Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-14T15:26:08.014117Z
Paper Citation Record · LEDGER
Exploring the Robustness of NMT Systems to Nonsensical Inputs
As of 20 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 1 inbound Pith citation observation for arXiv:1908.01165.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-10T17:31:37.067067Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-10T17:31:37.332380Z
Reference resolution
17 of 17 outbound references displayed
- verified exact0
- verified fuzzy16
- unresolved1
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 65817ec1-7e2f-4231-b6bf-690216d62ed3 · outbound
This paper cites Attention is all you need,.
Exploring the Robustness of NMT Systems to Nonsensical Inputs Attention is all you need,
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T15:26:08.170685Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation e56c6248-f317-45b2-8b07-1f45c8a797af · outbound
This paper cites BERT: P re- training of deep bidirectional transformers for language u nderstanding,.
Exploring the Robustness of NMT Systems to Nonsensical Inputs BERT: P re- training of deep bidirectional transformers for language u nderstanding,
Reference 2
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T15:26:07.964312Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b644ada4-6040-4141-bd8c-e23e40e3a2b1 · outbound
This paper cites Pathologies of neural models make interpretation s difficult,.
Exploring the Robustness of NMT Systems to Nonsensical Inputs Pathologies of neural models make interpretation s difficult,
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T15:26:08.159127Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 34f432ee-22dd-41be-9f9b-8fdd1a1071a4 · outbound
This paper cites Hotflip: White-b ox adversarial examples for text classification,.
Exploring the Robustness of NMT Systems to Nonsensical Inputs Hotflip: White-b ox adversarial examples for text classification,
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T15:26:08.151608Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 6caf73e7-a994-42a7-b32d-43b3e75e07f9 · outbound
This paper cites Synthetic and natural noise bot h break neural machine translation,.
Exploring the Robustness of NMT Systems to Nonsensical Inputs Synthetic and natural noise bot h break neural machine translation,
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T15:26:08.143859Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation e2a1cab4-85eb-454c-9b31-06e1191085ff · outbound
This paper cites On adversarial example s for character-level neural machine translation,.
Exploring the Robustness of NMT Systems to Nonsensical Inputs On adversarial example s for character-level neural machine translation,
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T15:26:08.134799Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation a3107483-67ba-458e-83e5-0052089277fd · outbound
This paper cites Character-ba sed neural machine translation,.
Exploring the Robustness of NMT Systems to Nonsensical Inputs Character-ba sed neural machine translation,
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T15:26:08.127273Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation a81c8a63-455b-412a-987d-ae85686dd79a · outbound
This paper cites Towards robu st neural machine translation,.
Exploring the Robustness of NMT Systems to Nonsensical Inputs Towards robu st neural machine translation,
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T15:26:08.117347Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation b7b514aa-c3d6-4e97-862a-df31f241012e · outbound
This paper cites Robust neural machi ne transla- tion with doubly adversarial inputs,.
Exploring the Robustness of NMT Systems to Nonsensical Inputs Robust neural machi ne transla- tion with doubly adversarial inputs,
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T15:26:08.109580Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation d7a31d7d-0fa1-4c0f-81f7-f55b0c23de10 · outbound
This paper cites Effective approac hes to attention-based neural machine translation,.
Exploring the Robustness of NMT Systems to Nonsensical Inputs Effective approac hes to attention-based neural machine translation,
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T15:26:08.101302Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation f603abe2-b6f3-495c-9181-faeaa822693b · outbound
This paper cites Detecting egregious responses in ne ural sequence- to-sequence models,.
Exploring the Robustness of NMT Systems to Nonsensical Inputs Detecting egregious responses in ne ural sequence- to-sequence models,
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T15:26:08.091653Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 37819c3d-1fcd-46b4-878b-52c587362320 · outbound
This paper cites Robust neura l machine translation with joint textual and phonetic embedding,.
Exploring the Robustness of NMT Systems to Nonsensical Inputs Robust neura l machine translation with joint textual and phonetic embedding,
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T15:26:08.082649Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 7ed47344-79a1-4cce-a386-9d92d8531b56 · outbound
This paper cites When and why are pre-trained word embeddings useful for neural ma chine translation?.
Exploring the Robustness of NMT Systems to Nonsensical Inputs When and why are pre-trained word embeddings useful for neural ma chine translation?
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T15:26:08.074591Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 0cbdc4de-dbeb-4e48-a4e9-0cabb62085ab · outbound
This paper cites Parameter sharing methods for multilin- gual self-attentional translation models,.
Exploring the Robustness of NMT Systems to Nonsensical Inputs Parameter sharing methods for multilin- gual self-attentional translation models,
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T15:26:08.066055Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 191efe3a-4f87-4f88-898d-038f15b266da · outbound
This paper cites Neural machine tr anslation of rare words with subword units,.
Exploring the Robustness of NMT Systems to Nonsensical Inputs Neural machine tr anslation of rare words with subword units,
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T15:26:08.055589Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation c424e133-79b1-4a9e-8693-511f339ad5f7 · outbound
This paper cites Bleu: a m ethod for automatic evaluation of machine translation,.
Exploring the Robustness of NMT Systems to Nonsensical Inputs Bleu: a m ethod for automatic evaluation of machine translation,
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T15:26:08.047162Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 8f47d117-77cb-4dbb-b489-760a50bec02c · outbound
This paper cites Towards deep learning models resistant to adversarial attacks,.
Exploring the Robustness of NMT Systems to Nonsensical Inputs Towards deep learning models resistant to adversarial attacks,
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T15:26:08.038207Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Pith citing papers
Observation dc273f9f-2ab4-41f3-86fc-50d9263b7d9c · inbound
Extend Adversarial Policy Against Neural Machine Translation via Unknown Token cites this paper.
Extend Adversarial Policy Against Neural Machine Translation via Unknown Token Exploring the Robustness of NMT Systems to Nonsensical Inputs
Reference 3
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-10T17:31:37.336678Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.