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Paper Citation Record · LEDGER

NPHardEval: Dynamic Benchmark on Reasoning Ability of Large Language Models via Complexity Classes

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2312.14890.

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

pith.paper-citation-record.v1
2312.14890 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T14:51:15.383999Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T23:10:40.938077Z

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 b40b5125-ae74-438d-832d-2b808802dce9 · inbound

Benchmark Data Contamination of Large Language Models: A Survey cites this paper.

Benchmark Data Contamination of Large Language Models: A Survey NPHardEval: Dynamic Benchmark on Reasoning Ability of Large Language Models via Complexity Classes

Reference 44

Resolution
verified exact
arxiv_id, observed 2026-05-22T23:10:40.940622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-22T23:10:40.420241Z digest=sha256:70978a27445f3e315f5aebcc16844e9dd453a60767c7adf2bce78565710566b6

Observation fc4c9d7f-1845-4048-833c-52fbfdf98479 · inbound

Unbiased Evaluation of Large Language Models from a Causal Perspective cites this paper.

Unbiased Evaluation of Large Language Models from a Causal Perspective NPHardEval: Dynamic Benchmark on Reasoning Ability of Large Language Models via Complexity Classes

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-08T14:51:15.383999Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T14:51:15.383999Z digest=sha256:6df0f5cf84da92f909a66ae201119f9f3056f54efbc0d0d187645c7cc381b97f

Observation 145fe6b8-60a8-4bd3-a933-6aa0a5eaad46 · inbound

Reasoning Multimodal Large Language Model: Data Contamination and Dynamic Evaluation cites this paper.

Reasoning Multimodal Large Language Model: Data Contamination and Dynamic Evaluation NPHardEval: Dynamic Benchmark on Reasoning Ability of Large Language Models via Complexity Classes

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-07T05:43:39.255176Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:43:39.255176Z digest=sha256:0e0a602b5864ee985e3bec797c3ef0a85f0c44fca12527786edb60de17804a7e

Observation ab83d070-3c04-44dc-b9e6-6c70cba195da · inbound

LogiPlan: A Structured Benchmark for Logical Planning and Relational Reasoning in LLMs cites this paper.

LogiPlan: A Structured Benchmark for Logical Planning and Relational Reasoning in LLMs NPHardEval: Dynamic Benchmark on Reasoning Ability of Large Language Models via Complexity Classes

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-07T04:28:40.881171Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T04:28:40.881171Z digest=sha256:388844cf44d563168ea270f550573a16c1ca9eefb7837d22c28a66ec2ecc9bf4

Observation 54c5a251-52c7-496e-97db-ec3ed7ebaf2d · inbound

OPT-BENCH: Evaluating LLM Agent on Large-Scale Search Spaces Optimization Problems cites this paper.

OPT-BENCH: Evaluating LLM Agent on Large-Scale Search Spaces Optimization Problems NPHardEval: Dynamic Benchmark on Reasoning Ability of Large Language Models via Complexity Classes

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-07T04:23:50.574907Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:23:50.574907Z digest=sha256:0ab3c4588fb942b7a0945f64b82c0aa9b80951cfbf03012eeac1a99873fca6aa

Observation e246aa72-431c-45c7-9abf-971d75dd7ba9 · inbound

Integrating LLMs and Digital Twins for Adaptive Multi-Robot Task Allocation in Construction cites this paper.

Integrating LLMs and Digital Twins for Adaptive Multi-Robot Task Allocation in Construction NPHardEval: Dynamic Benchmark on Reasoning Ability of Large Language Models via Complexity Classes

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-06T23:27:54.627307Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:27:54.627307Z digest=sha256:637d2d7b8e5007d679ab8bc590c43e70a382791ffc843630baafa1ec14898e42

Observation 853e4453-753f-4fbd-8832-3fb5fb32b6d8 · inbound

From Long to Short: LLMs Excel at Trimming Own Reasoning Chains cites this paper.

From Long to Short: LLMs Excel at Trimming Own Reasoning Chains NPHardEval: Dynamic Benchmark on Reasoning Ability of Large Language Models via Complexity Classes

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-05T00:03:58.509677Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T00:03:58.509677Z digest=sha256:4c9c5c781a66801d16f50b4bc8c73aad81c6f2bfbfeb90d511a7bbe3f1750a68

Observation 2a023073-a666-49df-bd67-f5a2d60efaf8 · inbound

OPT-BENCH: Evaluating the Iterative Self-Optimization of LLM Agents in Large-Scale Search Spaces cites this paper.

OPT-BENCH: Evaluating the Iterative Self-Optimization of LLM Agents in Large-Scale Search Spaces NPHardEval: Dynamic Benchmark on Reasoning Ability of Large Language Models via Complexity Classes

Reference 132

Resolution
verified exact
arxiv_id, observed 2026-05-12T03:01:18.635644Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-12T02:57:15.521594Z digest=sha256:227c2ad7a26aeee4acd28e103ad7c629a6e9f6fc42706fdd42124ea507ba4b85