Paper Citation Record · LEDGER

Parsimonious Morpheme Segmentation with an Application to Enriching Word Embeddings

As of 16 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 0 inbound Pith citation observations for arXiv:1908.07832.

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

pith.paper-citation-record.v1
1908.07832 v2

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T12:53:05.089293Z

measured 45 of 45 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

45 of 45 outbound references displayed

verified exact0
verified fuzzy42
unresolved3
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b64ec8d4-571e-4b33-ba51-6b25f129966f · outbound

This paper cites Factored neural language models.

Parsimonious Morpheme Segmentation with an Application to Enriching Word Embeddings Factored neural language models

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:53:05.613086Z

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 2dcbc741-c0a7-42fe-86e0-67435409040d · outbound

This paper cites Semr-11: A multi-lingual gold-standard for semantic similarity and relatedness for eleven languages.

Parsimonious Morpheme Segmentation with an Application to Enriching Word Embeddings Semr-11: A multi-lingual gold-standard for semantic similarity and relatedness for eleven languages

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:53:05.602063Z

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 cfc6635a-82eb-4473-9842-80be853b7bda · outbound

This paper cites Enriching word vectors with subword information.

Parsimonious Morpheme Segmentation with an Application to Enriching Word Embeddings Enriching word vectors with subword information

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:53:05.592104Z

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 08d9ced2-5ad6-4cac-9e68-63ef5c85821d · outbound

This paper cites Alternative structures for character-level rnns.

Parsimonious Morpheme Segmentation with an Application to Enriching Word Embeddings Alternative structures for character-level rnns

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:53:05.582067Z

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 63d3e1b3-4651-4690-a0d7-796d57117302 · outbound

This paper cites A uniﬁed architecture for natural language processing: Deep neural networks with multitask learning.

Parsimonious Morpheme Segmentation with an Application to Enriching Word Embeddings A uniﬁed architecture for natural language processing: Deep neural networks with multitask learning

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:53:05.571178Z

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 515181f4-54e0-4f2f-8dc2-afaa5eb1ddeb · outbound

This paper cites Morphological word-embeddings.

Parsimonious Morpheme Segmentation with an Application to Enriching Word Embeddings Morphological word-embeddings

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:53:05.559923Z

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 dd627b8b-e2a9-4e63-a309-65d033ffa7ee · outbound

This paper cites Unsupervised discovery of mor- phemes.

Parsimonious Morpheme Segmentation with an Application to Enriching Word Embeddings Unsupervised discovery of mor- phemes

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:53:05.549108Z

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 a0ae1e27-188e-4843-92ab-74f25b0df4c9 · outbound

This paper cites Knet: A general framework for learning word embedding using morphological knowledge.

Parsimonious Morpheme Segmentation with an Application to Enriching Word Embeddings Knet: A general framework for learning word embedding using morphological knowledge

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:53:05.538053Z

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 80d81cc9-6462-4970-9e9f-fcaaa4a86826 · outbound

This paper cites Morphemes as necessary concept for structures discovery from untagged corpora.

Parsimonious Morpheme Segmentation with an Application to Enriching Word Embeddings Morphemes as necessary concept for structures discovery from untagged corpora

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:53:05.526983Z

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 495a781b-6b4e-4ae6-b4b1-738797e24e21 · outbound

This paper cites Untangling herdan’s law and heaps’ law: Mathematical and informetric arguments.

Parsimonious Morpheme Segmentation with an Application to Enriching Word Embeddings Untangling herdan’s law and heaps’ law: Mathematical and informetric arguments

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:53:05.517392Z

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 ab348ad2-c389-4ecd-8232-676336173985 · outbound

This paper cites Entropy-based subword mining with an application to word embeddings.

Parsimonious Morpheme Segmentation with an Application to Enriching Word Embeddings Entropy-based subword mining with an application to word embeddings

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:53:05.507307Z

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 90635aee-162b-40dd-9951-c6ee6e0592ad · outbound

This paper cites Finding structure in time.

Parsimonious Morpheme Segmentation with an Application to Enriching Word Embeddings Finding structure in time

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:53:05.495396Z

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 971139e5-fbeb-4c99-9ea2-280ba8577a36 · outbound

This paper cites Anlamver: Semantic model evaluation dataset for turkish-word similarity and relatedness.

Parsimonious Morpheme Segmentation with an Application to Enriching Word Embeddings Anlamver: Semantic model evaluation dataset for turkish-word similarity and relatedness

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:53:05.484421Z

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 e0fbd7a4-be9e-4cf3-8549-6b6ea9201d2b · outbound

This paper cites Problems with evaluation of word embeddings using word similarity tasks.

Parsimonious Morpheme Segmentation with an Application to Enriching Word Embeddings Problems with evaluation of word embeddings using word similarity tasks

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:53:05.470187Z

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 b60bb70c-4295-4d9f-867a-15a484272003 · outbound

This paper cites Placing search in context: The concept revisited.

Parsimonious Morpheme Segmentation with an Application to Enriching Word Embeddings Placing search in context: The concept revisited

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:53:05.457857Z

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 f8977539-1402-4663-b912-b93146b0a6cc · outbound

This paper cites Scientiﬁc method in practice.

Parsimonious Morpheme Segmentation with an Application to Enriching Word Embeddings Scientiﬁc method in practice

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:53:05.446697Z

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 0df31107-8c68-45ce-830c-10bf3458d684 · outbound

This paper cites Word segmentation by letter successor varieties.

Parsimonious Morpheme Segmentation with an Application to Enriching Word Embeddings Word segmentation by letter successor varieties

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:53:05.437033Z

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 dc745415-d144-4af7-b5e7-72390689e33d · outbound

This paper cites Unsupervised learning of mor- phology.

Parsimonious Morpheme Segmentation with an Application to Enriching Word Embeddings Unsupervised learning of mor- phology

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:53:05.425463Z

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 766cef7f-fcd3-4757-aefa-52b4da850c0d · outbound

This paper cites From phoneme to morpheme.

Parsimonious Morpheme Segmentation with an Application to Enriching Word Embeddings From phoneme to morpheme

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:53:05.413958Z

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 7d8932b5-dc90-4f5e-abab-f9849a2f00ea · outbound

This paper cites Simlex-999: Evaluating semantic models with (genuine) similarity estimation.

Parsimonious Morpheme Segmentation with an Application to Enriching Word Embeddings Simlex-999: Evaluating semantic models with (genuine) similarity estimation

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:53:05.401729Z

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 38522258-0dba-4d7a-b601-6a8285097761 · outbound

This paper cites Bidirectional LSTM-CRF Models for Sequence Tagging.

Parsimonious Morpheme Segmentation with an Application to Enriching Word Embeddings Bidirectional LSTM-CRF Models for Sequence Tagging

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-14T12:53:05.009117Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 45c32a30-a974-4477-ac35-2bc647fbad3d · outbound

This paper cites Bag of tricks for efﬁcient text classiﬁcation.

Parsimonious Morpheme Segmentation with an Application to Enriching Word Embeddings Bag of tricks for efﬁcient text classiﬁcation

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:53:05.389416Z

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 3f7dda83-5f4b-42e9-96db-a674e804f082 · outbound

This paper cites Character-aware neural language models.

Parsimonious Morpheme Segmentation with an Application to Enriching Word Embeddings Character-aware neural language models

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:53:05.376633Z

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 eeb71e05-b456-4ae7-8e35-a88324fce00a · outbound

This paper cites semantic.

Parsimonious Morpheme Segmentation with an Application to Enriching Word Embeddings semantic

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:53:05.366241Z

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 a5ab51b8-a03d-494a-b039-14a1f276069a · outbound

This paper cites Mathematical linguistics.

Parsimonious Morpheme Segmentation with an Application to Enriching Word Embeddings Mathematical linguistics

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:53:05.356856Z

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 13c2f4f7-4db1-48fb-8996-cd1805d664c3 · outbound

This paper cites Subword regularization: Improving neural network trans- lation models with multiple subword candidates.

Parsimonious Morpheme Segmentation with an Application to Enriching Word Embeddings Subword regularization: Improving neural network trans- lation models with multiple subword candidates

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:53:05.346244Z

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 63bd9c6c-b663-4da9-90c2-c208cc6e7f51 · outbound

This paper cites Morpho challenge competition 2005–2010: evaluations and results.

Parsimonious Morpheme Segmentation with an Application to Enriching Word Embeddings Morpho challenge competition 2005–2010: evaluations and results

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:53:05.335418Z

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 45fc7f35-f012-4d83-b33f-4923bca1b573 · outbound

This paper cites Better word representations with recursive neural networks for morphology.

Parsimonious Morpheme Segmentation with an Application to Enriching Word Embeddings Better word representations with recursive neural networks for morphology

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:53:05.324739Z

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 79ec2566-2c70-480c-be3b-a2b7899552e2 · outbound

This paper cites Efficient Estimation of Word Representations in Vector Space.

Parsimonious Morpheme Segmentation with an Application to Enriching Word Embeddings Efficient Estimation of Word Representations in Vector Space

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-14T12:53:05.037669Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a54ff60a-b1b1-4174-b1c1-8f812750b935 · outbound

This paper cites Distributed representations of words and phrases and their compositionality.

Parsimonious Morpheme Segmentation with an Application to Enriching Word Embeddings Distributed representations of words and phrases and their compositionality

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:53:05.311362Z

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 7a70f3ba-0ca9-4504-9da8-23c40538850c · outbound

This paper cites Linguistic regular- ities in continuous space word representations.

Parsimonious Morpheme Segmentation with an Application to Enriching Word Embeddings Linguistic regular- ities in continuous space word representations

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:53:05.300019Z

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 80a35a02-48ca-4be9-a514-3d93b3c02c3e · outbound

This paper cites Unsupervised learning of morphology without morphemes.

Parsimonious Morpheme Segmentation with an Application to Enriching Word Embeddings Unsupervised learning of morphology without morphemes

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:53:05.290011Z

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 37c4589b-1cba-4f4d-bc23-d3a1aed09030 · outbound

This paper cites Co-learning of word representations and morpheme representations.

Parsimonious Morpheme Segmentation with an Application to Enriching Word Embeddings Co-learning of word representations and morpheme representations

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:53:05.277691Z

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 5e1ac288-06c0-40a0-a735-654ade3b74bf · outbound

This paper cites Learn- ing representations by back-propagating errors.

Parsimonious Morpheme Segmentation with an Application to Enriching Word Embeddings Learn- ing representations by back-propagating errors

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:53:05.264577Z

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 1c08aafd-6413-45f8-888e-8f06abd10f40 · outbound

This paper cites Word segmentation: The role of distributional cues.

Parsimonious Morpheme Segmentation with an Application to Enriching Word Embeddings Word segmentation: The role of distributional cues

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:53:05.253785Z

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 505a6f6b-7f01-461d-a993-6215a1cbd173 · outbound

This paper cites Classiﬁcation of turkish semantic relation pairs using different sources.

Parsimonious Morpheme Segmentation with an Application to Enriching Word Embeddings Classiﬁcation of turkish semantic relation pairs using different sources

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:53:05.243000Z

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 a3efd0c5-03c3-4f17-9dff-73250d3f17d9 · outbound

This paper cites Morphology-based and sub-word language modeling for turkish speech recognition.

Parsimonious Morpheme Segmentation with an Application to Enriching Word Embeddings Morphology-based and sub-word language modeling for turkish speech recognition

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:53:05.230979Z

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 34b1f2e8-a973-474d-999e-9f0289108c46 · outbound

This paper cites Knowledge-free induction of inﬂectional morphologies.

Parsimonious Morpheme Segmentation with an Application to Enriching Word Embeddings Knowledge-free induction of inﬂectional morphologies

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:53:05.220555Z

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 e06ca6c9-ce56-4a9c-a810-1a2d38183fb3 · outbound

This paper cites Japanese and korean voice search.

Parsimonious Morpheme Segmentation with an Application to Enriching Word Embeddings Japanese and korean voice search

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:53:05.210529Z

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 ecbb2ed9-4f79-4b4e-bb47-56ae71c7fc6c · outbound

This paper cites Neural machine translation of rare words with subword units.

Parsimonious Morpheme Segmentation with an Application to Enriching Word Embeddings Neural machine translation of rare words with subword units

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:53:05.198551Z

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 ead5485c-25d7-4cde-a170-1d6ebc9a2101 · outbound

This paper cites A mathematical theory of communication.

Parsimonious Morpheme Segmentation with an Application to Enriching Word Embeddings A mathematical theory of communication

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:53:05.186911Z

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 4ea1820f-55b8-4923-a9c6-72bacac6cbe6 · outbound

This paper cites Generating text with recurrent neural networks.

Parsimonious Morpheme Segmentation with an Application to Enriching Word Embeddings Generating text with recurrent neural networks

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:53:05.174489Z

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 3570b34f-d1ce-4451-b19b-96a7e449716c · outbound

This paper cites Learning sentiment-speciﬁc word embedding for twitter sentiment classiﬁcation.

Parsimonious Morpheme Segmentation with an Application to Enriching Word Embeddings Learning sentiment-speciﬁc word embedding for twitter sentiment classiﬁcation

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:53:05.162846Z

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 113289cc-00ec-467e-b7f7-782257a51339 · outbound

This paper cites Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation.

Parsimonious Morpheme Segmentation with an Application to Enriching Word Embeddings Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-14T12:53:05.085253Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d868cedc-2a3a-4f6d-8c70-b319fd79b698 · outbound

This paper cites Bilingual word embeddings for phrase-based machine translation.

Parsimonious Morpheme Segmentation with an Application to Enriching Word Embeddings Bilingual word embeddings for phrase-based machine translation

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:53:05.150936Z

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.