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Paper Citation Record · LEDGER

ReaLM: Reflection-Enhanced Autonomous Reasoning with Small Language Models

As of 16 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 0 inbound Pith citation observations for arXiv:2508.12387.

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

pith.paper-citation-record.v1
2508.12387 v1

Coverage vector

measured 46 of 46 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T17:30:10.366860Z

measured 46 of 46 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

46 of 46 outbound references displayed

  • verified exact1
  • verified fuzzy0
  • unresolved45
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

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Outbound references

Observation 8432d6b2-4b6a-497c-bace-101932d726fe · outbound

This paper cites MCC-KD: Multi-CoT Consistent Knowledge Distillation.

ReaLM: Reflection-Enhanced Autonomous Reasoning with Small Language Models MCC-KD: Multi-CoT Consistent Knowledge Distillation

Reference 1

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source=arxiv_source observed=2026-08-15T17:30:09.997455Z digest=sha256:8f6c5e6a9bfd28a4187e502b6b30f89f402c100e133c3a92eac553d0eca1121a

Observation 8f640e9a-fbab-4c67-9d08-abd81a441dc8 · outbound

This paper cites an unresolved cited work.

ReaLM: Reflection-Enhanced Autonomous Reasoning with Small Language Models Unresolved cited work

Reference 2

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source=arxiv_source observed=2026-08-15T17:30:10.006417Z digest=sha256:7b1cd184f5d917942b8b2cd81561116e2ca0c5cae09fcdb6b37014f11b14e6fd

Observation 6fa91cd9-ee7b-4a85-9d1e-ed8569a11dc9 · outbound

This paper cites Universal Self-Consistency for Large Language Model Generation.

ReaLM: Reflection-Enhanced Autonomous Reasoning with Small Language Models Universal Self-Consistency for Large Language Model Generation

Reference 3

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source=arxiv_source observed=2026-08-15T17:30:10.012367Z digest=sha256:6b64a21df1bda93c7102a071d47a9bf2585970cdac701888d11ce1b684926bc0

Observation 1e2aee67-d4b1-40b7-a6b9-5f8d6c987496 · outbound

This paper cites an unresolved cited work.

ReaLM: Reflection-Enhanced Autonomous Reasoning with Small Language Models Unresolved cited work

Reference 4

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source=arxiv_source observed=2026-08-15T17:30:10.018584Z digest=sha256:6741f78c275b964f4131e1d9bfb1a87c11d3931975b1df864a12be3985928f99

Observation 8ddc747b-4e1a-4548-b861-f99b7614675f · outbound

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

ReaLM: Reflection-Enhanced Autonomous Reasoning with Small Language Models Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 5

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source=arxiv_source observed=2026-08-15T17:30:10.025196Z digest=sha256:3101f74eb6a562246c7d04bd09dc9064275b3f6b3871be0e56f38eac02725554

Observation 2adfa126-7575-4906-b9f8-4f93a3ee4105 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

ReaLM: Reflection-Enhanced Autonomous Reasoning with Small Language Models Training Verifiers to Solve Math Word Problems

Reference 6

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source=arxiv_source observed=2026-08-15T17:30:10.032031Z digest=sha256:2213d1837b80efb682711821ad95c672031c8d4621ef701638ee9d7b2a40ddfa

Observation d60ea19f-685a-4960-9fe8-a93fd9afe398 · outbound

This paper cites Improve Student's Reasoning Generalizability through Cascading Decomposed CoTs Distillation.

ReaLM: Reflection-Enhanced Autonomous Reasoning with Small Language Models Improve Student's Reasoning Generalizability through Cascading Decomposed CoTs Distillation

Reference 7

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source=arxiv_source observed=2026-08-15T17:30:10.039486Z digest=sha256:9731127913042a54749d549121b85802481107e9d72d75a26b1b021e32df7fa6

Observation f69e4fd5-e182-403a-a396-193db6ba8449 · outbound

This paper cites Investigating Symbolic Capabilities of Large Language Models.

ReaLM: Reflection-Enhanced Autonomous Reasoning with Small Language Models Investigating Symbolic Capabilities of Large Language Models

Reference 8

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source=arxiv_source observed=2026-08-15T17:30:10.046467Z digest=sha256:93ff1db5f24cbd45f68cf9db11f691ba5283144084a9b7ae0784dfa49b504718

Observation 5bd4380b-62bf-44e2-b115-ea97a63a180b · outbound

This paper cites an unresolved cited work.

ReaLM: Reflection-Enhanced Autonomous Reasoning with Small Language Models Unresolved cited work

Reference 9

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source=arxiv_source observed=2026-08-15T17:30:10.051819Z digest=sha256:1e8e024ca755aacbf1ec8f26747c3f658d5b0fc004e49287a513045b2caf22c0

Observation 6b6cf652-22fa-4e10-be71-e57b220a7bb0 · outbound

This paper cites an unresolved cited work.

ReaLM: Reflection-Enhanced Autonomous Reasoning with Small Language Models Unresolved cited work

Reference 10

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source=arxiv_source observed=2026-08-15T17:30:10.057883Z digest=sha256:6ffdcdbf644c6a468e1b8defd2c7d2c9eff195cd792dbe37ced34c9cba8ccb53

Observation e440bc80-48a1-438c-8670-1d35ddf5c36a · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

ReaLM: Reflection-Enhanced Autonomous Reasoning with Small Language Models DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 11

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source=arxiv_source observed=2026-08-15T17:30:10.064832Z digest=sha256:1fd1a7464503e6f061fd8dc5cc8df33db0995e7126e3313ac15d3fc6bce8f4b8

Observation c4f230cd-5547-4796-b405-5e7f9fc5bcbb · outbound

This paper cites an unresolved cited work.

ReaLM: Reflection-Enhanced Autonomous Reasoning with Small Language Models Unresolved cited work

Reference 12

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source=arxiv_source observed=2026-08-15T17:30:10.070606Z digest=sha256:ecae1fbab7f73bdc9cd86d5c882a7076fada4529bd1291ddb789600ba86f4627

Observation 5d8c221f-b28f-48ed-8b47-f016461849c1 · outbound

This paper cites On the Impact of Knowledge Distillation for Model Interpretability.

ReaLM: Reflection-Enhanced Autonomous Reasoning with Small Language Models On the Impact of Knowledge Distillation for Model Interpretability

Reference 13

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source=arxiv_source observed=2026-08-15T17:30:10.076003Z digest=sha256:dd63b5a15a7837a2f5c75e64e892edba85a6d7b9fbc5c6eb2a6fbfa2ee8c8b34

Observation a4860222-7179-4dd9-b878-8de876ce840d · outbound

This paper cites Measuring Massive Multitask Language Understanding.

ReaLM: Reflection-Enhanced Autonomous Reasoning with Small Language Models Measuring Massive Multitask Language Understanding

Reference 14

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source=arxiv_source observed=2026-08-15T17:30:10.081962Z digest=sha256:d3bdbfe05549c6c599e43655a473497f24c1a6b77e11cbf8b5a25a79a159e444

Observation eca87bf4-5dff-4c63-9cac-8f6c546b1b10 · outbound

This paper cites Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes.

ReaLM: Reflection-Enhanced Autonomous Reasoning with Small Language Models Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes

Reference 15

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source=arxiv_source observed=2026-08-15T17:30:10.087366Z digest=sha256:a827aef737c8341712a43e4e81e1414e5213654fcdc146c3fec6a577f752bd3c

Observation 5ce6bc4e-4f41-40c6-b904-87278c9c0d06 · outbound

This paper cites Qwen2.5-Coder Technical Report.

ReaLM: Reflection-Enhanced Autonomous Reasoning with Small Language Models Qwen2.5-Coder Technical Report

Reference 16

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source=arxiv_source observed=2026-08-15T17:30:10.093473Z digest=sha256:a8a0faf18364f74f24175dddb846e1da1342ad7505ac1c7671ad2ddbc7561b6c

Observation 37f53f8d-f51c-490d-bc38-47243f20455b · outbound

This paper cites Simple and Scalable Strategies to Continually Pre-train Large Language Models.

ReaLM: Reflection-Enhanced Autonomous Reasoning with Small Language Models Simple and Scalable Strategies to Continually Pre-train Large Language Models

Reference 17

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Observation efd70028-0b3f-47f5-9d93-3e5bfc7e3beb · outbound

This paper cites OpenAI o1 System Card.

ReaLM: Reflection-Enhanced Autonomous Reasoning with Small Language Models OpenAI o1 System Card

Reference 18

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source=arxiv_source observed=2026-08-15T17:30:10.108597Z digest=sha256:3a2f3f313e12e7e6bd2d12897c6101abefde7b51d39e600db6abe53a61d4be4b

Observation ff61485d-33eb-4d24-8e62-4473686cfccb · outbound

This paper cites Scaling Laws for Neural Language Models.

ReaLM: Reflection-Enhanced Autonomous Reasoning with Small Language Models Scaling Laws for Neural Language Models

Reference 19

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source=arxiv_source observed=2026-08-15T17:30:10.114480Z digest=sha256:15feaeeaeb630ce68b82e3c0dbc3c4a2507eccaf650d74a35bea8c6fc1652dc0

Observation a7236b47-a1d3-460d-8c57-eabcea247270 · outbound

This paper cites The CoT Collection: Improving Zero-shot and Few-shot Learning of Language Models via Chain-of-Thought Fine-Tuning.

ReaLM: Reflection-Enhanced Autonomous Reasoning with Small Language Models The CoT Collection: Improving Zero-shot and Few-shot Learning of Language Models via Chain-of-Thought Fine-Tuning

Reference 20

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source=arxiv_source observed=2026-08-15T17:30:10.119254Z digest=sha256:8ddaa8ac3777025015896fd2f95f8f154781213ae13c4fac0c206b4ea18a468c

Observation ce40e913-bef6-46b7-8b88-93710474b509 · outbound

This paper cites GSM-Plus: A Comprehensive Benchmark for Evaluating the Robustness of LLMs as Mathematical Problem Solvers.

ReaLM: Reflection-Enhanced Autonomous Reasoning with Small Language Models GSM-Plus: A Comprehensive Benchmark for Evaluating the Robustness of LLMs as Mathematical Problem Solvers

Reference 21

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source=arxiv_source observed=2026-08-15T17:30:10.125206Z digest=sha256:8f6defccdb8e0c10ee185159e28336cf26b0e960c73fbcbe8aa128d6d0bb32ec

Observation 72803b75-f54f-42e2-ae6b-679d7e66dfd5 · outbound

This paper cites Explanations from Large Language Models Make Small Reasoners Better.

ReaLM: Reflection-Enhanced Autonomous Reasoning with Small Language Models Explanations from Large Language Models Make Small Reasoners Better

Reference 22

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source=arxiv_source observed=2026-08-15T17:30:10.132783Z digest=sha256:a74acebffb81697646a471448d4205de26c46b92300e1a4d074aa1438338bb18

Observation d532f56f-1d36-4e14-a307-9d752f503eed · outbound

This paper cites Model Merging in Pre-training of Large Language Models.

ReaLM: Reflection-Enhanced Autonomous Reasoning with Small Language Models Model Merging in Pre-training of Large Language Models

Reference 23

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source=arxiv_source observed=2026-08-15T17:30:10.163726Z digest=sha256:37883cb45df128738049d6630f07ad1d6dab2a8afa9a44e523638b2b9b5f2bf5

Observation 9cdbfe87-a25c-4528-81e5-64f0d3799ae5 · outbound

This paper cites $\textit{SKIntern}$: Internalizing Symbolic Knowledge for Distilling Better CoT Capabilities into Small Language Models.

ReaLM: Reflection-Enhanced Autonomous Reasoning with Small Language Models $\textit{SKIntern}$: Internalizing Symbolic Knowledge for Distilling Better CoT Capabilities into Small Language Models

Reference 24

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source=arxiv_source observed=2026-08-15T17:30:10.202314Z digest=sha256:359cc64a48fe41e8b245e15a4abf89ee27ad1e8839aefd68acd60f458b72ac67

Observation f158f0e1-900f-44fb-82f0-f9a9af57a7da · outbound

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ReaLM: Reflection-Enhanced Autonomous Reasoning with Small Language Models Unresolved cited work

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source=arxiv_source observed=2026-08-15T17:30:10.208928Z digest=sha256:8d4c0c2f05a564f491f67b3eecc4d37bfa517cfc00877e520dd5ba285ec6b158

Observation dce8a3a3-818d-47c0-8276-c3770c2480a0 · outbound

This paper cites Mind's Mirror: Distilling Self-Evaluation Capability and Comprehensive Thinking from Large Language Models.

ReaLM: Reflection-Enhanced Autonomous Reasoning with Small Language Models Mind's Mirror: Distilling Self-Evaluation Capability and Comprehensive Thinking from Large Language Models

Reference 26

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source=arxiv_source observed=2026-08-15T17:30:10.216030Z digest=sha256:29b34c2759bd244faf4530a3d9bd1e0515349857d84689b34ef467032019066c

Observation 2a29cc3b-2bae-4c45-b852-7083dd8091f0 · outbound

This paper cites an unresolved cited work.

ReaLM: Reflection-Enhanced Autonomous Reasoning with Small Language Models Unresolved cited work

Reference 27

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source=arxiv_source observed=2026-08-15T17:30:10.222024Z digest=sha256:409aa3826d9152b180cc4da7dc4bb288e650db4973d458210e6be1360432db2e

Observation 80340091-be7f-4bd1-abaa-4ee8b83eb3ae · outbound

This paper cites SQuAD: 100,000+ Questions for Machine Comprehension of Text.

ReaLM: Reflection-Enhanced Autonomous Reasoning with Small Language Models SQuAD: 100,000+ Questions for Machine Comprehension of Text

Reference 28

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source=arxiv_source observed=2026-08-15T17:30:10.228110Z digest=sha256:98721a8c3eb9b5f811fe45b85fc18376a5600527131cf30a0750bbb767af1c79

Observation 739bd6f1-b775-42ab-be4d-6ee58d00d90e · outbound

This paper cites an unresolved cited work.

ReaLM: Reflection-Enhanced Autonomous Reasoning with Small Language Models Unresolved cited work

Reference 29

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-15T17:30:10.234315Z digest=sha256:619a81f014c7f0a92d66efa7e077c020dff88fea73df89b232adb9a5f74e854b

Observation 878e4188-55bf-4e77-a1ef-a89b59af5b45 · outbound

This paper cites Active Learning for Convolutional Neural Networks: A Core-Set Approach.

ReaLM: Reflection-Enhanced Autonomous Reasoning with Small Language Models Active Learning for Convolutional Neural Networks: A Core-Set Approach

Reference 30

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source=arxiv_source observed=2026-08-15T17:30:10.243928Z digest=sha256:85262b512b730f784416e2e4d159e44600fc610dde963732cedb336aa215f4bf

Observation f3776c99-b666-4ffb-acb3-8a308e1797a1 · outbound

This paper cites Rewarding Progress: Scaling Automated Process Verifiers for LLM Reasoning.

ReaLM: Reflection-Enhanced Autonomous Reasoning with Small Language Models Rewarding Progress: Scaling Automated Process Verifiers for LLM Reasoning

Reference 31

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source=arxiv_source observed=2026-08-15T17:30:10.251490Z digest=sha256:07099714295cfd18a6d48e64324ae02e3077d9ddcbd13daaa742f6f91a867763

Observation 143b60e9-9fad-474d-b27d-b569c6246724 · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

ReaLM: Reflection-Enhanced Autonomous Reasoning with Small Language Models DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 32

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source=arxiv_source observed=2026-08-15T17:30:10.261498Z digest=sha256:e325bb4cf178e571911873ed9bd3332bd0f47d8bdd648ac00413f0c84466a58f

Observation 24c9c5b6-544f-4ad0-88ce-436cde86f6a2 · outbound

This paper cites A.; Abid, A.; Fisch, A.; Brown, A.

ReaLM: Reflection-Enhanced Autonomous Reasoning with Small Language Models A.; Abid, A.; Fisch, A.; Brown, A

Reference 33

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source=arxiv_source observed=2026-08-15T17:30:10.267698Z digest=sha256:a6da316d5d5bb7573be53a0719e074391243d99a510b2ce675da1bd7bb29e753

Observation 8e60cab9-2d9e-415a-9590-5a3a96fc5387 · outbound

This paper cites Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them.

ReaLM: Reflection-Enhanced Autonomous Reasoning with Small Language Models Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them

Reference 34

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source=arxiv_source observed=2026-08-15T17:30:10.276856Z digest=sha256:3e91eb807dd07d0fe25020d829c1ccc3bae84b1deb9a5d9cb6f01b124ec13319

Observation 39009085-8a5a-43f4-b847-496c1bef439b · outbound

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

ReaLM: Reflection-Enhanced Autonomous Reasoning with Small Language Models Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 35

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source=arxiv_source observed=2026-08-15T17:30:10.285920Z digest=sha256:d1979b4334b4f706bf944b47156cac9eae15c00ccff286cd038bb11a160b1aec

Observation b2f2421b-99d1-4ea6-aaee-26f7de7dea2e · outbound

This paper cites Interpretable Preferences via Multi-Objective Reward Modeling and Mixture-of-Experts.

ReaLM: Reflection-Enhanced Autonomous Reasoning with Small Language Models Interpretable Preferences via Multi-Objective Reward Modeling and Mixture-of-Experts

Reference 36

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source=arxiv_source observed=2026-08-15T17:30:10.291665Z digest=sha256:19553f76ac6fa4f9f1e20242c7569957b34367dcf5a851b19720c26647f03cc0

Observation a68d2bfc-8f75-42e3-8380-e6c34325ab38 · outbound

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

ReaLM: Reflection-Enhanced Autonomous Reasoning with Small Language Models Self-Consistency Improves Chain of Thought Reasoning in Language Models

Reference 37

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source=arxiv_source observed=2026-08-15T17:30:10.298033Z digest=sha256:633a7835804c795deb48a7d97a31641b6ce6dce257acdaf7fb56f641e160b67f

Observation e32ed6e3-1c5b-42f6-a4a4-6e4ee7b7cdbd · outbound

This paper cites V.; Zhou, D.; et al.

ReaLM: Reflection-Enhanced Autonomous Reasoning with Small Language Models V.; Zhou, D.; et al

Reference 38

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no resolver link, observed 2026-08-15T17:30:10.303249Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-15T17:30:10.303249Z digest=sha256:b9b820b3ad76c3e5ad5d61220d2168000ebc37dd41bc4f24b1e3c88aebddf9be

Observation 166a238d-5d8c-4071-8861-3695b7761c84 · outbound

This paper cites an unresolved cited work.

ReaLM: Reflection-Enhanced Autonomous Reasoning with Small Language Models Unresolved cited work

Reference 39

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verified exact
raw_fallback, observed 2026-08-15T17:30:10.685464Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-15T17:30:10.313356Z digest=sha256:77d192e9ef9682e38116e05cf9e96ba5d3acf78ae607f5282f4129b28fab37a9

Observation 0ca5fcd7-cc00-45bf-bc93-c9780812a81b · outbound

This paper cites LLMs-as-Instructors: Learning from Errors Toward Automating Model Improvement.

ReaLM: Reflection-Enhanced Autonomous Reasoning with Small Language Models LLMs-as-Instructors: Learning from Errors Toward Automating Model Improvement

Reference 40

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no resolver link, observed 2026-08-15T17:30:10.319553Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-15T17:30:10.319553Z digest=sha256:c2be5b90b5c1e945ba18f199e20ac83ad09c5f764dbb97fd12df652e113193be

Observation fe457447-e8ca-4eae-a665-dc163fefc2e8 · outbound

This paper cites Scaling Relationship on Learning Mathematical Reasoning with Large Language Models.

ReaLM: Reflection-Enhanced Autonomous Reasoning with Small Language Models Scaling Relationship on Learning Mathematical Reasoning with Large Language Models

Reference 41

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unresolved
no resolver link, observed 2026-08-15T17:30:10.331861Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T17:30:10.331861Z digest=sha256:67502d26c747451d0b9e35e2aae5c21c849df16cb2d321c43ed5c015a0f7985e

Observation f1f0bda7-5e68-4f86-a0c2-ad79bb686e11 · outbound

This paper cites CoT-based Synthesizer: Enhancing LLM Performance through Answer Synthesis.

ReaLM: Reflection-Enhanced Autonomous Reasoning with Small Language Models CoT-based Synthesizer: Enhancing LLM Performance through Answer Synthesis

Reference 42

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unresolved
no resolver link, observed 2026-08-15T17:30:10.340136Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T17:30:10.340136Z digest=sha256:4e48ccaf87f4df974c1f9223690b4038aa677ddcba86e9c91bb2136ca6239659

Observation 5b09c08b-0b53-4b17-8b80-040962e910e2 · outbound

This paper cites Towards the Law of Capacity Gap in Distilling Language Models.

ReaLM: Reflection-Enhanced Autonomous Reasoning with Small Language Models Towards the Law of Capacity Gap in Distilling Language Models

Reference 43

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no resolver link, observed 2026-08-15T17:30:10.347134Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T17:30:10.347134Z digest=sha256:7623b9011afbe07f23f0cb5684b9ec58b73ff75d367e7d9cf6103e5f343d42df

Observation b782d167-d4c3-44e2-8bf8-c9b727fbe744 · outbound

This paper cites TinyLLaVA-Video-R1: Towards Smaller LMMs for Video Reasoning.

ReaLM: Reflection-Enhanced Autonomous Reasoning with Small Language Models TinyLLaVA-Video-R1: Towards Smaller LMMs for Video Reasoning

Reference 44

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no resolver link, observed 2026-08-15T17:30:10.352493Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T17:30:10.352493Z digest=sha256:3bc80ba8aa38f3acbc8216f9ce38b202bc19a0ef56e9231c497e9c5c704997e9

Observation 6dd2f60a-b4a4-4803-8b55-5ed589bf5855 · outbound

This paper cites AGIEval: A Human-Centric Benchmark for Evaluating Foundation Models.

ReaLM: Reflection-Enhanced Autonomous Reasoning with Small Language Models AGIEval: A Human-Centric Benchmark for Evaluating Foundation Models

Reference 45

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unresolved
no resolver link, observed 2026-08-15T17:30:10.358136Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T17:30:10.358136Z digest=sha256:bb20837236ba8581b043ac7623b1dbda368b7ab0c59f893b41b8006920cfb176

Observation 69358d05-724e-4983-8aca-6792ff0d6fba · outbound

This paper cites Rethinking Soft Labels for Knowledge Distillation: A Bias-Variance Tradeoff Perspective.

ReaLM: Reflection-Enhanced Autonomous Reasoning with Small Language Models Rethinking Soft Labels for Knowledge Distillation: A Bias-Variance Tradeoff Perspective

Reference 46

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unresolved
no resolver link, observed 2026-08-15T17:30:10.366860Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T17:30:10.366860Z digest=sha256:98ec31c4c2705caf307df5be0de52db876ae4a1dffb2737f4c3dde406deaef43

Pith citing papers

No inbound Pith citation observations are available.