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Paper Citation Record · LEDGER

Anticipating Safety Issues in E2E Conversational AI: Framework and Tooling

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2107.03451.

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

pith.paper-citation-record.v1
2107.03451 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:21:58.636063Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T03:17:32.369632Z

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 432d88f3-b3c5-4fe4-9270-cb89f3520045 · inbound

Ethical and social risks of harm from Language Models cites this paper.

Ethical and social risks of harm from Language Models Anticipating Safety Issues in E2E Conversational AI: Framework and Tooling

Reference 66

Resolution
verified exact
arxiv_id, observed 2026-05-11T18:24:30.136566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-05-11T18:24:28.835688Z digest=sha256:7219639c52b736cbef046f207e7327e31a25cb0eb97cbf16fb27b1cbe2d18088

Observation 4ccabe67-8715-47d2-8ce4-7589c71d2d31 · inbound

LaMDA: Language Models for Dialog Applications cites this paper.

LaMDA: Language Models for Dialog Applications Anticipating Safety Issues in E2E Conversational AI: Framework and Tooling

Reference 53

Resolution
verified exact
arxiv_id, observed 2026-05-12T03:17:32.372498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-12T03:17:32.272353Z digest=sha256:0f6f64c6bba67f03ca79f6b73ae7c694a57db50ed3858718b7ad11a3f3e35986

Observation e253363c-9d25-4071-a351-552356a8afa8 · inbound

Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned cites this paper.

Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned Anticipating Safety Issues in E2E Conversational AI: Framework and Tooling

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-05-12T01:38:08.482200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-12T01:38:08.362920Z digest=sha256:90f1085cbefabf27c108a77ee14d6858abdec4a9f0f0648ae286809bdc2620c1

Observation e182abdc-9e22-47b8-9852-ac3d6f0eb28d · inbound

Reinforcement Learning from Human Feedback with High-Confidence Safety Constraints cites this paper.

Reinforcement Learning from Human Feedback with High-Confidence Safety Constraints Anticipating Safety Issues in E2E Conversational AI: Framework and Tooling

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-07T05:21:58.636063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:21:58.636063Z digest=sha256:ff70fd12bc05923bd6dd65348d291ccb896859bc5417fa8a744ada3ab60b58c4

Observation 779b986d-ceb5-4c6e-bc6a-45aa7984ce34 · inbound

Whose View of Safety? A Deep DIVE Dataset for Pluralistic Alignment of Text-to-Image Models cites this paper.

Whose View of Safety? A Deep DIVE Dataset for Pluralistic Alignment of Text-to-Image Models Anticipating Safety Issues in E2E Conversational AI: Framework and Tooling

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-06T17:08:14.521441Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:08:14.521441Z digest=sha256:209968c7ed764c0d30aae90672b8d511606279fe73b67b60444e6be70dcdd2a8

Observation c5aecd7d-65bd-48b3-ab38-abb4810f133a · inbound

Safe Inference-Time Alignment via Lagrangian Reward Augmentation cites this paper.

Safe Inference-Time Alignment via Lagrangian Reward Augmentation Anticipating Safety Issues in E2E Conversational AI: Framework and Tooling

Reference 100

Resolution
unresolved
no resolver link, observed 2026-07-12T07:05:47.150308Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T07:05:47.150308Z digest=sha256:b7732e9c7986f1c15ead48c7f7fe867750d9a4198808a84cc5b9d627f55b4239