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Paper Citation Record · LEDGER

I Think, Therefore I am: Benchmarking Awareness of Large Language Models Using AwareBench

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2401.17882.

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

pith.paper-citation-record.v1
2401.17882 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:19:51.087053Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T09:59:44.696863Z

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 321fc81e-8712-446d-93af-2f0ad347d767 · inbound

Large language models for artificial general intelligence (AGI): A survey of foundational principles and approaches cites this paper.

Large language models for artificial general intelligence (AGI): A survey of foundational principles and approaches I Think, Therefore I am: Benchmarking Awareness of Large Language Models Using AwareBench

Reference 154

Resolution
unresolved
no resolver link, observed 2026-08-10T21:56:12.574238Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:56:12.574238Z digest=sha256:9858e5588fcab037cbe6339476fef36769cfe8b18f6bc75f1398e64a5de10e1d

Observation 2f8217fe-d694-42ef-89ed-fdea0efa7ddd · inbound

AI Awareness cites this paper.

AI Awareness I Think, Therefore I am: Benchmarking Awareness of Large Language Models Using AwareBench

Reference 158

Resolution
unresolved
no resolver link, observed 2026-08-16T10:19:51.087053Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:19:51.087053Z digest=sha256:55ac9bf4ee1342bcf40c9ddaf593e4251b7d74810af48bb93a10d1bf652967d6

Observation 1814f7a2-bf6f-418c-8c18-2b90ea161c3e · inbound

Agents Require Metacognitive and Strategic Reasoning to Succeed in the Coming Labor Markets cites this paper.

Agents Require Metacognitive and Strategic Reasoning to Succeed in the Coming Labor Markets I Think, Therefore I am: Benchmarking Awareness of Large Language Models Using AwareBench

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-07T14:02:21.006903Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:02:21.006903Z digest=sha256:7afa8f91a84e702a03fd3e083208020b806e699061b2cc97a3d608369ada6073

Observation ba3a48cd-c8d5-4c2c-a5b6-45fde16add6b · inbound

Truly Self-Improving Agents Require Intrinsic Metacognitive Learning cites this paper.

Truly Self-Improving Agents Require Intrinsic Metacognitive Learning I Think, Therefore I am: Benchmarking Awareness of Large Language Models Using AwareBench

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-07T10:28:20.658807Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:28:20.658807Z digest=sha256:19fb6c6c13be2d704258a5f92d33b1547c70e1046b145dc28c874d6f06313799

Observation aefbd018-7f2d-4e21-a74b-e26d9195f1b9 · inbound

Domain Specific Benchmarks for Evaluating Multimodal Large Language Models cites this paper.

Domain Specific Benchmarks for Evaluating Multimodal Large Language Models I Think, Therefore I am: Benchmarking Awareness of Large Language Models Using AwareBench

Reference 135

Resolution
unresolved
no resolver link, observed 2026-08-07T00:39:42.144625Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:39:42.144625Z digest=sha256:f1faf47144557f6942e26a1e11130a94712a2306457f59aa0b58cbe44a59b046

Observation de5a92b4-f639-4ba0-8086-4247c877ddae · inbound

Self-Critique-Guided Curiosity Refinement: Enhancing Honesty and Helpfulness in Large Language Models via In-Context Learning cites this paper.

Self-Critique-Guided Curiosity Refinement: Enhancing Honesty and Helpfulness in Large Language Models via In-Context Learning I Think, Therefore I am: Benchmarking Awareness of Large Language Models Using AwareBench

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-06T23:49:26.402742Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:49:26.402742Z digest=sha256:d409d3a75dd7d64da9699dbfe5422b4d01273823f506027dd3bd27473599362e

Observation 377ba697-8220-4d83-9192-a9e18d34e16b · inbound

Fragile Thoughts: How Large Language Models Handle Chain-of-Thought Perturbations cites this paper.

Fragile Thoughts: How Large Language Models Handle Chain-of-Thought Perturbations I Think, Therefore I am: Benchmarking Awareness of Large Language Models Using AwareBench

Reference 32

Resolution
verified exact
arxiv_id, observed 2026-05-16T03:47:15.235544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-16T03:43:18.987241Z digest=sha256:b5244fe56b4457eaecb5f3b38d26f23e52f587f8db1baaf9382f2d8bb0a07a0d

Observation ff15f7ff-a51a-4606-bede-b8d8d59d12db · inbound

Decomposing and Steering Functional Metacognition in Large Language Models cites this paper.

Decomposing and Steering Functional Metacognition in Large Language Models I Think, Therefore I am: Benchmarking Awareness of Large Language Models Using AwareBench

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-05-12T03:01:18.858226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-12T02:57:09.180530Z digest=sha256:c39059ef7581fbc3194442236368108a31fe959dd75e9086e6e513482d6d2c65

Observation 8126cef3-c67f-4fa3-88b7-87763c0f24d5 · inbound

SingGuard: A Policy-Adaptive Multimodal LLM Guardrail with Dynamic Reasoning cites this paper.

SingGuard: A Policy-Adaptive Multimodal LLM Guardrail with Dynamic Reasoning I Think, Therefore I am: Benchmarking Awareness of Large Language Models Using AwareBench

Reference 221

Resolution
verified exact
arxiv_id, observed 2026-07-04T09:59:44.698346Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-06-26T09:19:50.623741Z digest=sha256:ef97679f121bf23ea0bdf685e89237a8fb92089e0a1288620063934419577448

Observation 3bd8a84f-0db7-46c7-809d-eab5890ff217 · inbound

SingGuard: A Policy-Adaptive Multimodal LLM Guardrail with Dynamic Reasoning cites this paper.

SingGuard: A Policy-Adaptive Multimodal LLM Guardrail with Dynamic Reasoning I Think, Therefore I am: Benchmarking Awareness of Large Language Models Using AwareBench

Reference 220

Resolution
verified exact
arxiv_id, observed 2026-07-01T18:55:59.621463Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-06-29T01:18:19.195007Z digest=sha256:2add332870d45342ddddd107b3827cb06b3393d8c9abc5fbde84ad63b27c7d6a

Observation 2703bcca-d960-490c-a58b-06d803421d62 · inbound

Chain-of-Models: Cross-Model Auditing for Bias-Robust LLM Judges cites this paper.

Chain-of-Models: Cross-Model Auditing for Bias-Robust LLM Judges I Think, Therefore I am: Benchmarking Awareness of Large Language Models Using AwareBench

Reference 88

Resolution
unresolved
no resolver link, observed 2026-08-03T00:55:26.876886Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T00:55:26.876886Z digest=sha256:421eae5c0642cbc020facf6ba4f093b63f7a933a0274cc2ad20db524db32d5d7