Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Hybrid Code Networks: practical and efficient end-to-end dialog control with supervised and reinforcement learning
As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1702.03274.
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 2026-08-14T06:32:32.682623+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-14T11:31:41.315239Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-09T15:10:39.098201Z
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 1a6dadc5-4c4e-445a-97bb-32828fd73fc2 · inbound
Deep Learning Based Chatbot Models cites this paper.
Deep Learning Based Chatbot Models Hybrid Code Networks: practical and efficient end-to-end dialog control with supervised and reinforcement learning
Reference 112
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T11:31:41.315239Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ce304677-0367-4726-a184-aecd74b2a40d · inbound
How to Build User Simulators to Train RL-based Dialog Systems cites this paper.
How to Build User Simulators to Train RL-based Dialog Systems Hybrid Code Networks: practical and efficient end-to-end dialog control with supervised and reinforcement learning
Reference 42
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T05:23:46.559517Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 054dac79-5ce3-4e3c-8023-ddb7455b472f · inbound
Process-Supervised Reinforcement Learning for Code Generation cites this paper.
Process-Supervised Reinforcement Learning for Code Generation Hybrid Code Networks: practical and efficient end-to-end dialog control with supervised and reinforcement learning
Reference 46
- Resolution
- verified exact
- local_arxiv, observed 2026-08-09T15:10:39.104213Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.