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Paper Citation Record · LEDGER

Towards Benchmarking and Improving the Temporal Reasoning Capability of Large Language Models

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2306.08952.

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

pith.paper-citation-record.v1
2306.08952 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:47:15.798080Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T19:13:53.117583Z

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 c251b9f7-f9ca-43fe-b35f-5a38e669c87a · inbound

USTBench: Benchmarking and Dissecting Spatiotemporal Reasoning of LLMs as Urban Agents cites this paper.

USTBench: Benchmarking and Dissecting Spatiotemporal Reasoning of LLMs as Urban Agents Towards Benchmarking and Improving the Temporal Reasoning Capability of Large Language Models

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-07T14:47:15.798080Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:47:15.798080Z digest=sha256:6a0be7329ae169c94ea66fd1aa670ee7942540f6c0b86274dea3b996550f204d

Observation c5f5e0c8-c4f8-4afa-aa57-d465439c2fc3 · inbound

ExAnte: A Benchmark for Ex-Ante Inference in Large Language Models cites this paper.

ExAnte: A Benchmark for Ex-Ante Inference in Large Language Models Towards Benchmarking and Improving the Temporal Reasoning Capability of Large Language Models

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-07T14:17:09.966209Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:17:09.966209Z digest=sha256:ae6b9a5c98c441ee2bb70874679a6bbc1790cc777958d510d6e7b07c3c99b3bc

Observation 325538cb-e4b1-437b-94f5-1592e4f6cf6d · inbound

TempoBench: Evaluating Temporal Causal Reasoning in Large Language Models cites this paper.

TempoBench: Evaluating Temporal Causal Reasoning in Large Language Models Towards Benchmarking and Improving the Temporal Reasoning Capability of Large Language Models

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-04T07:01:42.227326Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T07:01:42.227326Z digest=sha256:8783472360077cc768bb2d5dcf39e3551b11b17598c5d1581e7b0e540a147549

Observation 216b4c58-b3ed-456f-b19b-bcadb3381aac · inbound

Temporal Reasoning Is Not the Bottleneck: A Probabilistic Inconsistency Framework for Neuro-Symbolic QA cites this paper.

Temporal Reasoning Is Not the Bottleneck: A Probabilistic Inconsistency Framework for Neuro-Symbolic QA Towards Benchmarking and Improving the Temporal Reasoning Capability of Large Language Models

Reference 80

Resolution
verified exact
arxiv_id, observed 2026-05-11T17:16:07.890653Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-08T17:45:44.270122Z digest=sha256:e33297bfbb20b5d90209c18ee3019d7ed39e52280861502c3cf8a80931173a85

Observation 6c8d4a49-3c3d-47e3-b4dd-977a673d21b0 · inbound

A Study of Temporal Fusion Strategies for Named Entity Recognition in Historical Texts cites this paper.

A Study of Temporal Fusion Strategies for Named Entity Recognition in Historical Texts Towards Benchmarking and Improving the Temporal Reasoning Capability of Large Language Models

Reference 35

Resolution
verified exact
arxiv_id, observed 2026-06-29T19:13:53.119924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-29T04:52:30.770882Z digest=sha256:f5e32a04028b973c64d65058e673ab7c1fef668983355b11d6d4cb9d161837bf