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Paper Citation Record · LEDGER

DenoiseRank: Learning to Rank by Diffusion Models

As of 12 August 2026, this Paper Citation Record lists 54 of 54 outbound references and 0 inbound Pith citation observations for arXiv:2604.20852.

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

pith.paper-citation-record.v1
2604.20852 v1

Coverage vector

measured 54 of 54 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-15T22:14:59.087555Z

measured 54 of 54 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

54 of 54 outbound references displayed

  • verified exact5
  • verified fuzzy19
  • unresolved30
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fab516cc-118a-4959-96e1-c5f656e2cd62 · outbound

This paper cites In Proceedings of the 22nd international conference on Machine learning, pages 89–96.

DenoiseRank: Learning to Rank by Diffusion Models In Proceedings of the 22nd international conference on Machine learning, pages 89–96

Reference 1

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 0e939a53-8d41-4274-ab01-7b2e92f7ee53 · outbound

This paper cites Jonathan Ho, Ajay Jain, and Pieter Abbeel.

DenoiseRank: Learning to Rank by Diffusion Models Jonathan Ho, Ajay Jain, and Pieter Abbeel

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 1ce78375-29b9-47b4-a570-79bab6e14c00 · outbound

This paper cites MrRank: Improving Question Answering Retrieval System through Multi-Result Ranking Model.

DenoiseRank: Learning to Rank by Diffusion Models MrRank: Improving Question Answering Retrieval System through Multi-Result Ranking Model

Reference 3

Resolution
verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation bd655dab-ad7d-4dab-a49e-80ffeaa9ef42 · outbound

This paper cites Wasserstein Generative Learning of Conditional Distribution.

DenoiseRank: Learning to Rank by Diffusion Models Wasserstein Generative Learning of Conditional Distribution

Reference 4

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation c93df18f-0b4e-470b-82dc-909a50466a2e · outbound

This paper cites ROIC-DM: Robust Text Inference and Classification via Diffusion Model.

DenoiseRank: Learning to Rank by Diffusion Models ROIC-DM: Robust Text Inference and Classification via Diffusion Model

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-15T22:16:42.688518Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 23ccbd3a-08ca-4f7c-9bcc-29afc845d091 · outbound

This paper cites an unresolved cited work.

DenoiseRank: Learning to Rank by Diffusion Models Unresolved cited work

Reference 6

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 1a220bd7-e012-46c9-9b61-c5fc6f4e7e4b · outbound

This paper cites an unresolved cited work.

DenoiseRank: Learning to Rank by Diffusion Models Unresolved cited work

Reference 7

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 70cf7c7f-8938-4bb8-b5e3-1af36cefbead · outbound

This paper cites an unresolved cited work.

DenoiseRank: Learning to Rank by Diffusion Models Unresolved cited work

Reference 8

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 3374d26d-c277-4316-8041-4a6a20f3351f · outbound

This paper cites an unresolved cited work.

DenoiseRank: Learning to Rank by Diffusion Models Unresolved cited work

Reference 9

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 1f95cb00-c185-4a31-bb15-9ec76e9666ef · outbound

This paper cites an unresolved cited work.

DenoiseRank: Learning to Rank by Diffusion Models Unresolved cited work

Reference 10

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 896a99e0-4bb6-4228-81f8-c4f20d6a6ce0 · outbound

This paper cites an unresolved cited work.

DenoiseRank: Learning to Rank by Diffusion Models Unresolved cited work

Reference 11

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 38e24c8d-4460-434d-9c62-69ccaa811d0f · outbound

This paper cites We have proposed two hypotheses: (1) DenoiseRank demonstrates greater robustness for sparse data (with few effec- tive features).

DenoiseRank: Learning to Rank by Diffusion Models We have proposed two hypotheses: (1) DenoiseRank demonstrates greater robustness for sparse data (with few effec- tive features)

Reference 12

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 5b68602b-5058-4b81-a650-05866147d7d1 · outbound

This paper cites Effec- tive feature count ranking: YAHOO > ISTLLA > WEB30K.

DenoiseRank: Learning to Rank by Diffusion Models Effec- tive feature count ranking: YAHOO > ISTLLA > WEB30K

Reference 13

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 3af22ef8-412f-4b15-a8a8-901a66bfa19b · outbound

This paper cites an unresolved cited work.

DenoiseRank: Learning to Rank by Diffusion Models Unresolved cited work

Reference 14

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation fbcf4a39-088b-4259-9657-289f4bafa412 · outbound

This paper cites an unresolved cited work.

DenoiseRank: Learning to Rank by Diffusion Models Unresolved cited work

Reference 15

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 20827002-dcdd-4406-9a30-a8327a386105 · outbound

This paper cites an unresolved cited work.

DenoiseRank: Learning to Rank by Diffusion Models Unresolved cited work

Reference 16

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation ffcc1db0-d742-4957-be12-5e7d31965062 · outbound

This paper cites In contrast, query-document length in Istella presents a hump distribution (max length < 190), and those in Yahoo gradually decreases be- tween 1 and 120 (max length < 140).

DenoiseRank: Learning to Rank by Diffusion Models In contrast, query-document length in Istella presents a hump distribution (max length < 190), and those in Yahoo gradually decreases be- tween 1 and 120 (max length < 140)

Reference 17

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 623f3f3e-6688-4890-8351-1ec0492b1ad0 · outbound

This paper cites an unresolved cited work.

DenoiseRank: Learning to Rank by Diffusion Models Unresolved cited work

Reference 18

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 1e4e134e-3257-4887-90fb-0cca5516c6a3 · outbound

This paper cites an unresolved cited work.

DenoiseRank: Learning to Rank by Diffusion Models Unresolved cited work

Reference 19

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 0416ed15-a309-48d4-affe-c337c4191828 · outbound

This paper cites an unresolved cited work.

DenoiseRank: Learning to Rank by Diffusion Models Unresolved cited work

Reference 20

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 52dfe235-876c-42d8-841b-16d46a9a7d3d · outbound

This paper cites an unresolved cited work.

DenoiseRank: Learning to Rank by Diffusion Models Unresolved cited work

Reference 21

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 57db54ee-5615-4fa4-be72-3856c2db3dc1 · outbound

This paper cites an unresolved cited work.

DenoiseRank: Learning to Rank by Diffusion Models Unresolved cited work

Reference 22

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation b7f3ede0-a820-4be9-b240-667106f2a3c0 · outbound

This paper cites The model per- forms optimally on the Istella dataset at T=.

DenoiseRank: Learning to Rank by Diffusion Models The model per- forms optimally on the Istella dataset at T=

Reference 23

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 868465c3-e9ae-4215-8bdf-8dc6a66ae470 · outbound

This paper cites E.2 Noise Scheduler The noise scheduler is the way in which the αt changes during diffusion, where αt := Qt s=1αs, see eq.

DenoiseRank: Learning to Rank by Diffusion Models E.2 Noise Scheduler The noise scheduler is the way in which the αt changes during diffusion, where αt := Qt s=1αs, see eq

Reference 24

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation f20f6bdf-11f6-4210-8bab-79293936f0ca · outbound

This paper cites an unresolved cited work.

DenoiseRank: Learning to Rank by Diffusion Models Unresolved cited work

Reference 25

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 9b2f22e8-c429-401b-8b52-ebaa24081256 · outbound

This paper cites TruncatedLinear>Sqrt>Linear>Cosine.

DenoiseRank: Learning to Rank by Diffusion Models TruncatedLinear>Sqrt>Linear>Cosine

Reference 26

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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 2026-08-12T06:34:41.77262+00:00.

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Observation dff9dc43-0420-48ea-a003-d4116c70fc39 · outbound

This paper cites E.3 The Number of Denoise Network Layers As shown in Figure.

DenoiseRank: Learning to Rank by Diffusion Models E.3 The Number of Denoise Network Layers As shown in Figure

Reference 27

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verified fuzzy
raw_fallback, observed 2026-05-15T22:16:43.364621Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 667068e4-d42a-40dc-897c-642bec7f243a · outbound

This paper cites an unresolved cited work.

DenoiseRank: Learning to Rank by Diffusion Models Unresolved cited work

Reference 28

Resolution
unresolved
raw_fallback, observed 2026-05-15T22:16:43.398004Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 56bbb547-6295-4dcc-9f1a-d806113e07d4 · outbound

This paper cites an unresolved cited work.

DenoiseRank: Learning to Rank by Diffusion Models Unresolved cited work

Reference 29

Resolution
unresolved
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 52ece416-f343-4496-bda1-29d8ce7c5c44 · outbound

This paper cites an unresolved cited work.

DenoiseRank: Learning to Rank by Diffusion Models Unresolved cited work

Reference 30

Resolution
unresolved
raw_fallback, observed 2026-05-15T22:16:43.289500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 8a5f3096-2420-4c3a-b7ab-bf44418e888a · outbound

This paper cites an unresolved cited work.

DenoiseRank: Learning to Rank by Diffusion Models Unresolved cited work

Reference 31

Resolution
verified exact
arxiv_id, observed 2026-05-15T22:16:42.701852Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 51b07e06-f657-43ab-a185-f39f1df58f65 · outbound

This paper cites an unresolved cited work.

DenoiseRank: Learning to Rank by Diffusion Models Unresolved cited work

Reference 32

Resolution
unresolved
raw_fallback, observed 2026-05-15T22:16:43.339775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation a6bacd94-77f8-4aa5-bccc-61a04e5df623 · outbound

This paper cites an unresolved cited work.

DenoiseRank: Learning to Rank by Diffusion Models Unresolved cited work

Reference 33

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation e9ce06f2-89fb-4ca0-9f79-3cfc5f9186c5 · outbound

This paper cites This is a way to boost premium content exposure.

DenoiseRank: Learning to Rank by Diffusion Models This is a way to boost premium content exposure

Reference 34

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raw_fallback, observed 2026-05-15T22:16:43.269094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation da41b377-060c-490e-a022-1e18deed8cc0 · outbound

This paper cites For example.

DenoiseRank: Learning to Rank by Diffusion Models For example

Reference 35

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-15T22:14:59.087555Z digest=sha256:4551e05a6df7ed493e1f89a311ce5d98c5c979e99d1faae7fd30ef1f3243252c

Observation 1524b14e-8f1a-4093-91f2-1498b9435151 · outbound

This paper cites an unresolved cited work.

DenoiseRank: Learning to Rank by Diffusion Models Unresolved cited work

Reference 36

Resolution
unresolved
raw_fallback, observed 2026-05-15T22:16:43.251640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-15T22:14:59.087555Z digest=sha256:970e170b7ce34b52918f051d0357b3f29aadaa382df455c6f0776ba6571bfb1a

Observation 4ad5803c-da91-4051-8a07-1ce319414b3b · outbound

This paper cites Unfortunately, previous LTR models did not con- sider uncertainty for ranking and may not rank items diversely.

DenoiseRank: Learning to Rank by Diffusion Models Unfortunately, previous LTR models did not con- sider uncertainty for ranking and may not rank items diversely

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-05-15T22:16:43.259185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-15T22:14:59.087555Z digest=sha256:1884f66815b0be194b392a6a128e7003db32700b7224f61d88cf281c900a76ce

Observation 1f192383-9ae4-4ac6-9fa1-56e97b20bca7 · outbound

This paper cites Best performance per column in bold.

DenoiseRank: Learning to Rank by Diffusion Models Best performance per column in bold

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-05-15T22:16:43.281501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation e84254ba-915c-482a-aab6-44e0bdd5e051 · outbound

This paper cites an unresolved cited work.

DenoiseRank: Learning to Rank by Diffusion Models Unresolved cited work

Reference 39

Resolution
unresolved
raw_fallback, observed 2026-05-15T22:16:43.414356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 1213d8ba-c5ac-4ce7-8029-4d87d2ac7b12 · outbound

This paper cites It proved our extrapolate that traditional LTR models do not inject un- certainty which results in a static ranking se- quence.

DenoiseRank: Learning to Rank by Diffusion Models It proved our extrapolate that traditional LTR models do not inject un- certainty which results in a static ranking se- quence

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-05-15T22:16:43.423195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 1d13e5db-93a3-4e1b-9e8d-886197952f08 · outbound

This paper cites According to the above analysis, our DenoiseR- ank can be applied to areas requiring diverse rank- ing sequences of items.

DenoiseRank: Learning to Rank by Diffusion Models According to the above analysis, our DenoiseR- ank can be applied to areas requiring diverse rank- ing sequences of items

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-05-15T22:16:43.427388Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 63b5e1a9-ccf9-420c-a592-0f73b672cdb4 · outbound

This paper cites an unresolved cited work.

DenoiseRank: Learning to Rank by Diffusion Models Unresolved cited work

Reference 42

Resolution
unresolved
raw_fallback, observed 2026-05-15T22:16:43.435786Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 76cc66b0-b81c-43fb-bf08-df6353e7a051 · outbound

This paper cites an unresolved cited work.

DenoiseRank: Learning to Rank by Diffusion Models Unresolved cited work

Reference 43

Resolution
unresolved
raw_fallback, observed 2026-05-15T22:16:43.406482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 206e7d60-c4da-45d2-a252-c72a0d76fdf4 · outbound

This paper cites an unresolved cited work.

DenoiseRank: Learning to Rank by Diffusion Models Unresolved cited work

Reference 44

Resolution
unresolved
raw_fallback, observed 2026-05-15T22:16:43.439790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-15T22:14:59.087555Z digest=sha256:92ef5892ce4a85d6c00ad294bf2f04f961e21b8ca6a585e1a37064180d05220f

Observation 0a3d1031-f865-4518-8078-11b21e4194c4 · outbound

This paper cites an unresolved cited work.

DenoiseRank: Learning to Rank by Diffusion Models Unresolved cited work

Reference 45

Resolution
unresolved
raw_fallback, observed 2026-05-15T22:16:43.443689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-15T22:14:59.087555Z digest=sha256:b71cbec6b98b92c8943e62c0d34e571513475d8e59f236cac4f36ff17e4d650f

Observation 5b42df67-eb26-42c2-8458-1f5042a6a35b · outbound

This paper cites an unresolved cited work.

DenoiseRank: Learning to Rank by Diffusion Models Unresolved cited work

Reference 46

Resolution
unresolved
raw_fallback, observed 2026-05-15T22:16:43.390462Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-15T22:14:59.087555Z digest=sha256:7706d537cc385b96650d2db3e31f52ad0b1d29157bb2321a5803ed30d52c32dc

Observation adcaf187-05bc-4564-91fd-bec8c770431b · outbound

This paper cites For different loss functions, we use AdamW optimizer and scan learning rate∈0.01,0.001,0.0001.

DenoiseRank: Learning to Rank by Diffusion Models For different loss functions, we use AdamW optimizer and scan learning rate∈0.01,0.001,0.0001

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-05-15T22:16:43.382052Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-15T22:14:59.087555Z digest=sha256:97f6b9dfa1d72c4182000aad840b3774708391a1154ea559583e25f582cd784b

Observation 6337a443-50a8-40b5-bf9b-df604a909161 · outbound

This paper cites an unresolved cited work.

DenoiseRank: Learning to Rank by Diffusion Models Unresolved cited work

Reference 48

Resolution
unresolved
raw_fallback, observed 2026-05-15T22:16:43.386126Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 0d310615-3701-4d1f-b377-e9cf539f72b6 · outbound

This paper cites an unresolved cited work.

DenoiseRank: Learning to Rank by Diffusion Models Unresolved cited work

Reference 49

Resolution
unresolved
raw_fallback, observed 2026-05-15T22:16:43.431659Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-15T22:14:59.087555Z digest=sha256:53ffc65d26cdade3dba61c5fce893a59eeb382265e200ada8de5a13eb80043de

Observation a4267807-4c85-4912-b320-fa1152539b1d · outbound

This paper cites How- ever, for the Yahoo! and Istella datasets, train- ing with MSE loss is the best choice.

DenoiseRank: Learning to Rank by Diffusion Models How- ever, for the Yahoo! and Istella datasets, train- ing with MSE loss is the best choice

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-05-15T22:16:43.294038Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-15T22:14:59.087555Z digest=sha256:8ff1e30bb4eef9c197e0e13874ca309ea6f9328aa38d7f145d9e68718338edd6

Observation 4f8813f1-caa4-486a-8e49-5c457f7b61ff · outbound

This paper cites an unresolved cited work.

DenoiseRank: Learning to Rank by Diffusion Models Unresolved cited work

Reference 51

Resolution
verified exact
arxiv_id, observed 2026-05-15T22:16:42.681473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-15T22:14:59.087555Z digest=sha256:9fcee2187efeb82e46b4449816110af21c370dfb8ea1e9d1e71f8bcb51abc260

Observation 716d9035-8bff-4741-be18-faf25d0c322c · outbound

This paper cites Therefore, it is necessary to strike a balance between time and performance and to use the appropriate time step in practice.

DenoiseRank: Learning to Rank by Diffusion Models Therefore, it is necessary to strike a balance between time and performance and to use the appropriate time step in practice

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-05-15T22:16:43.336227Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-15T22:14:59.087555Z digest=sha256:5594e3737782c4295257eff3aa217d0d7cccb17b6e7fa14f30acaa11280f2642

Observation b7fc70cb-95a3-4656-8e2e-585134c9d30e · outbound

This paper cites an unresolved cited work.

DenoiseRank: Learning to Rank by Diffusion Models Unresolved cited work

Reference 53

Resolution
unresolved
raw_fallback, observed 2026-05-15T22:16:43.402563Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-15T22:14:59.087555Z digest=sha256:67f60529a37c0a7aba7fd8e514f3762153ea5208239a473c82dae5693fe014bd

Observation 98024416-be1e-4be6-b8c3-2388d75b916f · outbound

This paper cites The time processed by the tree- based models is significantly lower than that by the neural network-based models, which is due to their more light-weight model struc- ture and size.

DenoiseRank: Learning to Rank by Diffusion Models The time processed by the tree- based models is significantly lower than that by the neural network-based models, which is due to their more light-weight model struc- ture and size

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-05-15T22:16:43.263816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-15T22:14:59.087555Z digest=sha256:301a39b8d82a2915a0184ad05cca3699b941b272848d87da21fbc686965131b3

Pith citing papers

No inbound Pith citation observations are available.