Paper Citation Record · LEDGER

Multi-Task Deep Neural Networks for Natural Language Understanding

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 19 inbound Pith citation observations for arXiv:1901.11504.

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

pith.paper-citation-record.v1
1901.11504 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 19 of 19 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T15:15:56.290610Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-04T12:49:51.909964Z

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 ee180364-d549-4a63-ad7e-10dc78b1743c · inbound

SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems cites this paper.

SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems Multi-Task Deep Neural Networks for Natural Language Understanding

Reference 120

Resolution: verified exact; local_arxiv, observed 2026-05-15T01:34:10.757651Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 6b5cdbdd-0d9d-4ea8-8a33-2ce8808b8fdc · inbound

XLNet: Generalized Autoregressive Pretraining for Language Understanding cites this paper.

XLNet: Generalized Autoregressive Pretraining for Language Understanding Multi-Task Deep Neural Networks for Natural Language Understanding

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-05-18T01:29:27.509639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 95bca717-14c1-4527-823f-4bb7e395acbe · inbound

To Tune or Not To Tune? How About the Best of Both Worlds? cites this paper.

To Tune or Not To Tune? How About the Best of Both Worlds? Multi-Task Deep Neural Networks for Natural Language Understanding

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-05-25T00:46:30.622943Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation a30af3ea-b967-4c99-b6a9-64bc633b8514 · inbound

RoBERTa: A Robustly Optimized BERT Pretraining Approach cites this paper.

RoBERTa: A Robustly Optimized BERT Pretraining Approach Multi-Task Deep Neural Networks for Natural Language Understanding

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-05-09T04:47:44.425009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 1755b56c-2157-4548-a092-a5ac8c2c3a2b · inbound

Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism cites this paper.

Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism Multi-Task Deep Neural Networks for Natural Language Understanding

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-10T18:34:44.858886Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 47ddca43-2e1d-4944-9785-3779654ae4d3 · inbound

Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer cites this paper.

Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer Multi-Task Deep Neural Networks for Natural Language Understanding

Reference 46

Resolution: verified exact; arxiv_id, observed 2026-05-12T05:37:55.800230Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 32194952-edc2-40fb-b1ef-1b69cc58c07f · inbound

Language Models are Few-Shot Learners cites this paper.

Language Models are Few-Shot Learners Multi-Task Deep Neural Networks for Natural Language Understanding

Reference 40

Resolution: verified exact; arxiv_id, observed 2026-05-10T12:05:38.291430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation bc14eb0b-5cdc-44a2-92a6-3bdaf5057ae6 · inbound

OPT: Open Pre-trained Transformer Language Models cites this paper.

OPT: Open Pre-trained Transformer Language Models Multi-Task Deep Neural Networks for Natural Language Understanding

Reference 81

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T20:53:17.390694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation acbf9965-271a-4de6-adf2-7467dd86134a · inbound

IterIS: Iterative Inference-Solving Alignment for LoRA Merging cites this paper.

IterIS: Iterative Inference-Solving Alignment for LoRA Merging Multi-Task Deep Neural Networks for Natural Language Understanding

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-12T15:15:56.290610Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5bbc6500-41bd-440b-87ee-34559a81b19b · inbound

Dynamic Self-Distillation via Previous Mini-batches for Fine-tuning Small Language Models cites this paper.

Dynamic Self-Distillation via Previous Mini-batches for Fine-tuning Small Language Models Multi-Task Deep Neural Networks for Natural Language Understanding

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-12T12:45:20.012458Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 13f1340b-b94e-4887-bf6f-b5f68ba93cc5 · inbound

LLMs are Also Effective Embedding Models: An In-depth Overview cites this paper.

LLMs are Also Effective Embedding Models: An In-depth Overview Multi-Task Deep Neural Networks for Natural Language Understanding

Reference 91

Resolution: unresolved; no resolver link, observed 2026-08-11T13:59:01.757855Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5925b884-372b-48bf-ab6a-62aecb4a40a5 · inbound

Tougher Text, Smarter Models: Raising the Bar for Adversarial Defence Benchmarks cites this paper.

Tougher Text, Smarter Models: Raising the Bar for Adversarial Defence Benchmarks Multi-Task Deep Neural Networks for Natural Language Understanding

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-10T22:12:49.983571Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b376b492-8d80-4f8d-ab6f-0c4c9a0675b9 · inbound

A Survey on Large Language Models with some Insights on their Capabilities and Limitations cites this paper.

A Survey on Large Language Models with some Insights on their Capabilities and Limitations Multi-Task Deep Neural Networks for Natural Language Understanding

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-10T22:17:55.648966Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 61074ac1-edc3-4e83-9567-321dfa50f885 · inbound

Efficiently Integrate Large Language Models with Visual Perception: A Survey from the Training Paradigm Perspective cites this paper.

Efficiently Integrate Large Language Models with Visual Perception: A Survey from the Training Paradigm Perspective Multi-Task Deep Neural Networks for Natural Language Understanding

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-09T15:04:40.108448Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0f5ff7bc-e362-4451-ad1d-a7f9cf62e3c7 · inbound

PiKE: Adaptive Data Mixing for Large-Scale Multi-Task Learning Under Low Gradient Conflicts cites this paper.

PiKE: Adaptive Data Mixing for Large-Scale Multi-Task Learning Under Low Gradient Conflicts Multi-Task Deep Neural Networks for Natural Language Understanding

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-08T16:20:38.287083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 372a565e-e29c-4466-a46d-58c3345b0360 · inbound

CLaC at SemEval-2025 Task 6: A Multi-Architecture Approach for Corporate Environmental Promise Verification cites this paper.

CLaC at SemEval-2025 Task 6: A Multi-Architecture Approach for Corporate Environmental Promise Verification Multi-Task Deep Neural Networks for Natural Language Understanding

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T12:47:01.912278Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6f08d134-1994-4838-a5ac-68bccb243035 · inbound

ROBAD: Robust Adversary-aware Local-Global Attended Bad Actor Detection Sequential Model cites this paper.

ROBAD: Robust Adversary-aware Local-Global Attended Bad Actor Detection Sequential Model Multi-Task Deep Neural Networks for Natural Language Understanding

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-06T15:46:44.815620Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d21e5e55-b7cb-4f46-b666-6e605b1fc57a · inbound

Federated User Behavior Modeling for Privacy-Preserving LLM Recommendation cites this paper.

Federated User Behavior Modeling for Privacy-Preserving LLM Recommendation Multi-Task Deep Neural Networks for Natural Language Understanding

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-10T10:09:06.474792Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation a5be81ac-1507-4435-b93f-2dc5fc785298 · inbound

Unified Multi-Task Relevance Modeling for E-Commerce: Comparing Task Routing Architectures Across LLMs and Cross-Encoders cites this paper.

Unified Multi-Task Relevance Modeling for E-Commerce: Comparing Task Routing Architectures Across LLMs and Cross-Encoders Multi-Task Deep Neural Networks for Natural Language Understanding

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-07-04T12:49:51.911159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.