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Paper Citation Record · LEDGER

How well do Large Language Models perform in Arithmetic tasks?

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2304.02015.

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

pith.paper-citation-record.v1
2304.02015 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T04:32:43.086678Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-28T23:52:49.758119Z

Reference resolution

0 of 0 outbound references displayed

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  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 4ce92760-6329-4722-a83f-a8c50b1dc9b0 · inbound

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

Scaling Relationship on Learning Mathematical Reasoning with Large Language Models How well do Large Language Models perform in Arithmetic tasks?

Reference 103

Resolution
verified exact
arxiv_id, observed 2026-05-15T00:22:11.044608Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-15T00:22:10.974593Z digest=sha256:31d8cc5364ed74e5aa717b633d4f75911883a357d94f52c74aaef478712f7e8a

Observation 82e21b28-e62c-40e4-9576-c40b6235649d · inbound

Code Simulation as a Proxy for High-order Tasks in Large Language Models cites this paper.

Code Simulation as a Proxy for High-order Tasks in Large Language Models How well do Large Language Models perform in Arithmetic tasks?

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-09T04:32:43.086678Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T04:32:43.086678Z digest=sha256:0986f731907d196afd843f2354b0dcb254785320343919d2b5256ae0a3ff1aa2

Observation cdf1b3b7-0ef0-4a28-98f7-d25e3ee8bb00 · inbound

Ignore the KL Penalty! Boosting Exploration on Critical Tokens to Enhance RL Fine-Tuning cites this paper.

Ignore the KL Penalty! Boosting Exploration on Critical Tokens to Enhance RL Fine-Tuning How well do Large Language Models perform in Arithmetic tasks?

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-08T15:11:08.200325Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T15:11:08.200325Z digest=sha256:fcbcb7ca28240f62d79f967ed81bcea3cea03282b64c67227e45c621dff3ab10

Observation aa43d4a0-dd03-4830-8394-52bec8d3ab11 · inbound

Evaluating the Meta- and Object-Level Reasoning of Large Language Models for Question Answering cites this paper.

Evaluating the Meta- and Object-Level Reasoning of Large Language Models for Question Answering How well do Large Language Models perform in Arithmetic tasks?

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-07T18:31:46.677098Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T18:31:46.677098Z digest=sha256:ddf21795335ffb0125aeb790028c1d6cbe74096726643229bb042c33951a3048

Observation c03f2d15-1fd9-43c4-a042-e11062ef6b4e · inbound

Towards Interpretable Time Series Foundation Models cites this paper.

Towards Interpretable Time Series Foundation Models How well do Large Language Models perform in Arithmetic tasks?

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-06T18:44:42.016394Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:44:42.016394Z digest=sha256:6d83dc72afa15974df9559e9b8ae772888578ab454958eecc2686ef1ee6b0e7f

Observation c6e8372f-62d1-4f30-83b1-06ac46e77f95 · inbound

TOPReward: Token Probabilities as Hidden Zero-Shot Rewards for Robotics cites this paper.

TOPReward: Token Probabilities as Hidden Zero-Shot Rewards for Robotics How well do Large Language Models perform in Arithmetic tasks?

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-02T21:43:10.979941Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T21:43:10.979941Z digest=sha256:efec9c00c11395263b3efa06bcbf54742dd44f05e3894cebade81d426dd8f2d4

Observation d8f9aa90-b92b-4f81-8b3f-e0ff2aa7fe9b · inbound

Evolvable Embodied Agent for Robotic Manipulation via Long Short-Term Reflection and Optimization cites this paper.

Evolvable Embodied Agent for Robotic Manipulation via Long Short-Term Reflection and Optimization How well do Large Language Models perform in Arithmetic tasks?

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-10T13:05:24.471866Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T13:04:48.932945Z digest=sha256:84e7d1e09f6159f0c32a314caf4f6fc9196b38d8e221db3d02455c5fd6a83b91

Observation 39899214-f2b2-42cb-9880-8350760bd784 · inbound

Multiplication in Multimodal LLMs: Computation with Text, Image, and Audio Inputs cites this paper.

Multiplication in Multimodal LLMs: Computation with Text, Image, and Audio Inputs How well do Large Language Models perform in Arithmetic tasks?

Reference 33

Resolution
verified exact
arxiv_id, observed 2026-05-11T11:51:04.159424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-10T04:31:01.954955Z digest=sha256:11e4d4d8592bcffa6724099d4b8d7fd833dcb66b8cb137d745c231502beaaaef

Observation 1fbcbf65-1b53-4548-a914-d6a85838ceb6 · inbound

Mathematical Reasoning in Large Language Models: Benchmarks, Architectures, Evaluation, and Open Challenges cites this paper.

Mathematical Reasoning in Large Language Models: Benchmarks, Architectures, Evaluation, and Open Challenges How well do Large Language Models perform in Arithmetic tasks?

Reference 7

Resolution
unresolved
no resolver link, observed 2026-07-12T16:29:56.962393Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T16:29:56.962393Z digest=sha256:b7b34f41b35b99aa2421e5b286b335dce7ee7a67999bddd0f003a15c88048dc1

Observation 3bbdb18a-e4e0-478c-9f07-38ec186d1c2b · inbound

DEL: Digit Entropy Loss for Numerical Learning of Large Language Models cites this paper.

DEL: Digit Entropy Loss for Numerical Learning of Large Language Models How well do Large Language Models perform in Arithmetic tasks?

Reference 32

Resolution
verified exact
arxiv_id, observed 2026-05-21T07:39:49.489389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-21T07:35:22.992256Z digest=sha256:bf7658bc17384c9d712ec24a87cac4a27e680927cb5e4c1fd0de2eddf6e81223

Observation 1031672a-1945-4256-8bc2-67981ce73f84 · inbound

The Shape of Addition: Geometric Structures of Arithmetic in Large Language Models cites this paper.

The Shape of Addition: Geometric Structures of Arithmetic in Large Language Models How well do Large Language Models perform in Arithmetic tasks?

Reference 41

Resolution
metadata mismatch
arxiv_id, observed 2026-06-28T23:52:49.759382Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-28T23:45:16.789926Z digest=sha256:8051bc7264b06c8b78eab0f72944bda68c8e2dcb1171e831100361d08eecf65c