Paper Citation Record · LEDGER

Representation Degeneration Problem in Training Natural Language Generation Models

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 28 inbound Pith citation observations for arXiv:1907.12009.

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

pith.paper-citation-record.v1
1907.12009 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 28 of 28 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 28 of 28 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T05:12:33.516692Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T08:19:44.366737Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 2191d9ec-0f33-433e-81f8-41aba9399977 · inbound

LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale cites this paper.

LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale Representation Degeneration Problem in Training Natural Language Generation Models

Reference 133

Resolution: verified exact; arxiv_id, observed 2026-05-13T13:35:36.078782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d1c43f97-007f-4651-8943-3a54b89bda33 · inbound

Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference cites this paper.

Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference Representation Degeneration Problem in Training Natural Language Generation Models

Reference 136

Resolution: verified exact; arxiv_id, observed 2026-05-20T17:46:47.049310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e273e7d8-50ab-4684-bee0-2c825b36252e · inbound

Better Embeddings with Coupled Adam cites this paper.

Better Embeddings with Coupled Adam Representation Degeneration Problem in Training Natural Language Generation Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-08T05:12:33.516692Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cc95aa04-cdbd-4173-ac24-230369221090 · inbound

Low-Perplexity LLM-Generated Sequences and Where To Find Them cites this paper.

Low-Perplexity LLM-Generated Sequences and Where To Find Them Representation Degeneration Problem in Training Natural Language Generation Models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T20:44:58.954375Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 904fb84a-b1c0-4bc6-a8b3-0501247744fd · inbound

SemCSE: Semantic Contrastive Sentence Embeddings Using LLM-Generated Summaries For Scientific Abstracts cites this paper.

SemCSE: Semantic Contrastive Sentence Embeddings Using LLM-Generated Summaries For Scientific Abstracts Representation Degeneration Problem in Training Natural Language Generation Models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T16:35:30.260801Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0090a1f5-657c-417f-9189-6a015e5362aa · inbound

Modality Alignment with Multi-scale Bilateral Attention for Multimodal Recommendation cites this paper.

Modality Alignment with Multi-scale Bilateral Attention for Multimodal Recommendation Representation Degeneration Problem in Training Natural Language Generation Models

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-04T19:44:04.718075Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fae43019-d7b9-4ecf-b747-cdad52f706d7 · inbound

Maximizing Local Entropy Where It Matters: Prefix-Aware Localized LLM Unlearning cites this paper.

Maximizing Local Entropy Where It Matters: Prefix-Aware Localized LLM Unlearning Representation Degeneration Problem in Training Natural Language Generation Models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-03T12:25:01.821481Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5b255bb7-ae98-4163-a76f-7e3ec57444a5 · inbound

Revisiting Anisotropy in Language Transformers: The Geometry of Learning Dynamics cites this paper.

Revisiting Anisotropy in Language Transformers: The Geometry of Learning Dynamics Representation Degeneration Problem in Training Natural Language Generation Models

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-11T07:35:57.180340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 52058b62-e2f8-4d36-99a4-135569212ad6 · inbound

Geometry-Aware Localized Watermarking for Copyright Protection in Embedding-as-a-Service cites this paper.

Geometry-Aware Localized Watermarking for Copyright Protection in Embedding-as-a-Service Representation Degeneration Problem in Training Natural Language Generation Models

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-11T09:36:03.860216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation aef89b46-586c-4652-8982-897b82e923b6 · inbound

Towards Faster Language Model Inference Using Mixture-of-Experts Flow Matching cites this paper.

Towards Faster Language Model Inference Using Mixture-of-Experts Flow Matching Representation Degeneration Problem in Training Natural Language Generation Models

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-10T10:29:24.653844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 91be5070-4e51-4d1a-8390-3295a92f8811 · inbound

Geometric Decoupling: Diagnosing the Structural Instability of Latent cites this paper.

Geometric Decoupling: Diagnosing the Structural Instability of Latent Representation Degeneration Problem in Training Natural Language Generation Models

Reference 56

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T09:48:48.299552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation cae2fd9b-eabb-4b0c-b918-f8d2a8cfe79e · inbound

HyperLens: Quantifying Cognitive Effort in LLMs with Fine-grained Confidence Trajectory cites this paper.

HyperLens: Quantifying Cognitive Effort in LLMs with Fine-grained Confidence Trajectory Representation Degeneration Problem in Training Natural Language Generation Models

Reference 34

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T19:36:08.966095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 99c99953-6e95-4fd5-bb0e-5edbaf8a9ab5 · inbound

How Does Attention Help? Insights from Random Matrices on Signal Recovery from Sequence Models cites this paper.

How Does Attention Help? Insights from Random Matrices on Signal Recovery from Sequence Models Representation Degeneration Problem in Training Natural Language Generation Models

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-11T05:05:58.711794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 1c53a417-f017-40bd-ad3e-f2c13a8646a3 · inbound

Elucidating Representation Degradation Problem in Diffusion Model Training cites this paper.

Elucidating Representation Degradation Problem in Diffusion Model Training Representation Degeneration Problem in Training Natural Language Generation Models

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-12T06:36:26.549194Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b4d66575-8ee2-4bba-9d35-a80201116404 · inbound

STRABLE: Benchmarking Tabular Machine Learning with Strings cites this paper.

STRABLE: Benchmarking Tabular Machine Learning with Strings Representation Degeneration Problem in Training Natural Language Generation Models

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-13T05:17:18.452001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation a2844c38-72c8-4ab1-8ad0-5ac2b5ae0c99 · inbound

Layer-wise Representation Dynamics: An Empirical Investigation Across Embedders and Base LLMs cites this paper.

Layer-wise Representation Dynamics: An Empirical Investigation Across Embedders and Base LLMs Representation Degeneration Problem in Training Natural Language Generation Models

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-14T21:58:04.043751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation dc5e2c19-5077-45e9-ba2b-b07b2a96b5cd · inbound

NITP: Next Implicit Token Prediction for LLM Pre-training cites this paper.

NITP: Next Implicit Token Prediction for LLM Pre-training Representation Degeneration Problem in Training Natural Language Generation Models

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-06-30T12:24:39.206810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6dc95a6b-e9e2-4f68-9286-d82a97625510 · inbound

NITP: Next Implicit Token Prediction for LLM Pre-training cites this paper.

NITP: Next Implicit Token Prediction for LLM Pre-training Representation Degeneration Problem in Training Natural Language Generation Models

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-07-04T00:39:16.290736Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation fe23d654-343f-4ae3-83cb-cb1bc98aa189 · inbound

NITP: Next Implicit Token Prediction for LLM Pre-training cites this paper.

NITP: Next Implicit Token Prediction for LLM Pre-training Representation Degeneration Problem in Training Natural Language Generation Models

Reference 6

Resolution: unresolved; no resolver link, observed 2026-07-14T18:45:28.635910Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2464641e-d40b-44a6-a1fa-3ac219290a29 · inbound

Decoupled Residual Quantization for Robust Semantic IDs in Recommendation cites this paper.

Decoupled Residual Quantization for Robust Semantic IDs in Recommendation Representation Degeneration Problem in Training Natural Language Generation Models

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-07-02T01:06:23.981168Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 637f68af-40a7-4d68-b495-c1cb1966f94b · inbound

Learning to Prompt: Improving Student Engagement with Adaptive LLM-based High-School Tutoring cites this paper.

Learning to Prompt: Improving Student Engagement with Adaptive LLM-based High-School Tutoring Representation Degeneration Problem in Training Natural Language Generation Models

Reference 1

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T03:39:30.464577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation a8ba26e5-17ad-4cee-85d2-4592406a760d · inbound

Channel Location Constrains the Auditability of Subliminal Learning cites this paper.

Channel Location Constrains the Auditability of Subliminal Learning Representation Degeneration Problem in Training Natural Language Generation Models

Reference 54

Resolution: verified exact; arxiv_id, observed 2026-07-04T08:19:44.368495Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6348bb86-0661-4706-87a7-ef03fe3d649e · inbound

How to deal with machine learning bias in economic history cites this paper.

How to deal with machine learning bias in economic history Representation Degeneration Problem in Training Natural Language Generation Models

Reference 42

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T18:35:58.707118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ec78f737-d848-4f8d-8f47-1904f5a047ac · inbound

Reliability Scaling Laws for Quantized Large Language Models cites this paper.

Reliability Scaling Laws for Quantized Large Language Models Representation Degeneration Problem in Training Natural Language Generation Models

Reference 146

Resolution: unresolved; no resolver link, observed 2026-07-14T08:45:52.855783Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 13d42076-af85-40c8-ab8b-de368453724b · inbound

Scaling Point-in-Time Language Models cites this paper.

Scaling Point-in-Time Language Models Representation Degeneration Problem in Training Natural Language Generation Models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-02T15:39:36.775680Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f70dce71-c672-455e-90f7-32b35e07fb7b · inbound

SpecFormer: Mitigating Embedding and Attention Collapse via Spectral-Aware Transformer for Recommendation cites this paper.

SpecFormer: Mitigating Embedding and Attention Collapse via Spectral-Aware Transformer for Recommendation Representation Degeneration Problem in Training Natural Language Generation Models

Reference 54

Resolution: unresolved; no resolver link, observed 2026-07-31T23:20:21.516591Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 85186d44-c892-490e-b2da-4ea130d879d7 · inbound

SpecFormer: Mitigating Embedding and Attention Collapse via Spectral-Aware Transformer for Recommendation cites this paper.

SpecFormer: Mitigating Embedding and Attention Collapse via Spectral-Aware Transformer for Recommendation Representation Degeneration Problem in Training Natural Language Generation Models

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-04T04:02:20.090483Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a3b02c52-8b58-487f-8fd0-5370dbf6c887 · inbound

ChaosProbe: A Neurochaotic Lens on Frozen Transformer Input-Embedding Spaces cites this paper.

ChaosProbe: A Neurochaotic Lens on Frozen Transformer Input-Embedding Spaces Representation Degeneration Problem in Training Natural Language Generation Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-04T17:41:17.425828Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.