Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Clembench: Using Game Play to Evaluate Chat-Optimized Language Models as Conversational Agents
As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2305.13455.
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 2026-08-09T12:15:05.236457Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-03T10:58:02.993024Z
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 0cd16a9d-bd9d-4ad9-a402-0fa2c1bb5792 · inbound
A Survey on Large Language Model based Autonomous Agents cites this paper.
A Survey on Large Language Model based Autonomous Agents Clembench: Using Game Play to Evaluate Chat-Optimized Language Models as Conversational Agents
Reference 165
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T04:03:01.009343Z
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.
Observation 3ebbb4c2-02b4-4766-b7bb-fddb2c6c9ff2 · inbound
Dynamic benchmarking framework for LLM-based conversational data capture cites this paper.
Dynamic benchmarking framework for LLM-based conversational data capture Clembench: Using Game Play to Evaluate Chat-Optimized Language Models as Conversational Agents
Reference 2023
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T12:15:05.236457Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d7d556b7-a257-45bf-acf8-d6fd019ebcca · inbound
Agentic Environment Engineering for Large Language Models: A Survey of Environment Modeling, Synthesis, Evaluation, and Application cites this paper.
Agentic Environment Engineering for Large Language Models: A Survey of Environment Modeling, Synthesis, Evaluation, and Application Clembench: Using Game Play to Evaluate Chat-Optimized Language Models as Conversational Agents
Reference 105
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T10:58:02.994650Z
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.