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Paper Citation Record · LEDGER

Robots in the Middle: Evaluating LLMs in Dispute Resolution

As of 4 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2410.07053.

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

pith.paper-citation-record.v1
2410.07053 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-30T21:12:13.820489Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T12:16:57.620065Z

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 d844af6a-fa63-4de5-a5d1-f69634a30953 · inbound

Real-Time Group Dynamics with LLM Facilitation: Evidence from a Charity Allocation Task cites this paper.

Real-Time Group Dynamics with LLM Facilitation: Evidence from a Charity Allocation Task Robots in the Middle: Evaluating LLMs in Dispute Resolution

Reference 48

Resolution
verified exact
arxiv_id, observed 2026-05-15T01:53:29.039686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-15T01:50:34.234176Z digest=sha256:f96958b02c6f3315b2f5bde07d5d57c6c04eecbf0186d091734c09bac91cc007

Observation 5ad6e4cb-7c39-4829-a59e-a42784bda63c · inbound

Real-Time Group Dynamics with LLM Facilitation: Evidence from a Charity Allocation Task cites this paper.

Real-Time Group Dynamics with LLM Facilitation: Evidence from a Charity Allocation Task Robots in the Middle: Evaluating LLMs in Dispute Resolution

Reference 48

Resolution
verified exact
arxiv_id, observed 2026-06-30T21:15:04.258553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-06-30T21:12:13.820489Z digest=sha256:e2480bab45dc8d31ead2ac2280662e27cd72a4a78a4308371a27246c5760740c

Observation 7cae496a-7cb5-4099-84fd-77695ad090bd · inbound

SoCRATES: Towards Reliable Automated Evaluation of Proactive LLM Mediation across Domains and Socio-cognitive Variations cites this paper.

SoCRATES: Towards Reliable Automated Evaluation of Proactive LLM Mediation across Domains and Socio-cognitive Variations Robots in the Middle: Evaluating LLMs in Dispute Resolution

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-07-02T12:16:57.621953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-06-28T02:12:47.295439Z digest=sha256:789b0e2bbd73927ec6b2a86827429a739d8e153933d6d67cb3c2908419b10ade

Observation 3b2773e1-4768-41d7-96fa-9e0b9b210fd2 · inbound

Can You Trust What You See? Human and AI Detection of Synthetic Legal Evidence cites this paper.

Can You Trust What You See? Human and AI Detection of Synthetic Legal Evidence Robots in the Middle: Evaluating LLMs in Dispute Resolution

Reference 81

Resolution
verified exact
arxiv_id, observed 2026-07-01T19:16:00.633813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=arxiv_source observed=2026-06-28T22:55:00.904065Z digest=sha256:f38a7ea84f575e1be08833e36ce58f0e1918987b3c6902c382bdf93b0a1f9f53