Pith. sign in

Paper Citation Record · LEDGER

Efficient user history modeling with amortized inference for deep learning recommendation models

As of 15 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 2 inbound Pith citation observations for arXiv:2412.06924.

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

pith.paper-citation-record.v1
2412.06924 v1

Coverage vector

measured 16 of 16 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T19:25:19.371087Z

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:32:20.780702Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T11:32:24.403866Z

Reference resolution

16 of 16 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved16
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 90139af8-e7e2-4847-966e-8af62451539a · outbound

This paper cites an unresolved cited work.

Efficient user history modeling with amortized inference for deep learning recommendation models Unresolved cited work

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-11T19:25:19.300077Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T19:25:19.300077Z digest=sha256:1264edd326d04c9fee3ccc70611c408bcfd7d1160f7674349661b095ebf3e42a

Observation 14cf3c4f-afb3-4a77-9942-e89c6aed66ce · outbound

This paper cites an unresolved cited work.

Efficient user history modeling with amortized inference for deep learning recommendation models Unresolved cited work

Reference 2

Resolution
unresolved
raw_fallback, observed 2026-08-11T19:25:19.595995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T19:25:19.305361Z digest=sha256:81985b2b670f7c59b13ec82248e40e3d7189358c550ee3f2f003f108a58ba3eb

Observation b4a1ccfb-610c-4889-8aa6-9f25bd07a650 · outbound

This paper cites an unresolved cited work.

Efficient user history modeling with amortized inference for deep learning recommendation models Unresolved cited work

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-11T19:25:19.310359Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T19:25:19.310359Z digest=sha256:bfab5c3ca9dee0275000605a50022293a5b34a1d3de77034ac5d1b1a37835761

Observation a9c36b2c-3b4a-4111-b805-0a8ab3bbfa8c · outbound

This paper cites an unresolved cited work.

Efficient user history modeling with amortized inference for deep learning recommendation models Unresolved cited work

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-11T19:25:19.314888Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T19:25:19.314888Z digest=sha256:5414ab34481ccccdfcdd8a7137cacad5e24961bb07fef0fb421f780574b62820

Observation 489f2c5e-00ef-449d-b293-ef92d1399364 · outbound

This paper cites an unresolved cited work.

Efficient user history modeling with amortized inference for deep learning recommendation models Unresolved cited work

Reference 5

Resolution
unresolved
raw_fallback, observed 2026-08-11T19:25:19.549498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T19:25:19.324150Z digest=sha256:326f54058bf22cda7f8ffd3d261ff26bc352f5636ef80a1bd5a8cb511be4d72f

Observation 49673d1f-61a9-4e18-9108-399e21355f4f · outbound

This paper cites an unresolved cited work.

Efficient user history modeling with amortized inference for deep learning recommendation models Unresolved cited work

Reference 6

Resolution
unresolved
raw_fallback, observed 2026-08-11T19:25:19.533624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T19:25:19.328578Z digest=sha256:7224e93284fb602f9c08291558a627d90ff4fd66169e5f5381c76f795e031730

Observation 409fcffa-3425-4234-9716-617a22a6056c · outbound

This paper cites an unresolved cited work.

Efficient user history modeling with amortized inference for deep learning recommendation models Unresolved cited work

Reference 7

Resolution
unresolved
raw_fallback, observed 2026-08-11T19:25:19.517502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T19:25:19.333084Z digest=sha256:2d11a4d985e927596823d1ceed4e26d8fad9daecbd71355c4d1ff1efffd751dc

Observation efcbfda8-b1a3-4277-9256-976de8ae84ee · outbound

This paper cites an unresolved cited work.

Efficient user history modeling with amortized inference for deep learning recommendation models Unresolved cited work

Reference 8

Resolution
unresolved
raw_fallback, observed 2026-08-11T19:25:19.501305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T19:25:19.338317Z digest=sha256:ac555187b41d99763739fa031e0775e753df86d46c7b03561714e30ecbff442c

Observation 967653c4-5127-48a0-9f10-ea7a5b46e550 · outbound

This paper cites an unresolved cited work.

Efficient user history modeling with amortized inference for deep learning recommendation models Unresolved cited work

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-11T19:25:19.342380Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T19:25:19.342380Z digest=sha256:2d7268435d7137d3f7524e112b0380fba75ba5e565ca57538273232455c01576

Observation 8a9f24f1-90d0-4f09-a459-346b00d8d8b1 · outbound

This paper cites an unresolved cited work.

Efficient user history modeling with amortized inference for deep learning recommendation models Unresolved cited work

Reference 10

Resolution
unresolved
raw_fallback, observed 2026-08-11T19:25:19.476226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T19:25:19.348387Z digest=sha256:ca8f58cbf00cae6a2296050cbd388f5ed0a8d492dc71e52d98cbf5c19db8112a

Observation 76b41e1a-6639-44e8-89a9-34fca45d7de3 · outbound

This paper cites ConvFormer: Revisiting Transformer for Sequential User Modeling.

Efficient user history modeling with amortized inference for deep learning recommendation models ConvFormer: Revisiting Transformer for Sequential User Modeling

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-11T19:25:19.352654Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T19:25:19.352654Z digest=sha256:e899a407e45eb1d932f13f592f1d51cab35c6d358e2a7b67fdf5c558483a2ea6

Observation 286e6f72-6507-4f56-ab3d-a13ce1d2c783 · outbound

This paper cites an unresolved cited work.

Efficient user history modeling with amortized inference for deep learning recommendation models Unresolved cited work

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-11T19:25:19.357547Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T19:25:19.357547Z digest=sha256:f614f4d02adee834734add0a2d664a57ff25eb656c6b54b4c545e096d03ed9b3

Observation 5fb09490-9491-45b8-9ab1-93551085a0c3 · outbound

This paper cites Actions Speak Louder than Words: Trillion-Parameter Sequential Transducers for Generative Recommendations.

Efficient user history modeling with amortized inference for deep learning recommendation models Actions Speak Louder than Words: Trillion-Parameter Sequential Transducers for Generative Recommendations

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-11T19:25:19.362208Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T19:25:19.362208Z digest=sha256:ee57e4737273c117b7eba129a449562d1c878f7248be86cce5d0c759b0934c5b

Observation ff86bc31-b6f6-44cb-85be-959cdf6dc210 · outbound

This paper cites an unresolved cited work.

Efficient user history modeling with amortized inference for deep learning recommendation models Unresolved cited work

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-11T19:25:19.366682Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T19:25:19.366682Z digest=sha256:36e3924cbe318a0517432cbb28113220c97d08a85bc858b2b8162b6603ab88ff

Observation 8e021756-4056-4561-8f12-34bf06bc5bc6 · outbound

This paper cites an unresolved cited work.

Efficient user history modeling with amortized inference for deep learning recommendation models Unresolved cited work

Reference 15

Resolution
unresolved
raw_fallback, observed 2026-08-11T19:25:19.442566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T19:25:19.371087Z digest=sha256:709cd94dee1306469377d28deadfdf87996642de682c1b6729339142b3f26cf5

Observation 475a11bc-3208-4a94-bfb3-410c1f7f3c8c · outbound

This paper cites In Proceedings of the 1st workshop on deep learning for recommender systems.

Efficient user history modeling with amortized inference for deep learning recommendation models In Proceedings of the 1st workshop on deep learning for recommender systems

Reference 2016

Resolution
unresolved
no resolver link, observed 2026-08-11T19:25:19.319388Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T19:25:19.319388Z digest=sha256:154b80f87ceb90fd1ffbd9fc7cf9c924b419484d88d0d405ca3bc44c37b7fb61

Pith citing papers

Observation fd39780c-9a8d-4a3a-a740-6798d83d6dd5 · inbound

TransAct V2: Lifelong User Action Sequence Modeling on Pinterest Recommendation cites this paper.

TransAct V2: Lifelong User Action Sequence Modeling on Pinterest Recommendation Efficient user history modeling with amortized inference for deep learning recommendation models

Reference 2024

Resolution
metadata mismatch
local_arxiv, observed 2026-08-07T11:32:24.484365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T11:32:20.780702Z digest=sha256:4e2497e0e8910ccab0fa8ac2339c0f4b966340cfca5f9f642edbc95da61e971b

Observation 8094a77a-dc08-49ba-87fc-145fbe6492c9 · inbound

An Industrial-Scale Sequential Recommender for LinkedIn Feed Ranking cites this paper.

An Industrial-Scale Sequential Recommender for LinkedIn Feed Ranking Efficient user history modeling with amortized inference for deep learning recommendation models

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-02T23:53:31.977661Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T23:53:31.977661Z digest=sha256:e2e857360430d2f713596688f607ae2d1c9ecc6a5b321ebcf7a51e33a9d00e17