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Paper Citation Record · LEDGER

Improve Rule Retrieval and Reasoning with Self-Induction and Relevance ReEstimate

As of 19 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 0 inbound Pith citation observations for arXiv:2505.10870.

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

pith.paper-citation-record.v1
2505.10870 v1

Coverage vector

measured 46 of 46 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:06:47.832223Z

measured 46 of 46 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+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 exact0
  • verified fuzzy0
  • unresolved46
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 87fe5be4-bae5-450a-a683-59e0d872126d · outbound

This paper cites Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone.

Improve Rule Retrieval and Reasoning with Self-Induction and Relevance ReEstimate Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone

Reference 1

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Observation df02b3e5-9daa-44f2-8c54-827e85d5da9d · outbound

This paper cites Yi: Open Foundation Models by 01.AI.

Improve Rule Retrieval and Reasoning with Self-Induction and Relevance ReEstimate Yi: Open Foundation Models by 01.AI

Reference 2

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source=arxiv_source observed=2026-08-15T21:06:47.622227Z digest=sha256:d7b0be941a215bfb12ee2ef79b18d3641ab049dee785f2c35edfa8478c6c9631

Observation 3f6a6bc6-da9e-407b-bc5c-a1a712f21ee2 · outbound

This paper cites MS MARCO: A Human Generated MAchine Reading COmprehension Dataset.

Improve Rule Retrieval and Reasoning with Self-Induction and Relevance ReEstimate MS MARCO: A Human Generated MAchine Reading COmprehension Dataset

Reference 3

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source=arxiv_source observed=2026-08-15T21:06:47.627557Z digest=sha256:f5a9a4db74f0824b194adc9690e05b4040c82bcc2b7e2515d22c769cb385a7f0

Observation 1ff0d636-768e-4b16-a556-566df0e4ccad · outbound

This paper cites an unresolved cited work.

Improve Rule Retrieval and Reasoning with Self-Induction and Relevance ReEstimate Unresolved cited work

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation b63b67d8-1d0d-47d0-ae9c-38ee0a1cf982 · outbound

This paper cites M3-Embedding: Multi-Linguality, Multi-Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillation.

Improve Rule Retrieval and Reasoning with Self-Induction and Relevance ReEstimate M3-Embedding: Multi-Linguality, Multi-Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillation

Reference 5

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source=arxiv_source observed=2026-08-15T21:06:47.637209Z digest=sha256:a9461633f2c46b3e046d5f14c41dbd2dd5f3c978d58875624855bb8afc2064b4

Observation c0c87bff-3778-475e-acfa-bf810ac6939b · outbound

This paper cites an unresolved cited work.

Improve Rule Retrieval and Reasoning with Self-Induction and Relevance ReEstimate Unresolved cited work

Reference 6

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source=arxiv_source observed=2026-08-15T21:06:47.642197Z digest=sha256:cdf2ce38795f21d14e820f06470095e60338667dc60ad3bd8d1c1780671bd307

Observation 9d71c155-bb4c-4489-a6e5-f2130518f88f · outbound

This paper cites Inductive or Deductive? Rethinking the Fundamental Reasoning Abilities of LLMs.

Improve Rule Retrieval and Reasoning with Self-Induction and Relevance ReEstimate Inductive or Deductive? Rethinking the Fundamental Reasoning Abilities of LLMs

Reference 7

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source=arxiv_source observed=2026-08-15T21:06:47.647297Z digest=sha256:c2997164323fb5c1caead5efd3018a544be181fe3c5766733b5c737df9b5c859

Observation 16139efb-7c78-48f6-943e-19a060875fed · outbound

This paper cites A Survey on In-context Learning.

Improve Rule Retrieval and Reasoning with Self-Induction and Relevance ReEstimate A Survey on In-context Learning

Reference 8

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source=arxiv_source observed=2026-08-15T21:06:47.652190Z digest=sha256:1a339c2f6f1d3acfe0548cb027846db6b1261eef7a0db2609a34fb8f73251056

Observation e981a988-5b70-4151-b298-6683fc0b8391 · outbound

This paper cites The Llama 3 Herd of Models.

Improve Rule Retrieval and Reasoning with Self-Induction and Relevance ReEstimate The Llama 3 Herd of Models

Reference 9

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source=arxiv_source observed=2026-08-15T21:06:47.657031Z digest=sha256:53d9475f3b5231498196b186a70353165535d1fd301eae55ad452ff7c890c3fb

Observation 7ead65b6-6aac-4371-b417-46135eb830f5 · outbound

This paper cites an unresolved cited work.

Improve Rule Retrieval and Reasoning with Self-Induction and Relevance ReEstimate Unresolved cited work

Reference 10

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source=arxiv_source observed=2026-08-15T21:06:47.661911Z digest=sha256:9b885843a41970aafa5dc7a3c4a7b90544629f5c624bd1ef51f28fe3c5b891fa

Observation 5f36d7ca-122e-4377-9036-fda1bd6cbee3 · outbound

This paper cites Gonzalez, Hao Zhang, and Ion Stoica.

Improve Rule Retrieval and Reasoning with Self-Induction and Relevance ReEstimate Gonzalez, Hao Zhang, and Ion Stoica

Reference 11

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source=arxiv_source observed=2026-08-15T21:06:47.666854Z digest=sha256:00019945503c4260528278892d301d9eb428d8337e3aceaf75d424fa76e9df21

Observation 9de03211-168d-40a8-9f2d-2ffaa60b8da5 · outbound

This paper cites an unresolved cited work.

Improve Rule Retrieval and Reasoning with Self-Induction and Relevance ReEstimate Unresolved cited work

Reference 12

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Observation 07c1ad30-e26b-431e-98c2-31a2e2d8e42a · outbound

This paper cites Pyserini: An Easy-to-Use Python Toolkit to Support Replicable IR Research with Sparse and Dense Representations.

Improve Rule Retrieval and Reasoning with Self-Induction and Relevance ReEstimate Pyserini: An Easy-to-Use Python Toolkit to Support Replicable IR Research with Sparse and Dense Representations

Reference 13

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source=arxiv_source observed=2026-08-15T21:06:47.676444Z digest=sha256:ca83d9d9a9e3047da91e5f4f2d3161218035f2a7c26ee945650f803bf5f3c8be

Observation 6f8d6681-becc-416d-b854-4695fb1a933e · outbound

This paper cites an unresolved cited work.

Improve Rule Retrieval and Reasoning with Self-Induction and Relevance ReEstimate Unresolved cited work

Reference 14

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source=arxiv_source observed=2026-08-15T21:06:47.681216Z digest=sha256:10a9843ff254428b18f2045761470f1ed1f3f76e0f6bb34e8c979b21b2e2980b

Observation a610c6c8-4992-482e-91e1-aebfd210b221 · outbound

This paper cites an unresolved cited work.

Improve Rule Retrieval and Reasoning with Self-Induction and Relevance ReEstimate Unresolved cited work

Reference 15

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source=arxiv_source observed=2026-08-15T21:06:47.685652Z digest=sha256:0a9ea43720b6ffe2fc762549ef51f284d2cf5ce3d6c6a232cfcdb853b15d398e

Observation 8fd0fddc-3a3e-418b-a047-69e035afc7c2 · outbound

This paper cites an unresolved cited work.

Improve Rule Retrieval and Reasoning with Self-Induction and Relevance ReEstimate Unresolved cited work

Reference 16

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source=arxiv_source observed=2026-08-15T21:06:47.690232Z digest=sha256:c2f43cd9787194c07a1cfbdf870e464a4694b707be0297758d59902ec986c646

Observation aff7f018-430b-4e50-99b0-3d2e314a07d5 · outbound

This paper cites an unresolved cited work.

Improve Rule Retrieval and Reasoning with Self-Induction and Relevance ReEstimate Unresolved cited work

Reference 17

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source=arxiv_source observed=2026-08-15T21:06:47.694713Z digest=sha256:685e4a2a826978f7a5479c1ef60ed202d2c87470a2d188089211b7045202cdcb

Observation 691d4782-60c6-40c3-9158-daaf03f4b26b · outbound

This paper cites BERGEN: A Benchmarking Library for Retrieval-Augmented Generation.

Improve Rule Retrieval and Reasoning with Self-Induction and Relevance ReEstimate BERGEN: A Benchmarking Library for Retrieval-Augmented Generation

Reference 18

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Observation aad7382f-f1d4-484c-b386-df6696e346a1 · outbound

This paper cites Testing the General Deductive Reasoning Capacity of Large Language Models Using OOD Examples.

Improve Rule Retrieval and Reasoning with Self-Induction and Relevance ReEstimate Testing the General Deductive Reasoning Capacity of Large Language Models Using OOD Examples

Reference 19

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source=arxiv_source observed=2026-08-15T21:06:47.703788Z digest=sha256:47df3c9c26ec2a773a376ab4841b80649bc857f7373882054c17e3171db900de

Observation dacce912-abf6-4828-b047-10ecd2f3aef9 · outbound

This paper cites The Prompt Report: A Systematic Survey of Prompt Engineering Techniques.

Improve Rule Retrieval and Reasoning with Self-Induction and Relevance ReEstimate The Prompt Report: A Systematic Survey of Prompt Engineering Techniques

Reference 20

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source=arxiv_source observed=2026-08-15T21:06:47.708438Z digest=sha256:ef52fa6cd6cc7f9f3f0be010ea499ceb655690d1925b6843c645e3d6529e3eb0

Observation 7feabbb1-3f36-4946-af24-32bfd3b69164 · outbound

This paper cites Hamilton.

Improve Rule Retrieval and Reasoning with Self-Induction and Relevance ReEstimate Hamilton

Reference 21

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Observation 8bf0105a-6bcd-4dd2-a54f-624019fdf8ad · outbound

This paper cites Large language models for generating rules, yay or nay?.

Improve Rule Retrieval and Reasoning with Self-Induction and Relevance ReEstimate Large language models for generating rules, yay or nay?

Reference 22

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Observation 2d05bb7e-9dc4-4848-89ec-4976a58923de · outbound

This paper cites an unresolved cited work.

Improve Rule Retrieval and Reasoning with Self-Induction and Relevance ReEstimate Unresolved cited work

Reference 23

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source=arxiv_source observed=2026-08-15T21:06:47.722945Z digest=sha256:aa9b8c5702dc911d73e8f24348e638c421a9e0992478fd8b6269f9732a01d854

Observation 3b047400-ff7a-4a5c-bb22-ff1aa7897166 · outbound

This paper cites an unresolved cited work.

Improve Rule Retrieval and Reasoning with Self-Induction and Relevance ReEstimate Unresolved cited work

Reference 24

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-15T21:06:47.727601Z digest=sha256:655e675fc11fd24f946f689f607f232b4f21a9e02885490be5ddf42b0b4fb844

Observation dee4cf25-94f2-496e-812d-a9a03724b887 · outbound

This paper cites Beyond Instruction Following: Evaluating Inferential Rule Following of Large Language Models.

Improve Rule Retrieval and Reasoning with Self-Induction and Relevance ReEstimate Beyond Instruction Following: Evaluating Inferential Rule Following of Large Language Models

Reference 25

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Observation 753aeff1-3dde-4095-bd76-7d1ce1123cf0 · outbound

This paper cites an unresolved cited work.

Improve Rule Retrieval and Reasoning with Self-Induction and Relevance ReEstimate Unresolved cited work

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Observation 44359288-6b1e-486c-be70-16677315a327 · outbound

This paper cites an unresolved cited work.

Improve Rule Retrieval and Reasoning with Self-Induction and Relevance ReEstimate Unresolved cited work

Reference 27

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Observation 72b9913f-54a5-4f9b-8f76-59973fd04193 · outbound

This paper cites an unresolved cited work.

Improve Rule Retrieval and Reasoning with Self-Induction and Relevance ReEstimate Unresolved cited work

Reference 28

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Observation b77c2d9f-aa6d-4424-9952-675d68b80415 · outbound

This paper cites an unresolved cited work.

Improve Rule Retrieval and Reasoning with Self-Induction and Relevance ReEstimate Unresolved cited work

Reference 29

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source=arxiv_source observed=2026-08-15T21:06:47.751566Z digest=sha256:812e1fbce8b6036aef2fc6966f06d165a2549f6439402ac1d1cfc94af5511f82

Observation 28282395-1602-4699-b9b8-055e327a1357 · outbound

This paper cites an unresolved cited work.

Improve Rule Retrieval and Reasoning with Self-Induction and Relevance ReEstimate Unresolved cited work

Reference 30

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Observation 5fd9c44a-a882-4b69-bb27-342317f2ee70 · outbound

This paper cites an unresolved cited work.

Improve Rule Retrieval and Reasoning with Self-Induction and Relevance ReEstimate Unresolved cited work

Reference 31

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Observation 284fac43-68c8-4fb8-9074-7bcbce6a7c78 · outbound

This paper cites Symbolic Working Memory Enhances Language Models for Complex Rule Application.

Improve Rule Retrieval and Reasoning with Self-Induction and Relevance ReEstimate Symbolic Working Memory Enhances Language Models for Complex Rule Application

Reference 32

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Observation 24c66c84-3ea1-4ecc-928e-35eb313ac6dd · outbound

This paper cites RuleAlign: Making Large Language Models Better Physicians with Diagnostic Rule Alignment.

Improve Rule Retrieval and Reasoning with Self-Induction and Relevance ReEstimate RuleAlign: Making Large Language Models Better Physicians with Diagnostic Rule Alignment

Reference 33

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source=arxiv_source observed=2026-08-15T21:06:47.769786Z digest=sha256:bb02abe8f9b8c388355bea6539aae1f109fe387c93f24fb0d84e5b02e58e3f14

Observation c101dfd2-81eb-44fc-8369-94ecd3220ddb · outbound

This paper cites Chi, Quoc V Le, and Denny Zhou.

Improve Rule Retrieval and Reasoning with Self-Induction and Relevance ReEstimate Chi, Quoc V Le, and Denny Zhou

Reference 34

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source=arxiv_source observed=2026-08-15T21:06:47.774513Z digest=sha256:9fff9d94cc9cb5627f7dfb95af36bbf1b8ecd7045d979719acdaecedc0839da7

Observation b2cb3a9a-ad01-472a-86b5-19ac04af2cbc · outbound

This paper cites CAIL2018: A Large-Scale Legal Dataset for Judgment Prediction.

Improve Rule Retrieval and Reasoning with Self-Induction and Relevance ReEstimate CAIL2018: A Large-Scale Legal Dataset for Judgment Prediction

Reference 35

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Observation fa879515-88bd-4f44-b67f-d637183336bd · outbound

This paper cites C-Pack: Packed Resources For General Chinese Embeddings.

Improve Rule Retrieval and Reasoning with Self-Induction and Relevance ReEstimate C-Pack: Packed Resources For General Chinese Embeddings

Reference 36

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source=arxiv_source observed=2026-08-15T21:06:47.784049Z digest=sha256:13d67131750ae3bf6024c6d5f6fed76c6803ef2ba388d8dd74f307e92da9f186

Observation b96d16d8-b157-4da5-98b9-7811402291b0 · outbound

This paper cites Qwen2 Technical Report.

Improve Rule Retrieval and Reasoning with Self-Induction and Relevance ReEstimate Qwen2 Technical Report

Reference 37

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source=arxiv_source observed=2026-08-15T21:06:47.788738Z digest=sha256:aea2c8f9d531d1a4c77beb35aac1512df65a8999f693be8465f7989b1a7353f0

Observation edfd6b15-55b8-4ef4-926b-bd008a49016f · outbound

This paper cites an unresolved cited work.

Improve Rule Retrieval and Reasoning with Self-Induction and Relevance ReEstimate Unresolved cited work

Reference 38

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:06:47.793874Z digest=sha256:acb3b109b5ebf18cb7f22b61065bab6590d98e88f888938b5e6203ad7334833e

Observation dfc3a979-0986-4f72-8b26-6a9199b0f616 · outbound

This paper cites an unresolved cited work.

Improve Rule Retrieval and Reasoning with Self-Induction and Relevance ReEstimate Unresolved cited work

Reference 39

Resolution
unresolved
raw_fallback, observed 2026-08-15T21:06:48.355067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-15T21:06:47.799065Z digest=sha256:34b7d9e3a29c41e1a1391e29dba7b6f9b29ced8489559619d775b329394bdb18

Observation 73379126-7999-484a-9059-9da810172b36 · outbound

This paper cites an unresolved cited work.

Improve Rule Retrieval and Reasoning with Self-Induction and Relevance ReEstimate Unresolved cited work

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-15T21:06:47.803497Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:06:47.803497Z digest=sha256:11996fbe16e06fdc2ce19055023402467e82d579695376c07f52dd4f95944726

Observation a7739e2f-ea6d-43b9-ad81-b4b99d86008a · outbound

This paper cites an unresolved cited work.

Improve Rule Retrieval and Reasoning with Self-Induction and Relevance ReEstimate Unresolved cited work

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-15T21:06:47.808885Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:06:47.808885Z digest=sha256:0bb87fd7b88f85426897c1f32201cc8b3b756258e32402db9b2ec806f2356200

Observation 961a7803-9b6c-4566-bbbb-cd498cdf97cd · outbound

This paper cites A Survey of Large Language Models.

Improve Rule Retrieval and Reasoning with Self-Induction and Relevance ReEstimate A Survey of Large Language Models

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-15T21:06:47.813451Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:06:47.813451Z digest=sha256:cf3b18c8735592c666f56bfe239c11c4de4f3365d6a7e568e688c7571a4b1430

Observation 379aed47-d625-41da-bdcf-76f22f1393c2 · outbound

This paper cites A Comprehensive Survey on Pretrained Foundation Models: A History from BERT to ChatGPT.

Improve Rule Retrieval and Reasoning with Self-Induction and Relevance ReEstimate A Comprehensive Survey on Pretrained Foundation Models: A History from BERT to ChatGPT

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-15T21:06:47.818193Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:06:47.818193Z digest=sha256:5f371032293cf2caa8b037ee596ba18497e392ec12d110881f3a13b2b456df21

Observation 9d3f1e39-3235-4e46-8973-d209bf60ace2 · outbound

This paper cites an unresolved cited work.

Improve Rule Retrieval and Reasoning with Self-Induction and Relevance ReEstimate Unresolved cited work

Reference 44

Resolution
unresolved
raw_fallback, observed 2026-08-15T21:06:48.339200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-15T21:06:47.822738Z digest=sha256:f442a6a303bd642be430182086c82a4862ac154b017d4ff6b8f1a36da785e0b1

Observation 319190e1-4da3-4ce0-b92d-b984c8dfdbdf · outbound

This paper cites online" 'onlinestring :=.

Improve Rule Retrieval and Reasoning with Self-Induction and Relevance ReEstimate online" 'onlinestring :=

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-15T21:06:47.827179Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:06:47.827179Z digest=sha256:965b1ab0398ba91465bc4ea84098b1c246cfc301b8b5f2b0cad19e9b6c9a9914

Observation 90ce8b40-b2e2-4b09-8c22-158b14599f5f · outbound

This paper cites write newline.

Improve Rule Retrieval and Reasoning with Self-Induction and Relevance ReEstimate write newline

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-15T21:06:47.832223Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:06:47.832223Z digest=sha256:3690ec2534309e0ba0460b23d6014fefc6927e9d8452eb347522a73e458933de

Pith citing papers

No inbound Pith citation observations are available.