Paper Citation Record · LEDGER

Neural Text Generation with Unlikelihood Training

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 32 inbound Pith citation observations for arXiv:1908.04319.

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

pith.paper-citation-record.v1
1908.04319 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 32 of 32 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:23:29.575264Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T19:40:07.174377Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
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malformed identifier0
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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 4b3e41b8-75a8-436d-b219-63dbc927e9c3 · inbound

CTRL: A Conditional Transformer Language Model for Controllable Generation cites this paper.

CTRL: A Conditional Transformer Language Model for Controllable Generation Neural Text Generation with Unlikelihood Training

Reference 48

Resolution: verified exact; arxiv_id, observed 2026-05-17T06:14:02.716864Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 73037089-7a32-49c1-aad8-8c7110ea4d36 · inbound

Learning to summarize from human feedback cites this paper.

Learning to summarize from human feedback Neural Text Generation with Unlikelihood Training

Reference 64

Resolution: verified exact; arxiv_id, observed 2026-05-18T01:46:18.679129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation db1809e2-df57-4895-b7e7-9cecaf1c03d5 · inbound

Direct Preference Optimization: Your Language Model is Secretly a Reward Model cites this paper.

Direct Preference Optimization: Your Language Model is Secretly a Reward Model Neural Text Generation with Unlikelihood Training

Reference 48

Resolution: verified exact; arxiv_id, observed 2026-05-11T02:33:28.304766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation c95a52db-fc14-43e6-b792-a57acb23f7e2 · inbound

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning cites this paper.

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning Neural Text Generation with Unlikelihood Training

Reference 76

Resolution: metadata mismatch; arxiv_id, observed 2026-05-17T10:58:53.517004Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation db259ed8-6ac3-4e39-8997-7e99f524df16 · inbound

ORPO: Monolithic Preference Optimization without Reference Model cites this paper.

ORPO: Monolithic Preference Optimization without Reference Model Neural Text Generation with Unlikelihood Training

Reference 136

Resolution: metadata mismatch; arxiv_id, observed 2026-05-16T09:34:04.794717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e1ad950f-bcb4-4a33-966a-645f1a39bf38 · inbound

Agent Q: Advanced Reasoning and Learning for Autonomous AI Agents cites this paper.

Agent Q: Advanced Reasoning and Learning for Autonomous AI Agents Neural Text Generation with Unlikelihood Training

Reference 158

Resolution: metadata mismatch; arxiv_id, observed 2026-05-20T09:42:04.270036Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 22cb6a84-429b-4629-8e5f-f2c52eb3682b · inbound

The Differences Between Direct Alignment Algorithms are a Blur cites this paper.

The Differences Between Direct Alignment Algorithms are a Blur Neural Text Generation with Unlikelihood Training

Reference 41

Resolution: verified exact; arxiv_id, observed 2026-05-23T03:52:29.520281Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 3719482d-9228-4b9c-a973-3f5f38f008fa · inbound

Soft Reasoning: Navigating Solution Spaces in Large Language Models through Controlled Embedding Exploration cites this paper.

Soft Reasoning: Navigating Solution Spaces in Large Language Models through Controlled Embedding Exploration Neural Text Generation with Unlikelihood Training

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T12:23:29.575264Z

Source-reported events for the cited work

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Observation e830fb53-78a8-4b95-98e4-08ef26c4f7a0 · inbound

GOLFer: Smaller LM-Generated Documents Hallucination Filter & Combiner for Query Expansion in Information Retrieval cites this paper.

GOLFer: Smaller LM-Generated Documents Hallucination Filter & Combiner for Query Expansion in Information Retrieval Neural Text Generation with Unlikelihood Training

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T10:40:14.867721Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d2209df2-7498-4ed4-8c9d-23ce6917a6b3 · inbound

Multi-Agent Language Models: Advancing Cooperation, Coordination, and Adaptation cites this paper.

Multi-Agent Language Models: Advancing Cooperation, Coordination, and Adaptation Neural Text Generation with Unlikelihood Training

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-07T04:57:25.812220Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3944346b-d07f-4888-b30a-eef52552b6c0 · inbound

On the Fitness Landscape in the $NK$ Model cites this paper.

On the Fitness Landscape in the $NK$ Model Neural Text Generation with Unlikelihood Training

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-05T19:28:57.248796Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c236ebda-f6c7-4a5b-a2d2-a25e06254ba0 · inbound

Avoidance Decoding for Diverse Multi-Branch Story Generation cites this paper.

Avoidance Decoding for Diverse Multi-Branch Story Generation Neural Text Generation with Unlikelihood Training

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-05T11:56:55.167407Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9a6c2e49-c071-4832-b800-28a78a1a956e · inbound

Breaking the Likelihood Trap: Consistent Generative Recommendation with Graph-structured Model cites this paper.

Breaking the Likelihood Trap: Consistent Generative Recommendation with Graph-structured Model Neural Text Generation with Unlikelihood Training

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-04T10:22:38.155189Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e527a874-e97d-4d94-bd91-8784ee2e8a31 · inbound

A Universal Avoidance Method for Diverse Multi-branch Generation cites this paper.

A Universal Avoidance Method for Diverse Multi-branch Generation Neural Text Generation with Unlikelihood Training

Reference 29

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T06:51:46.367378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 667a479c-7385-4728-9831-f4dcab69aaaa · inbound

Self-Play Enhancement via Advantage-Weighted Refinement in Online Federated LLM Fine-Tuning with Real-Time Feedback cites this paper.

Self-Play Enhancement via Advantage-Weighted Refinement in Online Federated LLM Fine-Tuning with Real-Time Feedback Neural Text Generation with Unlikelihood Training

Reference 41

Resolution: verified exact; arxiv_id, observed 2026-05-11T03:50:54.392111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 5a6b95d2-3897-4e3a-b717-2d226bb7c158 · inbound

Annotations Mitigate Post-Training Mode Collapse cites this paper.

Annotations Mitigate Post-Training Mode Collapse Neural Text Generation with Unlikelihood Training

Reference 16

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T06:46:51.960967Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation fd4e5731-cdc1-4c16-adc7-c414c16a397f · inbound

Self-Attention as a Covariance Readout: A Unified View of In-Context Learning and Repetition cites this paper.

Self-Attention as a Covariance Readout: A Unified View of In-Context Learning and Repetition Neural Text Generation with Unlikelihood Training

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-12T06:46:29.488804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 46cd232d-d897-4723-a869-b7ff49898b6c · inbound

SOMA: Efficient Multi-turn LLM Serving via Small Language Model cites this paper.

SOMA: Efficient Multi-turn LLM Serving via Small Language Model Neural Text Generation with Unlikelihood Training

Reference 49

Resolution: verified exact; arxiv_id, observed 2026-05-13T01:42:04.262872Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation fc5257cb-2a25-448f-97c2-9fad8d5b5759 · inbound

Asking Back: Interaction-Layer Antidistillation Watermarks cites this paper.

Asking Back: Interaction-Layer Antidistillation Watermarks Neural Text Generation with Unlikelihood Training

Reference 40

Resolution: verified exact; arxiv_id, observed 2026-05-20T18:13:37.544601Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 421645f1-8c4f-4f5e-ae2a-4734beba09e2 · inbound

CLORE: Content-Level Optimization for Reasoning Efficiency cites this paper.

CLORE: Content-Level Optimization for Reasoning Efficiency Neural Text Generation with Unlikelihood Training

Reference 47

Resolution: verified exact; arxiv_id, observed 2026-05-22T05:51:08.106790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 71df3d1d-1390-4b58-bf11-4d841904de37 · inbound

AMix-2: Establishing Protein as a Native Modality in Large Language Models cites this paper.

AMix-2: Establishing Protein as a Native Modality in Large Language Models Neural Text Generation with Unlikelihood Training

Reference 69

Resolution: verified exact; arxiv_id, observed 2026-06-28T20:12:37.772843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e2a7de01-2aeb-48c9-b1a5-6bd15dc055e1 · inbound

Seeing the Hivemind: A Consensus-Aware Interaction Technique for Mitigating AI Homogenization cites this paper.

Seeing the Hivemind: A Consensus-Aware Interaction Technique for Mitigating AI Homogenization Neural Text Generation with Unlikelihood Training

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-07-03T03:37:35.947111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 033f5f21-3979-425f-98f5-f42c7521ea91 · inbound

Brevity is the Soul of Inference Efficiency: Inducing Concision in VLMs via Data Curation cites this paper.

Brevity is the Soul of Inference Efficiency: Inducing Concision in VLMs via Data Curation Neural Text Generation with Unlikelihood Training

Reference 56

Resolution: verified exact; arxiv_id, observed 2026-07-04T19:40:07.175970Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation cb53792a-9591-4018-8b55-523eeede3c9a · inbound

Brevity is the Soul of Inference Efficiency: Inducing Concision in VLMs via Data Curation cites this paper.

Brevity is the Soul of Inference Efficiency: Inducing Concision in VLMs via Data Curation Neural Text Generation with Unlikelihood Training

Reference 55

Resolution: verified exact; arxiv_id, observed 2026-07-01T09:35:39.593537Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 9f5819d0-170d-4072-81db-f5a8abed1e35 · inbound

Mitigating Package Hallucinations in Large Language Models via Model Editing cites this paper.

Mitigating Package Hallucinations in Large Language Models via Model Editing Neural Text Generation with Unlikelihood Training

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-07-03T08:57:47.298927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation bfb19622-cd95-4af0-a83a-c164290a885c · inbound

MentalThink: Shaping Thoughts in Mental SVG World cites this paper.

MentalThink: Shaping Thoughts in Mental SVG World Neural Text Generation with Unlikelihood Training

Reference 242

Resolution: unresolved; no resolver link, observed 2026-07-12T01:50:59.184754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b2c42370-35df-4c45-94cc-4cc272e3d3d0 · inbound

LP-SFT: Local-Preserving Supervised Fine-Tuning via Multimodal Entropy Structure cites this paper.

LP-SFT: Local-Preserving Supervised Fine-Tuning via Multimodal Entropy Structure Neural Text Generation with Unlikelihood Training

Reference 21

Resolution: unresolved; no resolver link, observed 2026-07-11T14:23:31.109787Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b8f00bbc-86a1-4398-906c-23b5739303d6 · inbound

LP-SFT: Local-Preserving Supervised Fine-Tuning via Multimodal Entropy Structure cites this paper.

LP-SFT: Local-Preserving Supervised Fine-Tuning via Multimodal Entropy Structure Neural Text Generation with Unlikelihood Training

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-02T08:38:37.781693Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 77cfbb00-f862-4196-adfc-dc88b6390736 · inbound

Token-Level Off-Policy Learning for Faithful Generation Under Distribution Shift cites this paper.

Token-Level Off-Policy Learning for Faithful Generation Under Distribution Shift Neural Text Generation with Unlikelihood Training

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-01T17:47:42.511417Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 157afa55-0b54-448c-bc60-f3703568036b · inbound

Between Suppression and Collapse: Evaluating Narrative Unlearning with LENS cites this paper.

Between Suppression and Collapse: Evaluating Narrative Unlearning with LENS Neural Text Generation with Unlikelihood Training

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-02T09:46:58.789149Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 579802b6-8b4c-4597-ad9e-7114a2e88dcc · inbound

Between Suppression and Collapse: Evaluating Narrative Unlearning with LENS cites this paper.

Between Suppression and Collapse: Evaluating Narrative Unlearning with LENS Neural Text Generation with Unlikelihood Training

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-03T02:07:32.345073Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3c8182a4-d9b0-452a-9499-e701db41df60 · inbound

Bayesian Repetition Penalty: A Principled Adjacent-Conditional Framework for Reversing Attention Collapse in Autoregressive Language Models cites this paper.

Bayesian Repetition Penalty: A Principled Adjacent-Conditional Framework for Reversing Attention Collapse in Autoregressive Language Models Neural Text Generation with Unlikelihood Training

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-01T21:23:34.561927Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.