Paper Citation Record · LEDGER

Decision Trees That Remember: Gradient-Based Learning of Recurrent Decision Trees with Memory

As of 21 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:2502.04052.

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

pith.paper-citation-record.v1
2502.04052 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T23:49:09.478724Z

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+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

30 of 30 outbound references displayed

verified exact2
verified fuzzy18
unresolved10
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e22b49fd-5b0f-4fcb-8932-816b520cb67b · outbound

This paper cites Optuna: A next-generation hyperparameter optimization framework.

Decision Trees That Remember: Gradient-Based Learning of Recurrent Decision Trees with Memory Optuna: A next-generation hyperparameter optimization framework

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-08T23:49:09.391615Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ba7c3ade-2752-4e0d-ab0e-61e2be373de2 · outbound

This paper cites Learning Decision Trees Recurrently Through Communication.

Decision Trees That Remember: Gradient-Based Learning of Recurrent Decision Trees with Memory Learning Decision Trees Recurrently Through Communication

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-08-08T23:49:09.548105Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 405e9ab2-e982-4ed5-b9bf-5aef99072cb1 · outbound

This paper cites Linear model decision trees as surrogates in optimization of engineering applications.

Decision Trees That Remember: Gradient-Based Learning of Recurrent Decision Trees with Memory Linear model decision trees as surrogates in optimization of engineering applications

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T23:49:09.731426Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ce6181c0-dedd-4b89-aaf5-6b983f9224b1 · outbound

This paper cites xLSTM: Extended Long Short-Term Memory.

Decision Trees That Remember: Gradient-Based Learning of Recurrent Decision Trees with Memory xLSTM: Extended Long Short-Term Memory

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-08T23:49:09.401510Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0a28c71c-c2eb-45d2-bd4d-b448f491345d · outbound

This paper cites Classification and regression trees.

Decision Trees That Remember: Gradient-Based Learning of Recurrent Decision Trees with Memory Classification and regression trees

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T23:49:09.722364Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5a775fd2-e9b5-49d4-954f-ea44e8e814d2 · outbound

This paper cites Prediction of financial time series with recurrent lolimot (locally linear model tree).

Decision Trees That Remember: Gradient-Based Learning of Recurrent Decision Trees with Memory Prediction of financial time series with recurrent lolimot (locally linear model tree)

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T23:49:09.714051Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 34ceda48-0bc8-4543-9ac8-33591e4d46ca · outbound

This paper cites Learning online smooth predictors for realtime camera planning using recurrent decision trees.

Decision Trees That Remember: Gradient-Based Learning of Recurrent Decision Trees with Memory Learning online smooth predictors for realtime camera planning using recurrent decision trees

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T23:49:09.705561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 87841ee7-24d0-4924-88c2-301050b761b5 · outbound

This paper cites Xgboost: A scalable tree boosting system.

Decision Trees That Remember: Gradient-Based Learning of Recurrent Decision Trees with Memory Xgboost: A scalable tree boosting system

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T23:49:09.696945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 8da97fe0-e829-4487-9d28-13d2af065aae · outbound

This paper cites The role of decision tree representation in regression problems--an evolutionary perspective.

Decision Trees That Remember: Gradient-Based Learning of Recurrent Decision Trees with Memory The role of decision tree representation in regression problems--an evolutionary perspective

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T23:49:09.688521Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9fbfbe0a-fb00-4221-ab05-99ac74c2801c · outbound

This paper cites Finding structure in time.

Decision Trees That Remember: Gradient-Based Learning of Recurrent Decision Trees with Memory Finding structure in time

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-08T23:49:09.420276Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dee97635-c8c3-4238-90ca-79fb8ac5bc2a · outbound

This paper cites The vanishing gradient problem during learning recurrent neural nets and problem solutions.

Decision Trees That Remember: Gradient-Based Learning of Recurrent Decision Trees with Memory The vanishing gradient problem during learning recurrent neural nets and problem solutions

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T23:49:09.675023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e5d9090b-294c-40a6-8bf5-d624792a663a · outbound

This paper cites Soft decision trees.

Decision Trees That Remember: Gradient-Based Learning of Recurrent Decision Trees with Memory Soft decision trees

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T23:49:09.666662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0ae032af-d034-4849-8f61-75649e8904c1 · outbound

This paper cites Sdtr: Soft decision tree regressor for tabular data.

Decision Trees That Remember: Gradient-Based Learning of Recurrent Decision Trees with Memory Sdtr: Soft decision tree regressor for tabular data

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T23:49:09.656988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 494df550-8a6c-45ca-bd79-62c41db5c912 · outbound

This paper cites Gradtree: Learning axis-aligned decision trees with gradient descent.

Decision Trees That Remember: Gradient-Based Learning of Recurrent Decision Trees with Memory Gradtree: Learning axis-aligned decision trees with gradient descent

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T23:49:09.648705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation cb043894-2e5e-4fa3-9e30-370e95e0e755 · outbound

This paper cites Grande: Gradient-based decision tree ensembles for tabular data.

Decision Trees That Remember: Gradient-Based Learning of Recurrent Decision Trees with Memory Grande: Gradient-based decision tree ensembles for tabular data

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T23:49:09.640393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 758c9775-7cc2-4294-bde1-3f8ff4e14022 · outbound

This paper cites Tree-Structured Recurrent Switching Linear Dynamical Systems for Multi-Scale Modeling.

Decision Trees That Remember: Gradient-Based Learning of Recurrent Decision Trees with Memory Tree-Structured Recurrent Switching Linear Dynamical Systems for Multi-Scale Modeling

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-08-08T23:49:09.528758Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3b3943ef-2fd9-4c3b-adb9-44848a45b74d · outbound

This paper cites Nonlinear dynamic system identification.

Decision Trees That Remember: Gradient-Based Learning of Recurrent Decision Trees with Memory Nonlinear dynamic system identification

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T23:49:09.631993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a94d57ea-7fb1-487a-a7f7-ef5e0a28da5c · outbound

This paper cites Basis function networks for interpolation of local linear models.

Decision Trees That Remember: Gradient-Based Learning of Recurrent Decision Trees with Memory Basis function networks for interpolation of local linear models

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T23:49:09.623742Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ab224967-1657-4ec9-95cb-60effefa0f98 · outbound

This paper cites Resurrecting Recurrent Neural Networks for Long Sequences.

Decision Trees That Remember: Gradient-Based Learning of Recurrent Decision Trees with Memory Resurrecting Recurrent Neural Networks for Long Sequences

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-08T23:49:09.446301Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 36deb390-2806-4f73-979c-c725793980ca · outbound

This paper cites Catboost: unbiased boosting with categorical features.

Decision Trees That Remember: Gradient-Based Learning of Recurrent Decision Trees with Memory Catboost: unbiased boosting with categorical features

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-08T23:49:09.449444Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b5d6da6e-4741-4c83-83af-35223e7bb906 · outbound

This paper cites an unresolved cited work.

Decision Trees That Remember: Gradient-Based Learning of Recurrent Decision Trees with Memory Unresolved cited work

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-08T23:49:09.452247Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3e3d9f61-82de-42b6-8148-a968d6c13e26 · outbound

This paper cites Tree-rnn: Tree structural recurrent neural network for network traffic classification.

Decision Trees That Remember: Gradient-Based Learning of Recurrent Decision Trees with Memory Tree-rnn: Tree structural recurrent neural network for network traffic classification

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T23:49:09.605898Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 439d4b81-2fd9-4fe3-8f6e-b4ce198df992 · outbound

This paper cites Long short-term memory.

Decision Trees That Remember: Gradient-Based Learning of Recurrent Decision Trees with Memory Long short-term memory

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T23:49:09.597188Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 198fd8a2-30f1-41b2-b502-cdac12e1072f · outbound

This paper cites Backpropagation through time: what it does and how to do it.

Decision Trees That Remember: Gradient-Based Learning of Recurrent Decision Trees with Memory Backpropagation through time: what it does and how to do it

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T23:49:09.588947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a04ea63f-cbca-41a5-93ee-b139e03179d3 · outbound

This paper cites Experimental analysis of the real-time recurrent learning algorithm.

Decision Trees That Remember: Gradient-Based Learning of Recurrent Decision Trees with Memory Experimental analysis of the real-time recurrent learning algorithm

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T23:49:09.580454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 6db4f704-d94d-4259-92b4-d1ec40cc0604 · outbound

This paper cites Understanding Straight-Through Estimator in Training Activation Quantized Neural Nets.

Decision Trees That Remember: Gradient-Based Learning of Recurrent Decision Trees with Memory Understanding Straight-Through Estimator in Training Activation Quantized Neural Nets

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-08T23:49:09.466090Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 02663937-cf80-482e-8098-c77dd5a66e96 · outbound

This paper cites write newline.

Decision Trees That Remember: Gradient-Based Learning of Recurrent Decision Trees with Memory write newline

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-08T23:49:09.469211Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f9f7fb22-1491-4eb2-bb3d-cddf5a0c1ec6 · outbound

This paper cites @esa (Ref.

Decision Trees That Remember: Gradient-Based Learning of Recurrent Decision Trees with Memory @esa (Ref

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-08T23:49:09.472663Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 88c2f5b2-7923-44ce-b417-ddcc68e45301 · outbound

This paper cites an unresolved cited work.

Decision Trees That Remember: Gradient-Based Learning of Recurrent Decision Trees with Memory Unresolved cited work

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-08T23:49:09.475827Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d2c6861d-6fab-4c22-bfd8-5ff79efeee04 · outbound

This paper cites < 9˄ v !'_Xqz*0j#qͨܠ y z7-ygɊ k 6?<Ws˿? ?W;Ρ r oP ]|y4VR &e41 gu Qx&]k( 화FLO] 3G>qgb o ^? r ܵ=wq ._xftA[!W4v 5_o xO :L r|0 ,: x꾸U_s; mj;1=xŞ7 TX ;[;J ȞK y'< 2k|.

Decision Trees That Remember: Gradient-Based Learning of Recurrent Decision Trees with Memory < 9˄ v !'_Xqz*0j#qͨܠ y z7-ygɊ k 6?<Ws˿? ?W;Ρ r oP ]|y4VR &e41 gu Qx&]k( 화FLO] 3G>qgb o ^? r ܵ=wq ._xftA[!W4v 5_o xO :L r|0 ,: x꾸U_s; mj;1=xŞ7 TX ;[;J ȞK y'< 2k|

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T23:49:09.557968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Pith citing papers

No inbound Pith citation observations are available.