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Paper Citation Record · LEDGER

LOGICPO: Efficient Translation of NL-based Logical Problems to FOL using LLMs and Preference Optimization

As of 20 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 1 inbound Pith citation observation for arXiv:2506.18383.

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

pith.paper-citation-record.v1
2506.18383 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:54:30.311297Z

measured 25 of 25 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-28T14:29:43.379840Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

24 of 24 outbound references displayed

  • verified exact3
  • verified fuzzy5
  • unresolved15
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation dadb5a6b-b771-423a-9bd6-47e8cb55365c · outbound

This paper cites KTO: Model Alignment as Prospect Theoretic Optimization.

LOGICPO: Efficient Translation of NL-based Logical Problems to FOL using LLMs and Preference Optimization KTO: Model Alignment as Prospect Theoretic Optimization

Reference 5

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Observation d1e55af5-37c6-4633-bd00-ed29ba32111f · outbound

This paper cites The Llama 3 Herd of Models.

LOGICPO: Efficient Translation of NL-based Logical Problems to FOL using LLMs and Preference Optimization The Llama 3 Herd of Models

Reference 6

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source=pdf_text observed=2026-08-15T18:54:30.242928Z digest=sha256:4a56efb862f6706b0d3d7430691273d061015167a534a0a48e5b688d42f5ac25

Observation a1adb26a-ab4c-4db6-b047-6a193a80b76c · outbound

This paper cites Mistral 7B.

LOGICPO: Efficient Translation of NL-based Logical Problems to FOL using LLMs and Preference Optimization Mistral 7B

Reference 7

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source=pdf_text observed=2026-08-15T18:54:30.247454Z digest=sha256:6dbfbd7985dcfdee5bfa42a8c767c15483eb422757f208e0b4dce9628463259d

Observation d44dadbf-3869-4b43-a7cb-d3ca64082543 · outbound

This paper cites Mistral 7B.

LOGICPO: Efficient Translation of NL-based Logical Problems to FOL using LLMs and Preference Optimization Mistral 7B

Reference 8

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source=pdf_text observed=2026-08-15T18:54:30.251866Z digest=sha256:39fb91a4fba7af2cedcbb2fdb9510880f76108312c30fd67cd8f29600df19ee3

Observation 4fff75c4-67b7-4a1b-9649-f96579568790 · outbound

This paper cites an unresolved cited work.

LOGICPO: Efficient Translation of NL-based Logical Problems to FOL using LLMs and Preference Optimization Unresolved cited work

Reference 10

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source=pdf_text observed=2026-08-15T18:54:30.259880Z digest=sha256:1521986684400404517ffbc559d9120f3431c09ab4c0d8b7663bbe5578550bf9

Observation 5fe2ce00-2a27-4bae-9a01-1d0a06521d34 · outbound

This paper cites URL https://doi.org/10.

LOGICPO: Efficient Translation of NL-based Logical Problems to FOL using LLMs and Preference Optimization URL https://doi.org/10

Reference 11

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no resolver link, observed 2026-08-15T18:54:30.263650Z

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source=pdf_text observed=2026-08-15T18:54:30.263650Z digest=sha256:ffde9036e679a5870d4642e6ef1067f4c0cc1dfa45c703cfcbd21b24ca17480c

Observation 116b68f0-51c2-494a-b27b-717dedb21ccd · outbound

This paper cites URL https://aclanthology.org/2022.coling-1.481.

LOGICPO: Efficient Translation of NL-based Logical Problems to FOL using LLMs and Preference Optimization URL https://aclanthology.org/2022.coling-1.481

Reference 12

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verified fuzzy
raw_fallback, observed 2026-08-15T18:54:30.771646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T18:54:30.267309Z digest=sha256:244716534fe69f421558653354702410e7706b14b08c0c7dd7babd288b1f7b1d

Observation c7a55a19-c026-404d-9d44-1d2304ce5fb8 · outbound

This paper cites Arithmetic Without Algorithms: Language Models Solve Math With a Bag of Heuristics.

LOGICPO: Efficient Translation of NL-based Logical Problems to FOL using LLMs and Preference Optimization Arithmetic Without Algorithms: Language Models Solve Math With a Bag of Heuristics

Reference 13

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source=pdf_text observed=2026-08-15T18:54:30.271111Z digest=sha256:84947622385be32b4f06418be7efb356121497baf6ab9260ac2011b7c44a82cb

Observation 279e1922-afe4-40b7-8b91-e13b961a445c · outbound

This paper cites EMNLP-MAIN.313.

LOGICPO: Efficient Translation of NL-based Logical Problems to FOL using LLMs and Preference Optimization EMNLP-MAIN.313

Reference 14

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source=pdf_text observed=2026-08-15T18:54:30.274494Z digest=sha256:6377dc870312d17693e34e1c0c59de11f43b8ee5b6c0079823f078503e9828c3

Observation aa19c657-3cc2-43e2-9dbf-76342822e65d · outbound

This paper cites URL https://doi.org/10.18653/v1/2023.findings-emnlp.248.

LOGICPO: Efficient Translation of NL-based Logical Problems to FOL using LLMs and Preference Optimization URL https://doi.org/10.18653/v1/2023.findings-emnlp.248

Reference 15

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source=pdf_text observed=2026-08-15T18:54:30.277846Z digest=sha256:24bb2d612302adc3d3731b43b4d0db3afb7f264b912eec3c9da027e7d2aec047

Observation a23f518a-38dd-41a2-b984-523bde8d810d · outbound

This paper cites Direct Preference Optimization: Your Language Model is Secretly a Reward Model.

LOGICPO: Efficient Translation of NL-based Logical Problems to FOL using LLMs and Preference Optimization Direct Preference Optimization: Your Language Model is Secretly a Reward Model

Reference 16

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Observation 1c5ef0b2-a9a2-4a04-8f99-333eb9e9e9f9 · outbound

This paper cites Arpit Sharma, Nguyen Ha Vo, Somak Aditya, and Chitta Baral.

LOGICPO: Efficient Translation of NL-based Logical Problems to FOL using LLMs and Preference Optimization Arpit Sharma, Nguyen Ha Vo, Somak Aditya, and Chitta Baral

Reference 17

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raw_fallback, observed 2026-08-15T18:54:30.761066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T18:54:30.284198Z digest=sha256:60270d2a998e4635c6b16ea0b9e5665ac595d85b0e4e474eeffbe4f9bfa53bca

Observation 45c2e073-8186-490a-8be3-156fa420dcd0 · outbound

This paper cites Gemma 2: Improving Open Language Models at a Practical Size.

LOGICPO: Efficient Translation of NL-based Logical Problems to FOL using LLMs and Preference Optimization Gemma 2: Improving Open Language Models at a Practical Size

Reference 19

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source=pdf_text observed=2026-08-15T18:54:30.292666Z digest=sha256:fbe19a061396874bc79e584343795f3f8e3a003a97ebfb9b6762dde3fba5ddf5

Observation 7c295393-d544-4117-b08f-f2f06ceea373 · outbound

This paper cites Dick, and Anton van den Hengel.

LOGICPO: Efficient Translation of NL-based Logical Problems to FOL using LLMs and Preference Optimization Dick, and Anton van den Hengel

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T18:54:30.296937Z digest=sha256:d421652f70ea92714754fbfc58dc94ac3cdbdfa2348d56deac38c93d1e4b9d73

Observation cc649e5a-e970-4266-9a25-ebc4efd490b7 · outbound

This paper cites doi: 10.18653/v1/2024.acl-long.375.

LOGICPO: Efficient Translation of NL-based Logical Problems to FOL using LLMs and Preference Optimization doi: 10.18653/v1/2024.acl-long.375

Reference 22

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source=pdf_text observed=2026-08-15T18:54:30.303790Z digest=sha256:1c5d4d245e173f75d514a51dd206717e074fa919fb0864d18b6c3311423bd45b

Observation e694105b-2f35-4e6c-a3bd-8e6dcdd9ce02 · outbound

This paper cites A Appendix A.1 Few-shot Baseline prompts For our baseline models, we evaluate off-the-shelf models in a few-shot setting.

LOGICPO: Efficient Translation of NL-based Logical Problems to FOL using LLMs and Preference Optimization A Appendix A.1 Few-shot Baseline prompts For our baseline models, we evaluate off-the-shelf models in a few-shot setting

Reference 23

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T18:54:30.306936Z digest=sha256:9b0d330e82c74f9287a916897f3b0ff6912f255a174643fa2337b02763da421a

Observation 28df8fef-cedd-4b41-bb5c-fa8d6aea2a9b · outbound

This paper cites As the process of ProverQA creation was quite different, the high improvement of the preference optimized models underlines the generalizability of our LOGICPO dataset.

LOGICPO: Efficient Translation of NL-based Logical Problems to FOL using LLMs and Preference Optimization As the process of ProverQA creation was quite different, the high improvement of the preference optimized models underlines the generalizability of our LOGICPO dataset

Reference 24

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T18:54:30.311297Z digest=sha256:d9f56bdab01014291480a909e408964a15f0bb8908a56c070e6202a4ab694cb0

Observation 14965f1d-da49-497e-ad69-3101fca734b7 · outbound

This paper cites Open-source Frame Semantic Parsing.

LOGICPO: Efficient Translation of NL-based Logical Problems to FOL using LLMs and Preference Optimization Open-source Frame Semantic Parsing

Reference 2014

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source=pdf_text observed=2026-08-15T18:54:30.226908Z digest=sha256:5c962f5f56c48a0db8775ebe128ed6132c4507b181f931fd63cadcdb3ed24889

Observation 5faba0a5-d42c-4577-92dc-215d74f5b921 · outbound

This paper cites URLhttps://doi.org/10.1109/CVPR.2016.500.

LOGICPO: Efficient Translation of NL-based Logical Problems to FOL using LLMs and Preference Optimization URLhttps://doi.org/10.1109/CVPR.2016.500

Reference 2016

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doi, observed 2026-08-15T18:54:30.343465Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T18:54:30.300599Z digest=sha256:d0d22e461021fd8d443758e722b5805ca3d9992e518142cb14df853d3905ebb5

Observation 18a51ac2-5c2b-44bd-ab19-e352b9ca3d43 · outbound

This paper cites URLhttp://www.vldb.org/pvldb/vol13/p1737-kim.pdf.

LOGICPO: Efficient Translation of NL-based Logical Problems to FOL using LLMs and Preference Optimization URLhttp://www.vldb.org/pvldb/vol13/p1737-kim.pdf

Reference 2020

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source=pdf_text observed=2026-08-15T18:54:30.255764Z digest=sha256:3cb567acba7967a0c66867bc280abc690b4a361e9fb4aa3b9e1d769acc44bedd

Observation cf09980f-6237-433a-88f5-3cbbf8646f5d · outbound

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

LOGICPO: Efficient Translation of NL-based Logical Problems to FOL using LLMs and Preference Optimization ProofWriter: Generating Implications, Proofs, and Abductive Statements over Natural Language

Reference 2021

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source=pdf_text observed=2026-08-15T18:54:30.288031Z digest=sha256:d97fa259852ddf88e227598fa369ac3de2a2e979da640562e17b5048c5ee7629

Observation 6dea769a-f21b-4e49-bc38-a2992fe418f8 · outbound

This paper cites URLhttps://doi.org/10.24963/ijcai.2022/568.

LOGICPO: Efficient Translation of NL-based Logical Problems to FOL using LLMs and Preference Optimization URLhttps://doi.org/10.24963/ijcai.2022/568

Reference 2022

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doi, observed 2026-08-15T18:54:30.449203Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T18:54:30.234687Z digest=sha256:a15a08fb9435887e876b1e00333ba972b5b95d58170dc5723802973fc2471af4

Observation 32b67e4b-166b-44bb-ae41-bdaf065842ec · outbound

This paper cites In- terpretable amr-based question decomposition for multi-hop question answering.

LOGICPO: Efficient Translation of NL-based Logical Problems to FOL using LLMs and Preference Optimization In- terpretable amr-based question decomposition for multi-hop question answering

Reference 2023

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T18:54:30.231078Z digest=sha256:c0dc96874bb26f7d695aa3b65e6426dcd98417cdb79661cc119a7012bc420cd6

Observation 1aa34efc-bc18-4840-a3e5-7baa54ad1cba · outbound

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

LOGICPO: Efficient Translation of NL-based Logical Problems to FOL using LLMs and Preference Optimization Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone

Reference 2024

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source=pdf_text observed=2026-08-15T18:54:30.221905Z digest=sha256:de07737adb882d7111e9ba7c7517099c18ef9c734c4cf1acc1218340804c66b2

Pith citing papers

Observation 07a3f812-afc9-416e-a7cf-f4b74ec55c0d · inbound

Fixing FOLIO and MALLS: Verified Annotations and an LLM-assisted Framework to Focus Human Relabeling cites this paper.

Fixing FOLIO and MALLS: Verified Annotations and an LLM-assisted Framework to Focus Human Relabeling LOGICPO: Efficient Translation of NL-based Logical Problems to FOL using LLMs and Preference Optimization

Reference 60

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arxiv_id, observed 2026-06-28T14:32:17.690321Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-06-28T14:29:43.379840Z digest=sha256:d0753ba4e1be921382403323f2a156177e3772b62c3d5e963d50c42236801671