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Paper Citation Record · LEDGER

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models

As of 9 August 2026, this Paper Citation Record lists 97 of 97 outbound references and 0 inbound Pith citation observations for arXiv:2507.00092.

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

pith.paper-citation-record.v1
2507.00092 v1

Coverage vector

measured 97 of 97 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:38:18.903822Z

measured 97 of 97 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Source: cited_works

Reference resolution

97 of 97 outbound references displayed

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Outbound references

Observation dbc692e6-dc34-4d37-92b6-899daf8929c4 · outbound

This paper cites Tracing the thoughts of a large language model.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Tracing the thoughts of a large language model

Reference 1

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Observation 94608b0a-35a6-4bb1-a986-58d0c1b4e034 · outbound

This paper cites Meta-Models: An Architecture for Decoding LLM Behaviors Through Interpreted Embeddings and Natural Language.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Meta-Models: An Architecture for Decoding LLM Behaviors Through Interpreted Embeddings and Natural Language

Reference 2

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Observation 6ce28c04-ea46-4255-8d9d-f813e21a7006 · outbound

This paper cites A Mechanistic Analysis of a Transformer Trained on a Symbolic Multi-Step Reasoning Task.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models A Mechanistic Analysis of a Transformer Trained on a Symbolic Multi-Step Reasoning Task

Reference 3

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Observation 129bbd78-5bb5-4b2f-bec3-2b58744f0db9 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 4

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Observation f9bce19d-1ceb-4f0d-bfa2-0ad00b9015fb · outbound

This paper cites an unresolved cited work.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Unresolved cited work

Reference 5

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Observation 3bf59554-1e1c-4d7f-ba84-e75ad68ec92c · outbound

This paper cites Singh and others.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Singh and others

Reference 6

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Observation 31f7b10c-ed4c-41e4-9cec-4673810b06af · outbound

This paper cites Brown and others.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Brown and others

Reference 7

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Observation 9c22f8ff-ae9b-4604-8ba6-caf06ad8ec74 · outbound

This paper cites an unresolved cited work.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Unresolved cited work

Reference 8

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Observation 5a204019-88a5-46ce-8cbe-1c584a4928db · outbound

This paper cites Jain and B.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Jain and B

Reference 9

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Observation a456f4e6-8fb3-4d2d-bec6-d445898d58b7 · outbound

This paper cites Elhage and others.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Elhage and others

Reference 10

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Observation 5cd748e7-07e4-4b78-aed0-da62b6bd6559 · outbound

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Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Lightman and others

Reference 11

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Observation 9533d97c-dd82-4502-95d5-306d25587841 · outbound

This paper cites Singh and others.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Singh and others

Reference 12

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Observation a20558ac-467a-413f-b164-18535bba607d · outbound

This paper cites Meng and others.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Meng and others

Reference 13

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Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Unresolved cited work

Reference 14

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Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Chain-of-thought prompting elicits reasoning in large language models

Reference 15

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Observation 1a31290d-d8e4-4989-8415-712a6b619dac · outbound

This paper cites A primer in BERTology: What we know about how BERT works.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models A primer in BERTology: What we know about how BERT works

Reference 16

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Observation eefa2681-81f3-4678-982c-fec6859b2283 · outbound

This paper cites What Does BERT Look At? An Analysis of BERT's Attention.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models What Does BERT Look At? An Analysis of BERT's Attention

Reference 17

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Observation e1bd1e25-b477-4be2-b9eb-ec3dcc899284 · outbound

This paper cites Large language models are zero-shot reasoners.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Large language models are zero-shot reasoners

Reference 18

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Observation d324cbff-0351-417e-a3ca-9e288963ac88 · outbound

This paper cites Tree of thoughts: Deliberate problem solving with large language models.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Tree of thoughts: Deliberate problem solving with large language models

Reference 20

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Observation 4e413e82-7cb1-42f9-afe9-30b3fdd5a31c · outbound

This paper cites Neural Machine Translation by Jointly Learning to Align and Translate.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Neural Machine Translation by Jointly Learning to Align and Translate

Reference 21

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Observation c06f0942-6145-48c9-a379-c1486a0e7fdd · outbound

This paper cites Attention is all you need.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Attention is all you need

Reference 22

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Observation 3cb18fbc-0903-4d6e-ada6-0a30085d31ab · outbound

This paper cites Attention is not not Explanation.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Attention is not not Explanation

Reference 23

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Observation ba227c8f-5550-4900-857d-97593e4f7413 · outbound

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Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Zoom in: An introduction to circuits

Reference 24

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This paper cites Network dissection: Quantifying interpretability of deep visual represen- tations.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Network dissection: Quantifying interpretability of deep visual represen- tations

Reference 25

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This paper cites Causal Mediation Analysis for Interpreting Neural NLP: The Case of Gender Bias.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Causal Mediation Analysis for Interpreting Neural NLP: The Case of Gender Bias

Reference 26

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Observation a963e12f-d631-407a-a938-b3f31f251dae · outbound

This paper cites Building machines that learn and think like people.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Building machines that learn and think like people

Reference 27

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Observation f8007a1a-1a02-49d7-a7ad-84a74ee1bd79 · outbound

This paper cites Model-agnostic meta-learning for fast adaptation of deep networks.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Model-agnostic meta-learning for fast adaptation of deep networks

Reference 28

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Observation 908fc2ce-184f-4d3e-8fab-73ff0622217b · outbound

This paper cites Metacognition and cognitive monitoring: A new area of cognitive–developmental inquiry.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Metacognition and cognitive monitoring: A new area of cognitive–developmental inquiry

Reference 29

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Observation a0aa777b-7a65-45ff-8984-fdad6ddc7278 · outbound

This paper cites A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks

Reference 30

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Observation 713fc596-84d6-40cb-80fd-0bacbd99a917 · outbound

This paper cites Dropout as a bayesian approximation: Representing model uncertainty in deep learning.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Dropout as a bayesian approximation: Representing model uncertainty in deep learning

Reference 31

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Observation 22b6afcf-28b2-4776-993b-1d33cbc595cf · outbound

This paper cites Reflexion: Language agents with verbal reinforcement learning.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Reflexion: Language agents with verbal reinforcement learning

Reference 32

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Observation 14f94fdb-bd05-40e0-86cb-284b5c87955a · outbound

This paper cites Program induction by rationale generation: Learning to solve and explain algebraic word problems.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Program induction by rationale generation: Learning to solve and explain algebraic word problems

Reference 33

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Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Training Verifiers to Solve Math Word Problems

Reference 34

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Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Measuring Mathematical Problem Solving With the MATH Dataset

Reference 35

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Observation 81739dc0-be09-4e6f-b047-d8351871d992 · outbound

This paper cites LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 36

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Observation 84ece5cd-d8cc-49d6-a9c8-3746a51c2c5c · outbound

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Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models ReClor: A Reading Comprehension Dataset Requiring Logical Reasoning

Reference 37

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Observation a21ab4f1-d809-4dd7-993e-b9eb4f28087d · outbound

This paper cites ProofWriter: Generating Implications, Proofs, and Abductive Statements over Natural Language.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models ProofWriter: Generating Implications, Proofs, and Abductive Statements over Natural Language

Reference 38

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source=pdf_text observed=2026-08-06T21:38:12.584725Z digest=sha256:5a8fc3b83a3ae5ca94aa364d72f5e4bd74e8c1d2ef2093aa6379fc3e1d87ae49

Observation 7c7c37a8-83ef-4422-98ad-9cb6f5a70f2e · outbound

This paper cites CommonsenseQA: A Question Answering Challenge Targeting Commonsense Knowledge.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models CommonsenseQA: A Question Answering Challenge Targeting Commonsense Knowledge

Reference 39

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Observation 1fa1e29f-8ef5-45e2-ae9e-20980d66ceba · outbound

This paper cites Did aristotle use a laptop? a question answering benchmark with implicit reasoning strategies.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Did aristotle use a laptop? a question answering benchmark with implicit reasoning strategies

Reference 40

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source=pdf_text observed=2026-08-06T21:38:12.790260Z digest=sha256:ae5ea8bb44ecfd9f2c81917d0f8a66320c46f736bac0ba837363081384c8bf76

Observation bf586b85-3d92-4c70-a32c-cb11f83dbbcf · outbound

This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 41

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source=pdf_text observed=2026-08-06T21:38:12.874493Z digest=sha256:3cd5ea61fc4a2fe72016575a9094eb6b895361f3cc300517b3dc6e333ba5bd7f

Observation 4a1b6b1b-29af-4437-ba6f-9a5c7561c8b2 · outbound

This paper cites Aligning AI With Shared Human Values.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Aligning AI With Shared Human Values

Reference 42

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Observation f72eb595-9bdc-463e-8cbb-e2b0a889db43 · outbound

This paper cites Moral Stories: Situated Reasoning about Norms, Intents, Actions, and their Consequences.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Moral Stories: Situated Reasoning about Norms, Intents, Actions, and their Consequences

Reference 43

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source=pdf_text observed=2026-08-06T21:38:13.031082Z digest=sha256:6ee9ff769d94d2f5dc3ed976e07f115ab87fdd2d5d1e2cee053564ca6c260cce

Observation ce5ad1c4-e6ee-445f-b143-3701ddc878bc · outbound

This paper cites Why should i trust you? explaining the predictions of any classi- fier.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Why should i trust you? explaining the predictions of any classi- fier

Reference 44

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source=pdf_text observed=2026-08-06T21:38:13.125246Z digest=sha256:50ed1122c1b918bdf7acff187d27ad382e8d0c434922652ec832ef71976fa8b8

Observation 5b091dba-5516-49ca-911a-9bd982552cca · outbound

This paper cites A unified approach to interpreting model predictions.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models A unified approach to interpreting model predictions

Reference 45

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source=pdf_text observed=2026-08-06T21:38:13.211481Z digest=sha256:8c7a43b0f39d4a40f89834ff256844e7cd1c9a3d0eef5a223ac6869af95bd7bb

Observation 289ca3f9-f581-4e3b-a571-1890709edb1c · outbound

This paper cites Measuring and Narrowing the Compositionality Gap in Language Models.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Measuring and Narrowing the Compositionality Gap in Language Models

Reference 46

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source=pdf_text observed=2026-08-06T21:38:13.274210Z digest=sha256:c2cd9c5bbe3fb579dbed55e4911534c89c92dca2aedb3b10847a990351182496

Observation 0fca2900-3358-467d-974d-3adfe0f460b0 · outbound

This paper cites ReAct: Synergizing Reasoning and Acting in Language Models.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models ReAct: Synergizing Reasoning and Acting in Language Models

Reference 47

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Observation 176c5fe2-4669-44bf-bac9-19a180108248 · outbound

This paper cites GPT-4 Technical Report.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models GPT-4 Technical Report

Reference 48

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source=pdf_text observed=2026-08-06T21:38:13.386228Z digest=sha256:53379c87c1d756533d7ba572a8a5025824cc09bf0ab1eafa9e1b92ff5cfbb8dd

Observation 86adc98c-7e25-4f46-a35b-bb0d18a61d36 · outbound

This paper cites Claude 3 model card.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Claude 3 model card

Reference 49

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verified fuzzy
raw_fallback, observed 2026-08-06T21:38:21.459903Z

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source=pdf_text observed=2026-08-06T21:38:13.468415Z digest=sha256:f33f32d0e0cb7c5780682a05be4451db1f4867a99882464a77c3bb5f0ae8fcd4

Observation e4461e01-434c-4715-94ad-31e23655c2fe · outbound

This paper cites Palm: Scaling language modeling with pathways.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Palm: Scaling language modeling with pathways

Reference 50

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verified fuzzy
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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=2026-08-06T21:38:13.539440Z digest=sha256:ec7a2ebb979e6b051e3be8836382ca12bbccbbd6d0c24c6b5358269a74a7c9e9

Observation 441ba540-33ae-46ec-a1f2-0bbc3ab1d4ca · outbound

This paper cites Solving Math Word Problems via Cooperative Reasoning induced Language Models.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Solving Math Word Problems via Cooperative Reasoning induced Language Models

Reference 51

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source=pdf_text observed=2026-08-06T21:38:13.625443Z digest=sha256:7a0fc2503fda1f30529def047adeb51e2b197a9f7e05ad8d7a0b8c61c1bae2f9

Observation b0edc789-cce4-4e88-af11-345fa4f0c160 · outbound

This paper cites Self-Consistency Improves Chain of Thought Reasoning in Language Models.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Self-Consistency Improves Chain of Thought Reasoning in Language Models

Reference 52

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source=pdf_text observed=2026-08-06T21:38:13.723436Z digest=sha256:3b4bfa1f7221011a86ab7ae955b10ee1ad514b26e7e73b87cec2bb817fe326c8

Observation 17adb6b6-9150-4cbe-9279-929851213e1f · outbound

This paper cites Least-to-Most Prompting Enables Complex Reasoning in Large Language Models.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Least-to-Most Prompting Enables Complex Reasoning in Large Language Models

Reference 53

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source=pdf_text observed=2026-08-06T21:38:13.807774Z digest=sha256:4a64153f54d821367c68a3873e5cd19eca90e1476982e851d7c38e885cc3c31c

Observation 01ae75e6-31b2-4292-894e-82c9abe7f6ff · outbound

This paper cites Progressive-Hint Prompting Improves Reasoning in Large Language Models.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Progressive-Hint Prompting Improves Reasoning in Large Language Models

Reference 54

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source=pdf_text observed=2026-08-06T21:38:13.903323Z digest=sha256:c3105901ea273c65b3f0a7cac4a9b10a5eaff6689fda49c37713da2c24d2daff

Observation df121b65-7652-443b-852c-ba3ae38d10e9 · outbound

This paper cites Self-Refine: Iterative Refinement with Self-Feedback.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Self-Refine: Iterative Refinement with Self-Feedback

Reference 55

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source=pdf_text observed=2026-08-06T21:38:13.982934Z digest=sha256:132f9a5cd6170c8323c1ee10316722a71d2f0af64106265e911ff6d581d079fd

Observation ec212fc2-0f56-41fe-aa65-eddcf63d229f · outbound

This paper cites Tree of Clarifications: Answering Ambiguous Questions with Retrieval-Augmented Large Language Models.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Tree of Clarifications: Answering Ambiguous Questions with Retrieval-Augmented Large Language Models

Reference 56

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source=pdf_text observed=2026-08-06T21:38:14.086464Z digest=sha256:483e193aa9d3dfd1de35102a027ff5db24b5ef198e77bde062be23683a0ca376

Observation f44e5b78-0413-4ab4-b973-dfb104b2e7c7 · outbound

This paper cites Chain-of-Verification Reduces Hallucination in Large Language Models.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Chain-of-Verification Reduces Hallucination in Large Language Models

Reference 57

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source=pdf_text observed=2026-08-06T21:38:14.153356Z digest=sha256:7ee50a525be2f308c900b131b7689a74eddc6ea8ef396f74b85cbbe54c2e345b

Observation b728bcc2-9cd8-4b32-af99-10b5b2c72947 · outbound

This paper cites Beyond Chain-of-Thought, Effective Graph-of-Thought Reasoning in Language Models.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Beyond Chain-of-Thought, Effective Graph-of-Thought Reasoning in Language Models

Reference 58

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source=pdf_text observed=2026-08-06T21:38:14.217604Z digest=sha256:5645b371e8a5acc56c5dd61a44252f70a5fb4a46de04ea59451943c5247b13f1

Observation dc4bf6d9-bde0-4ee6-a461-71b0e049e817 · outbound

This paper cites Graph of Thoughts: Solving Elaborate Problems with Large Language Models.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Graph of Thoughts: Solving Elaborate Problems with Large Language Models

Reference 59

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source=pdf_text observed=2026-08-06T21:38:14.282150Z digest=sha256:7597160299433777321a0da56a88fe8c125aa079c1295f36b444ea8e63e74da1

Observation 86dbc6c6-3011-4e5d-aeed-dc5043e8f0ac · outbound

This paper cites Large Language Model Guided Tree-of-Thought.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Large Language Model Guided Tree-of-Thought

Reference 60

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source=pdf_text observed=2026-08-06T21:38:14.361601Z digest=sha256:17427c34f48a2f4b6bb6df0d01bdb5022070d6796f2e53c35af93a59bbe8187d

Observation ff268dee-3964-4cb6-a5b5-5dc2f806bd22 · outbound

This paper cites Reasoning with Language Model is Planning with World Model.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Reasoning with Language Model is Planning with World Model

Reference 61

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source=pdf_text observed=2026-08-06T21:38:14.430455Z digest=sha256:2e72d7fe45b16d2a5dca448ac1fbf885eb3bface11f989eb08dbed825ed59aa4

Observation 4ee23331-b47a-4918-9836-721178f86c37 · outbound

This paper cites Automatic Chain of Thought Prompting in Large Language Models.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Automatic Chain of Thought Prompting in Large Language Models

Reference 62

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source=pdf_text observed=2026-08-06T21:38:14.518349Z digest=sha256:79d4336de714b39efdfbfa8308936280aa28ea3f8c56c674d1ccfa87e76d9266

Observation 2dded69f-c045-4c2c-a13f-d6d5e86a4a23 · outbound

This paper cites Complexity-Based Prompting for Multi-Step Reasoning.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Complexity-Based Prompting for Multi-Step Reasoning

Reference 63

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source=pdf_text observed=2026-08-06T21:38:14.576536Z digest=sha256:537e965d48fae694b5503a5b92e8d18beb260dd7e4abcea7aac14c712fb96f6f

Observation 012bd6e1-fb59-4c25-82c2-ba47e3425f75 · outbound

This paper cites Faithful Chain-of-Thought Reasoning.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Faithful Chain-of-Thought Reasoning

Reference 64

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source=pdf_text observed=2026-08-06T21:38:14.638518Z digest=sha256:94d44fb9f7ffb6f134b228fdfd2516df85fa68f05a5fbc31d093d0e04b9fbb52

Observation 6824e0da-91e9-4547-9a8c-cbf88512ff8f · outbound

This paper cites Measuring Faithfulness in Chain-of-Thought Reasoning.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Measuring Faithfulness in Chain-of-Thought Reasoning

Reference 65

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source=pdf_text observed=2026-08-06T21:38:14.643073Z digest=sha256:8184d407820163b82dc8132f62d9a8f6cea283223094723e926edf07c2be2c72

Observation e9551249-3c46-4628-9079-4e135bd62d59 · outbound

This paper cites Language Models Don't Always Say What They Think: Unfaithful Explanations in Chain-of-Thought Prompting.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Language Models Don't Always Say What They Think: Unfaithful Explanations in Chain-of-Thought Prompting

Reference 66

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source=pdf_text observed=2026-08-06T21:38:14.759770Z digest=sha256:07905632241077bc144a0e084bacf70d6b1bb3575b7c41725ce82c1d83469a8e

Observation 6fbc1714-cac2-46e3-8c69-0337b7fa6632 · outbound

This paper cites Language Models Are Greedy Reasoners: A Systematic Formal Analysis of Chain-of-Thought.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Language Models Are Greedy Reasoners: A Systematic Formal Analysis of Chain-of-Thought

Reference 67

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source=pdf_text observed=2026-08-06T21:38:14.845272Z digest=sha256:0c8c6a258cf24802e6d198d5deef9c2fe6662c67a8a2ed44afab2362f64b755e

Observation 5e6af1a1-3eb1-44e9-93e1-9cc0a31a8574 · outbound

This paper cites Program of Thoughts Prompting: Disentangling Computation from Reasoning for Numerical Reasoning Tasks.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Program of Thoughts Prompting: Disentangling Computation from Reasoning for Numerical Reasoning Tasks

Reference 68

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source=pdf_text observed=2026-08-06T21:38:14.988171Z digest=sha256:2341b761348c559a25e260ff3fd3742a27efdf6a5a4850f4c4e1cffcea60e254

Observation 7c1546f9-8789-4372-aa34-d9a2c12a8ed3 · outbound

This paper cites PAL: Program-aided Language Models.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models PAL: Program-aided Language Models

Reference 69

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source=pdf_text observed=2026-08-06T21:38:15.093301Z digest=sha256:10ab00f3b97432081bcf59a1f15d437667eaf6a7d7129a27e0b19470a371cc3c

Observation c3a3bdcf-5223-4e90-8a46-e6d3d3a45f9d · outbound

This paper cites Show Your Work: Scratchpads for Intermediate Computation with Language Models.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Show Your Work: Scratchpads for Intermediate Computation with Language Models

Reference 70

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source=pdf_text observed=2026-08-06T21:38:15.212084Z digest=sha256:0b0e072954ae7aaeb4804914e57d03ff844a6bdf8c6880d98f6974ad47de0a7f

Observation dcd7efd4-f557-428e-9306-70fc13f5d681 · outbound

This paper cites Larger language models do in-context learning differently.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Larger language models do in-context learning differently

Reference 71

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source=pdf_text observed=2026-08-06T21:38:15.320523Z digest=sha256:82efcbcac26b33d5d672ee98928a6a72646f562e47c21215b8f54f2f64df229f

Observation 9176c86e-ebdf-4f16-a538-e19742fbbc4a · outbound

This paper cites Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?

Reference 72

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source=pdf_text observed=2026-08-06T21:38:15.407609Z digest=sha256:7b31e8d672a572bc1acdd903b3ea4da9638894e659b04df972da6160d7eeca07

Observation dff0128a-b917-41de-9f64-8ece285bd6d5 · outbound

This paper cites An Explanation of In-context Learning as Implicit Bayesian Inference.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models An Explanation of In-context Learning as Implicit Bayesian Inference

Reference 73

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source=pdf_text observed=2026-08-06T21:38:15.481796Z digest=sha256:f630f80a72e22bf66ee3e061f32cd8c9fc182e7399c0983697fcaf4abbe35196

Observation 9a90d048-daaf-4f3d-94e3-3500651ff3d6 · outbound

This paper cites In-context Learning and Induction Heads.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models In-context Learning and Induction Heads

Reference 74

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source=pdf_text observed=2026-08-06T21:38:15.598291Z digest=sha256:e188925462f347a776e5f8bc891a8d5b3993077169549ff776cd2f86009ae1d1

Observation b41c34cf-72e6-4aae-abee-49da67b101bd · outbound

This paper cites Impact of Pretraining Term Frequencies on Few-Shot Reasoning.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Impact of Pretraining Term Frequencies on Few-Shot Reasoning

Reference 75

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source=pdf_text observed=2026-08-06T21:38:15.795444Z digest=sha256:f2cb013f224ebe5323da8fa56871a3a30403e8abdefbeb8aaf4e80cc357bfc46

Observation f124717c-d578-4f3a-aeba-a94ac95f1686 · outbound

This paper cites Data Distributional Properties Drive Emergent In-Context Learning in Transformers.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Data Distributional Properties Drive Emergent In-Context Learning in Transformers

Reference 76

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source=pdf_text observed=2026-08-06T21:38:15.949632Z digest=sha256:e453f55584155482777ebeda21dcb5d3fb3f3483a342137d0bc69f2481b53263

Observation 83f1bbe1-ef29-4705-89d6-2d22e9a75762 · outbound

This paper cites What Can Transformers Learn In-Context? A Case Study of Simple Function Classes.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models What Can Transformers Learn In-Context? A Case Study of Simple Function Classes

Reference 77

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source=pdf_text observed=2026-08-06T21:38:16.041875Z digest=sha256:ec781956487b0cc69aaeaa3e826856805cb939dba4a899ace147cb5b55f29a19

Observation 42a377f2-6f54-4f1c-b1c4-675a8a3acb67 · outbound

This paper cites What learning algorithm is in-context learning? Investigations with linear models.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models What learning algorithm is in-context learning? Investigations with linear models

Reference 78

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source=pdf_text observed=2026-08-06T21:38:16.167759Z digest=sha256:7552b10d16c6227a780be0257db395856863ab03dc4e9224c70c8aaa285e1932

Observation f01fd6a8-5cee-4206-817b-028894d7fec8 · outbound

This paper cites Transformers learn in-context by gradient descent.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Transformers learn in-context by gradient descent

Reference 79

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source=pdf_text observed=2026-08-06T21:38:16.278676Z digest=sha256:2b22e94a22cd921e0c597313312afdd0926db8e04b1e38fb626e489a0d3dc38e

Observation 9e863460-63fb-42d3-b1ed-6a727aab1fb1 · outbound

This paper cites Why Can GPT Learn In-Context? Language Models Implicitly Perform Gradient Descent as Meta-Optimizers.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Why Can GPT Learn In-Context? Language Models Implicitly Perform Gradient Descent as Meta-Optimizers

Reference 80

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source=pdf_text observed=2026-08-06T21:38:16.429781Z digest=sha256:8d1e81612e89a52b0d339c162e91eff3bdef575b89f4c018fa7a77b790ee5f01

Observation 3c914249-4c86-4330-9d8d-39768d667a13 · outbound

This paper cites Meta-learning via Language Model In-context Tuning.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Meta-learning via Language Model In-context Tuning

Reference 81

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source=pdf_text observed=2026-08-06T21:38:16.542685Z digest=sha256:924ec547b55bd686ae23760299d96115bc59cd0298134a71685176b0fbf48212

Observation 47477143-dafe-4423-9659-e731466d2111 · outbound

This paper cites Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLP.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLP

Reference 82

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source=pdf_text observed=2026-08-06T21:38:16.645592Z digest=sha256:78770a531a5ad3ac455f7d18421698d29c46b8f519bd4954d3d7badbc8b7be46

Observation 45b274f0-df37-4269-8f61-47d2e6d1856e · outbound

This paper cites Generate rather than Retrieve: Large Language Models are Strong Context Generators.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Generate rather than Retrieve: Large Language Models are Strong Context Generators

Reference 83

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source=pdf_text observed=2026-08-06T21:38:16.791784Z digest=sha256:1cf7267c7cb09539140332e67b6a74f0276c7d100bf5c9d4cffcc475f0472e55

Observation db98b562-8fde-494d-9ae0-e0a593aa5b46 · outbound

This paper cites When Not to Trust Language Models: Investigating Effectiveness of Parametric and Non-Parametric Memories.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models When Not to Trust Language Models: Investigating Effectiveness of Parametric and Non-Parametric Memories

Reference 84

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source=pdf_text observed=2026-08-06T21:38:16.982870Z digest=sha256:fee14361fba92a9727178e51b5351b955cd02f42bcc5a575c8a9abeafa1176a0

Observation 5afc816b-c571-4478-a31c-4a28bdb25e71 · outbound

This paper cites Large Language Models Can Be Easily Distracted by Irrelevant Context.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Large Language Models Can Be Easily Distracted by Irrelevant Context

Reference 85

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source=pdf_text observed=2026-08-06T21:38:17.192690Z digest=sha256:40ca42ea6e69921e1d6ebc3cd15964aec817d90ac9c3a076d108dcf31a05e3bb

Observation e9dc4650-34ac-4f33-b565-9b217cbc97f2 · outbound

This paper cites Lost in the Middle: How Language Models Use Long Contexts.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Lost in the Middle: How Language Models Use Long Contexts

Reference 86

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source=pdf_text observed=2026-08-06T21:38:17.352234Z digest=sha256:ba4578ea101e0060c8cc44ca6fa492f61d841a06cd78c9fd2114ceadc6ea9749

Observation f25c7346-a933-4797-b802-543e0355b6e4 · outbound

This paper cites Debiasing Vision-Language Models via Biased Prompts.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Debiasing Vision-Language Models via Biased Prompts

Reference 87

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source=pdf_text observed=2026-08-06T21:38:17.461164Z digest=sha256:f9c04a4a944fdf4e386515669192fde8d97fb9e72b7625b9da4b76b82e6fd711

Observation 3da5d697-ad21-45d1-9a13-585109c59aa4 · outbound

This paper cites Quantifying Memorization Across Neural Language Models.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Quantifying Memorization Across Neural Language Models

Reference 88

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source=pdf_text observed=2026-08-06T21:38:17.626450Z digest=sha256:04fbdd94c362c83b6cb929c1afeca435cb1b4a7dc6ac0f15c30ad147fc6474b1

Observation 2f97a63e-318d-4b68-9e8e-374f30348d9f · outbound

This paper cites Memorization Without Overfitting: Analyzing the Training Dynamics of Large Language Models.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Memorization Without Overfitting: Analyzing the Training Dynamics of Large Language Models

Reference 89

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source=pdf_text observed=2026-08-06T21:38:17.730528Z digest=sha256:a99bd87de78147899eb91b3b8a31201a46220a6c2c0320b5b70236daf47f64b8

Observation 88db7ac9-a528-478d-aaa3-8beb7bb33084 · outbound

This paper cites an unresolved cited work.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Unresolved cited work

Reference 90

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source=pdf_text observed=2026-08-06T21:38:17.866162Z digest=sha256:9fb75e3324e143a89a800b45e0341bdf34e717178d6260a6fd5d76e70448c8b9

Observation b2738633-c740-4f3d-ab22-ba4ee7986690 · outbound

This paper cites an unresolved cited work.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Unresolved cited work

Reference 91

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source=pdf_text observed=2026-08-06T21:38:18.038421Z digest=sha256:2d6573350752fa843f2073937ec06aa0ced73869a6277ab6b7c700f7262ffe75

Observation 37539507-1f31-44df-b80b-f31b2f650b68 · outbound

This paper cites an unresolved cited work.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Unresolved cited work

Reference 92

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source=pdf_text observed=2026-08-06T21:38:18.136887Z digest=sha256:0bf22c40ee82055cd054a37edf92139a047ea9db2ad79a05b85e382d38e4e475

Observation cb3bb155-2d0b-45a4-a180-bb0b55d12f35 · outbound

This paper cites an unresolved cited work.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Unresolved cited work

Reference 93

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source=pdf_text observed=2026-08-06T21:38:18.302371Z digest=sha256:e78a1c0f4e03f8bcbc27c1ccb5501bc48a4f0f7f0a9eb8929235f0f6d77d1027

Observation 06a86255-114e-4dff-b40c-aeadc1c86720 · outbound

This paper cites If 3x + 2 = 14, what is x?.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models If 3x + 2 = 14, what is x?

Reference 94

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

source=pdf_text observed=2026-08-06T21:38:18.381079Z digest=sha256:0c9a41efe9dcecdfbf2d006d457ca1bbb8f0dce0d85dca5ff3b118d8a85702ca

Observation c7f6204c-6546-4f43-81c3-44cf1744ae92 · outbound

This paper cites an unresolved cited work.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Unresolved cited work

Reference 95

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

source=pdf_text observed=2026-08-06T21:38:18.476792Z digest=sha256:674c36f7d20e5774bf671b2830b3e9c577ac726ee20e7a3f1808f832f1f06b40

Observation 61029ebf-b78f-49b7-865c-8d08ac8ae6ce · outbound

This paper cites an unresolved cited work.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Unresolved cited work

Reference 96

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

source=pdf_text observed=2026-08-06T21:38:18.607375Z digest=sha256:6c70714edb62943068efd3b2d89b1895d88c9ab2519cde58853918701841e728

Observation 7087d3db-d955-4134-b26e-c997c74dcf82 · outbound

This paper cites In a tournament, each team plays every other team exactly once. If there are 156 games total, how many teams participated?.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models In a tournament, each team plays every other team exactly once. If there are 156 games total, how many teams participated?

Reference 97

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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=2026-08-06T21:38:18.765047Z digest=sha256:244cb928f1ea15806831b90486f60077efabd8274c42e57e3020b002fb9c3556

Observation f5156283-f46e-431d-b9a9-0d8582420012 · outbound

This paper cites Explain why you chose method A over method B.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models Explain why you chose method A over method B

Reference 156

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verified fuzzy
raw_fallback, observed 2026-08-06T21:38:19.934702Z

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=2026-08-06T21:38:18.903822Z digest=sha256:52a9c9ff592b2c3a1729d7d37ce9fc06d6bbe76b966f3d47bc3fb62957a1f8c6

Pith citing papers

No inbound Pith citation observations are available.