Paper Citation Record · LEDGER

LSTM vs. GRU vs. Bidirectional RNN for script generation

As of 16 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 0 inbound Pith citation observations for arXiv:1908.04332.

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

pith.paper-citation-record.v1
1908.04332 v1

Coverage vector

measured 25 of 25 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T13:48:19.295633Z

measured 25 of 25 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 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

25 of 25 outbound references displayed

verified exact0
verified fuzzy20
unresolved5
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1e7686bc-a929-4613-ade6-9af23e742389 · outbound

This paper cites Learning long -term dependencies with gradient descent is difficult,.

LSTM vs. GRU vs. Bidirectional RNN for script generation Learning long -term dependencies with gradient descent is difficult,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:48:20.223172Z

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.

Observation bbf85a8e-cb85-45a0-8e3a-243b9c4489d1 · outbound

This paper cites Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation.

LSTM vs. GRU vs. Bidirectional RNN for script generation Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-14T13:48:19.039916Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ac14eb06-a345-4fe6-abc4-e40006a37870 · outbound

This paper cites A Critical Review of Recurrent Neural Networks for Sequence Learning.

LSTM vs. GRU vs. Bidirectional RNN for script generation A Critical Review of Recurrent Neural Networks for Sequence Learning

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-14T13:48:19.050598Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9758cb2b-f12a-4381-8e1a-c50808c7898d · outbound

This paper cites Got.pkl,.

LSTM vs. GRU vs. Bidirectional RNN for script generation Got.pkl,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:48:20.190479Z

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.

Observation bd271f7e-13ab-4eae-975f-c22c1734b738 · outbound

This paper cites Deep Reinforcement Learning for Dialogue Generation.

LSTM vs. GRU vs. Bidirectional RNN for script generation Deep Reinforcement Learning for Dialogue Generation

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-14T13:48:19.070282Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f8e83151-26d5-4634-a4d0-188be89f2943 · outbound

This paper cites Data -driven response generation in social media,.

LSTM vs. GRU vs. Bidirectional RNN for script generation Data -driven response generation in social media,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:48:20.157614Z

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.

Observation 18f16db5-ec66-4ac8-9ab3-9792d194b86a · outbound

This paper cites A Neural Conversational Model.

LSTM vs. GRU vs. Bidirectional RNN for script generation A Neural Conversational Model

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-14T13:48:19.090328Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5dcd9622-c1ad-41f4-9947-f70e3bd12a2a · outbound

This paper cites Learning from delayed rewards,.

LSTM vs. GRU vs. Bidirectional RNN for script generation Learning from delayed rewards,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:48:20.120165Z

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.

Observation c99872fb-8094-4a96-8bd2-789843be5644 · outbound

This paper cites Sequence to sequence learning with neural networks,.

LSTM vs. GRU vs. Bidirectional RNN for script generation Sequence to sequence learning with neural networks,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:48:20.076251Z

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.

Observation 473a0d30-95de-4390-842a-b469245be3f2 · outbound

This paper cites Building end -to-end dialogue systems using generative hierarchical neural ne twork models,.

LSTM vs. GRU vs. Bidirectional RNN for script generation Building end -to-end dialogue systems using generative hierarchical neural ne twork models,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:48:20.047607Z

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.

Observation 440e6553-d8fe-4468-8fda-acb8342f0d42 · outbound

This paper cites Using Markov decision process for learning dialogue strategies,.

LSTM vs. GRU vs. Bidirectional RNN for script generation Using Markov decision process for learning dialogue strategies,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:48:20.012376Z

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.

Observation cc1d1af5-e8ab-4ccb-968a-79bb6065b89e · outbound

This paper cites A Markovian decision process,.

LSTM vs. GRU vs. Bidirectional RNN for script generation A Markovian decision process,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:48:19.984437Z

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.

Observation fbd4b0b1-0d26-43a9-8c95-6c98a6f7fb77 · outbound

This paper cites Training a Real -world POMDP-based Dialogue System,.

LSTM vs. GRU vs. Bidirectional RNN for script generation Training a Real -world POMDP-based Dialogue System,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:48:19.954246Z

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.

Observation 6ece0da1-9f3a-4e9b-9017-97705b816e4b · outbound

This paper cites Continuously Learning Neural Dialogue Management.

LSTM vs. GRU vs. Bidirectional RNN for script generation Continuously Learning Neural Dialogue Management

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-14T13:48:19.178115Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c0c7fd20-5d0f-41dc-84a5-ffad35da3470 · outbound

This paper cites Magenta,.

LSTM vs. GRU vs. Bidirectional RNN for script generation Magenta,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:48:19.900650Z

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.

Observation f4f80257-c564-448f-84dd-a9566647bf9f · outbound

This paper cites Word embedding by Keras,.

LSTM vs. GRU vs. Bidirectional RNN for script generation Word embedding by Keras,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:48:19.870194Z

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.

Observation 80371947-d542-42e9-b8f3-1ae9c91ea6ac · outbound

This paper cites Dropout: A Simple Way to Prevent Neural Networks from Overfitting,.

LSTM vs. GRU vs. Bidirectional RNN for script generation Dropout: A Simple Way to Prevent Neural Networks from Overfitting,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:48:19.840188Z

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.

Observation 7045cb26-3d82-44d4-98ba-057c96156d94 · outbound

This paper cites Densely connected convolutional networks.,.

LSTM vs. GRU vs. Bidirectional RNN for script generation Densely connected convolutional networks.,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:48:19.809145Z

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.

Observation 9723c10d-fd00-4c35-8c44-afe69fadef7f · outbound

This paper cites Rnndrop: A novel dropout for rnns in asr,.

LSTM vs. GRU vs. Bidirectional RNN for script generation Rnndrop: A novel dropout for rnns in asr,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:48:19.770167Z

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.

Observation efd9cd18-cc17-47c7-9392-2dcfa2a97d67 · outbound

This paper cites Lecture 6.5 -rmsprop: Divide the gradient by a running average of its recent magnitude,.

LSTM vs. GRU vs. Bidirectional RNN for script generation Lecture 6.5 -rmsprop: Divide the gradient by a running average of its recent magnitude,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:48:19.748707Z

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.

Observation e3b14efe-1080-4908-aed1-a2705cdfa138 · outbound

This paper cites pickle — Python object serialization,.

LSTM vs. GRU vs. Bidirectional RNN for script generation pickle — Python object serialization,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:48:19.708337Z

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.

Observation 3211f80e-6455-47c2-b3e6-2878e0a13e03 · outbound

This paper cites Learning representations by back-propagating errors,.

LSTM vs. GRU vs. Bidirectional RNN for script generation Learning representations by back-propagating errors,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:48:19.682824Z

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.

Observation 3affbb6d-6390-4920-8896-85885cdb4507 · outbound

This paper cites gru_lstm_tv_script,.

LSTM vs. GRU vs. Bidirectional RNN for script generation gru_lstm_tv_script,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:48:19.637857Z

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.

Observation 0a1e9284-ecc6-4ae5-aa9d-9924b65ecdb1 · outbound

This paper cites Game of Thrones Data,.

LSTM vs. GRU vs. Bidirectional RNN for script generation Game of Thrones Data,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:48:19.597798Z

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.

Observation 09df59c5-91bd-414a-a71d-4062b8c70fe4 · outbound

This paper cites generated_text,.

LSTM vs. GRU vs. Bidirectional RNN for script generation generated_text,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:48:19.558470Z

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.

Pith citing papers

No inbound Pith citation observations are available.