autoencoders: In- terpretable cross-model concept alignment,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:29:57.512085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 7c247b99-aaba-49ef-862c-a01539d2c385 · outbound

This paper cites Interpreting the linear structure of vision- language model embedding spaces,.

Steering dense music retrieval with open-vocabulary concept discovery Interpreting the linear structure of vision- language model embedding spaces,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:29:57.469110Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 898a35f0-46f8-461d-814f-d5e035e19c7d · outbound

This paper cites Disentangling Dense Embeddings with Sparse Autoencoders.

Steering dense music retrieval with open-vocabulary concept discovery Disentangling Dense Embeddings with Sparse Autoencoders

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-14T04:29:55.165739Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T04:29:55.165739Z digest=sha256:19cb3adc9d558c618579684e694841766df4b1e6e195b6e53ead64415c50b33a

Observation a52028c4-0f77-4e6a-a434-c627aba1bda0 · outbound

This paper cites Decomposing multimodal embedding spaces with group-sparse au- toencoders,.

Steering dense music retrieval with open-vocabulary concept discovery Decomposing multimodal embedding spaces with group-sparse au- toencoders,

Reference 28

Resolution
verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation e39bb8c9-e27f-43f4-b91d-ca2df74e18bc · outbound

This paper cites Discover-then-name: Task-agnostic concept bottle- necks via automated concept discovery,.

Steering dense music retrieval with open-vocabulary concept discovery Discover-then-name: Task-agnostic concept bottle- necks via automated concept discovery,

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:29:57.384751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 15f55d79-b291-4f12-a9b7-78341542406b · outbound

This paper cites From What to How: Attributing CLIP's Latent Components Reveals Unexpected Semantic Reliance.

Steering dense music retrieval with open-vocabulary concept discovery From What to How: Attributing CLIP's Latent Components Reveals Unexpected Semantic Reliance

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-14T04:29:55.199436Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 2a9b0c30-a994-4e9e-8fd4-e1aabb55ee5a · outbound

This paper cites Sparse autoencoders do not find canonical units of analysis,.

Steering dense music retrieval with open-vocabulary concept discovery Sparse autoencoders do not find canonical units of analysis,

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:29:57.261525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 7f22e999-5795-440b-b5a8-c773795aa833 · outbound

This paper cites A is for absorption: Studying feature splitting and absorption in sparse au- toencoders,.

Steering dense music retrieval with open-vocabulary concept discovery A is for absorption: Studying feature splitting and absorption in sparse au- toencoders,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:29:57.148084Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation c269ef18-454c-43b5-8892-305ffafdb1bc · outbound

This paper cites Ortsae: Orthogonal sparse autoencoders uncover atomic features,.

Steering dense music retrieval with open-vocabulary concept discovery Ortsae: Orthogonal sparse autoencoders uncover atomic features,

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-14T04:29:55.242831Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T04:29:55.242831Z digest=sha256:08160b2695e75e46ba2a3217a8a273d1fb39ffbd9d4d70f618b0d87bffb34d3a

Observation de9e7b63-7153-42e3-a27f-bf9e09b0d104 · outbound

This paper cites Mind the gap: Understanding the modality gap in multi-modal contrastive representation learning,.

Steering dense music retrieval with open-vocabulary concept discovery Mind the gap: Understanding the modality gap in multi-modal contrastive representation learning,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:29:57.078945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 2e3c9e91-a73f-493b-9546-52f26b4a7917 · outbound

This paper cites Sparse Autoencoders Find Highly Interpretable Features in Language Models.

Steering dense music retrieval with open-vocabulary concept discovery Sparse Autoencoders Find Highly Interpretable Features in Language Models

Reference 35

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 5d25a6d7-cf54-4914-ad69-7b5d1f565293 · outbound

This paper cites Large-scale contrastive language- audio pretraining with feature fusion and keyword-to- caption augmentation,.

Steering dense music retrieval with open-vocabulary concept discovery Large-scale contrastive language- audio pretraining with feature fusion and keyword-to- caption augmentation,

Reference 36

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 0f3304b9-0583-4f31-9807-820fb890700f · outbound

This paper cites Un- derstanding the modality gap in clip,.

Steering dense music retrieval with open-vocabulary concept discovery Un- derstanding the modality gap in clip,

Reference 37

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation e5356885-ea53-43eb-aafc-14731cd796dd · outbound

This paper cites Slap: Siamese language-audio pretraining without negative samples for music understanding,.

Steering dense music retrieval with open-vocabulary concept discovery Slap: Siamese language-audio pretraining without negative samples for music understanding,

Reference 38

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 08c969bb-ef80-4460-a1e2-69cc94ef509e · outbound

This paper cites An analysis of variance test for normality (complete samples),.

Steering dense music retrieval with open-vocabulary concept discovery An analysis of variance test for normality (complete samples),

Reference 39

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 5552fedc-b90e-4f00-8697-130d54e8e7fd · outbound

This paper cites Jamendo- maxcaps: A large scale music-caption dataset with im- puted metadata,.

Steering dense music retrieval with open-vocabulary concept discovery Jamendo- maxcaps: A large scale music-caption dataset with im- puted metadata,

Reference 40

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 7a6c7b2f-d8f1-4156-b1db-87f5ad84c7c7 · outbound

This paper cites Muq: Self-supervised music representation learning with mel residual vector quan- tization,.

Steering dense music retrieval with open-vocabulary concept discovery Muq: Self-supervised music representation learning with mel residual vector quan- tization,

Reference 41

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation ab0e1531-36bc-4876-9d64-08ef86e104cf · outbound

This paper cites Cross the gap: Exposing the intra- modal misalignment in clip via modality inversion,.

Steering dense music retrieval with open-vocabulary concept discovery Cross the gap: Exposing the intra- modal misalignment in clip via modality inversion,

Reference 42

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation accd8073-ed80-456b-b1ed-e722bff4bd9e · outbound

This paper cites Training-free diffusion priors for text-to-image generation via optimization-based visual inversion,.

Steering dense music retrieval with open-vocabulary concept discovery Training-free diffusion priors for text-to-image generation via optimization-based visual inversion,

Reference 43

Resolution
verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation de85275b-c809-4a00-918e-5600c1c0c849 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Steering dense music retrieval with open-vocabulary concept discovery Adam: A Method for Stochastic Optimization

Reference 44

Resolution
unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 1af6e4e1-d0b2-4755-8174-0cb89aedbef9 · outbound

This paper cites A fast iterative shrinkage- thresholding algorithm for linear inverse problems,.

Steering dense music retrieval with open-vocabulary concept discovery A fast iterative shrinkage- thresholding algorithm for linear inverse problems,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:29:56.598581Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Pith citing papers

Observation 43e98c51-84ce-445b-90a6-2187d66a315a · inbound

Steering dense music retrieval with open-vocabulary concept discovery cites this paper.

Steering dense music retrieval with open-vocabulary concept discovery Steering dense music retrieval with open-vocabulary concept discovery

Reference 1

Resolution
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local_arxiv, observed 2026-08-14T04:29:56.545267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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