Pith. sign in

Paper Citation Record · LEDGER

Eliminating Hallucination-Induced Errors in LLM Code Generation with Functional Clustering

As of 16 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 2 inbound Pith citation observations for arXiv:2506.11021.

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

pith.paper-citation-record.v1
2506.11021 v1

Coverage vector

measured 27 of 27 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:56:36.046570Z

measured 29 of 29 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-03T09:01:48.501745Z

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

27 of 27 outbound references displayed

  • verified exact0
  • verified fuzzy6
  • unresolved20
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

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

Outbound references

Observation adcb272a-9a35-4fa4-be25-95c344662058 · outbound

This paper cites The claude 3 model family: Opus, sonnet, haiku, March 2024.

Eliminating Hallucination-Induced Errors in LLM Code Generation with Functional Clustering The claude 3 model family: Opus, sonnet, haiku, March 2024

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:56:36.506248Z

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=pdf_text observed=2026-08-15T20:56:35.950695Z digest=sha256:396c195d4ff29a8e8cccc224116beb2e672e3cfcd0a5f2e7247550384d9c6890

Observation 6b4bf681-33d7-42d8-b2e8-46a1d89dd279 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

Eliminating Hallucination-Induced Errors in LLM Code Generation with Functional Clustering Evaluating Large Language Models Trained on Code

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-15T20:56:35.954682Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:56:35.954682Z digest=sha256:239a1812395929a7db053c0d8aa2d373be1c0e6603bf273df213a4419f49a575

Observation 8dfbf4b4-f180-428f-af56-1b460d69d2f1 · outbound

This paper cites Calibration of pre-trained transformers.

Eliminating Hallucination-Induced Errors in LLM Code Generation with Functional Clustering Calibration of pre-trained transformers

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-15T20:56:35.958511Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:56:35.958511Z digest=sha256:cacd00d21289ce6679c3819fdebb375c2b05ecec5c9b7d3cf354ab7349582fcf

Observation d83f8731-8d89-40f4-bb5d-1bf2aed3d27c · outbound

This paper cites Detecting hallucinations in large language models using semantic entropy.

Eliminating Hallucination-Induced Errors in LLM Code Generation with Functional Clustering Detecting hallucinations in large language models using semantic entropy

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-15T20:56:35.962252Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:56:35.962252Z digest=sha256:02aed8af42ada2f7fb90e24a8f4581e09ef114c92872ad715da40b3304e85beb

Observation bc338a2c-93e0-464e-b7a3-db07acce918c · outbound

This paper cites A survey on hallucination in large language models: Principles, taxonomy, challenges, and open questions.

Eliminating Hallucination-Induced Errors in LLM Code Generation with Functional Clustering A survey on hallucination in large language models: Principles, taxonomy, challenges, and open questions

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-15T20:56:35.966780Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:56:35.966780Z digest=sha256:1f3af028182cd6ec8cd0164e062ce7f54815d5ac20f86e1a3bba40de098f7e0c

Observation 0936f32b-d05f-41a4-a627-1ec40b352c56 · outbound

This paper cites LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code.

Eliminating Hallucination-Induced Errors in LLM Code Generation with Functional Clustering LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-15T20:56:35.971110Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:56:35.971110Z digest=sha256:4db7fc255bb3f29cf79262d0d3efd9c1f68de74fd3b1d82ffa1a6b38e5cad28c

Observation f7635375-d102-44ba-b47d-3e8e00838381 · outbound

This paper cites Language Models (Mostly) Know What They Know.

Eliminating Hallucination-Induced Errors in LLM Code Generation with Functional Clustering Language Models (Mostly) Know What They Know

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-15T20:56:35.975550Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:56:35.975550Z digest=sha256:c62e80789bddbc71f2593cbdc60ea7bfd3beac7d90bc3548a9efc6cb1527d5c3

Observation 77ac6d32-49ca-4561-8b9d-c2d97454d86a · outbound

This paper cites Semantic uncertainty: Linguistic invari- ances for uncertainty estimation in natural language generation.

Eliminating Hallucination-Induced Errors in LLM Code Generation with Functional Clustering Semantic uncertainty: Linguistic invari- ances for uncertainty estimation in natural language generation

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:56:36.494338Z

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=pdf_text observed=2026-08-15T20:56:35.979392Z digest=sha256:b2d4e055064ea79876be546e709ad5deddc24688eb176eb616ff8d099d96125c

Observation 436d1e5a-35e0-4f2f-a0a4-3eebe71c390a · outbound

This paper cites Teaching models to express their uncertainty in words.

Eliminating Hallucination-Induced Errors in LLM Code Generation with Functional Clustering Teaching models to express their uncertainty in words

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:56:36.482929Z

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=pdf_text observed=2026-08-15T20:56:35.982966Z digest=sha256:694ea33003e5b16bc3e159a48306ecd8b4e0314489826d3d3c0a27eb9d3c23d7

Observation b8cf6b47-d3d1-4bc4-9afb-4c16211120c2 · outbound

This paper cites Exploring and evaluating hallucinations in llm-powered code generation,.

Eliminating Hallucination-Induced Errors in LLM Code Generation with Functional Clustering Exploring and evaluating hallucinations in llm-powered code generation,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:56:36.472279Z

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=pdf_text observed=2026-08-15T20:56:35.986564Z digest=sha256:0afd11a3a551b76a42556322cb20b6acdf90467c303f24b8fe3f01bdbb84f26c

Observation d9b85b58-0a03-4315-8e7c-08eeff93f1c4 · outbound

This paper cites Litcab: Lightweight language model calibration over short and long-form responses.

Eliminating Hallucination-Induced Errors in LLM Code Generation with Functional Clustering Litcab: Lightweight language model calibration over short and long-form responses

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:56:36.461030Z

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=pdf_text observed=2026-08-15T20:56:35.993683Z digest=sha256:eb17caa16264b505d7fd32f1bbfbaf3d548cd21cf15c3aedba1ff0da2579663e

Observation b340f3ae-d3e4-40ff-b65b-93201a4cd1b6 · outbound

This paper cites Estimating LLM Uncertainty with Evidence.

Eliminating Hallucination-Induced Errors in LLM Code Generation with Functional Clustering Estimating LLM Uncertainty with Evidence

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-15T20:56:35.997593Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:56:35.997593Z digest=sha256:5f81fcb1ce188174ee88281927b430865888c3a64abd7c6c229236f543ab53c0

Observation 368616d3-32c0-4e08-89e9-647127ea4802 · outbound

This paper cites Introducing gpt-4.1 in the api, April 2025.

Eliminating Hallucination-Induced Errors in LLM Code Generation with Functional Clustering Introducing gpt-4.1 in the api, April 2025

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-15T20:56:36.001384Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:56:36.001384Z digest=sha256:88d18c326322184d3d93cb554bf197f67f6baa7f52273bed30478caf4d9b9f3e

Observation c186334f-24f3-41d9-9005-30873d100299 · outbound

This paper cites GPT-4o System Card.

Eliminating Hallucination-Induced Errors in LLM Code Generation with Functional Clustering GPT-4o System Card

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-15T20:56:36.004620Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:56:36.004620Z digest=sha256:73b95b915425b9f1a9063768cc48486275b08af012bb7c87027fa6374303d3a8

Observation f1cc0fa0-e105-4927-ab05-64f70375c72a · outbound

This paper cites Competitive Programming with Large Reasoning Models.

Eliminating Hallucination-Induced Errors in LLM Code Generation with Functional Clustering Competitive Programming with Large Reasoning Models

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-15T20:56:36.009540Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:56:36.009540Z digest=sha256:cccefd2f14ffdad57669804ce5ff2da61b775de4701e840e2a1b8b75be166924

Observation f5aecc70-65a4-416c-8b99-7234ef6a4854 · outbound

This paper cites Semantic Density: Uncertainty Quantification for Large Language Models through Confidence Measurement in Semantic Space.

Eliminating Hallucination-Induced Errors in LLM Code Generation with Functional Clustering Semantic Density: Uncertainty Quantification for Large Language Models through Confidence Measurement in Semantic Space

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-15T20:56:36.013219Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:56:36.013219Z digest=sha256:a4606222e663c0965a3cc22db28614f7c8312fc50562ac280efa6a317cb82251

Observation 5751acfa-5cc0-4769-b2a1-7139f6c68bb4 · outbound

This paper cites Assessing Correctness in LLM-Based Code Generation via Uncertainty Estimation.

Eliminating Hallucination-Induced Errors in LLM Code Generation with Functional Clustering Assessing Correctness in LLM-Based Code Generation via Uncertainty Estimation

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-15T20:56:36.016848Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:56:36.016848Z digest=sha256:3c4ab47d5d2c4ac5ada1c22dd3110bd2447124cd7c7c3d046886cfde63cd254e

Observation b9da7232-80ca-412e-a5da-b6aeaa96e25d · outbound

This paper cites Magis: Llm-based multi-agent framework for github issue resolution.

Eliminating Hallucination-Induced Errors in LLM Code Generation with Functional Clustering Magis: Llm-based multi-agent framework for github issue resolution

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:56:36.441072Z

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=pdf_text observed=2026-08-15T20:56:36.020232Z digest=sha256:b61d3b85a42143285d9bf3a6f23995d17a06551a7b632fa54c81ab0db0327136

Observation 8b627423-8e32-4eb4-bdc4-f41efd45c907 · outbound

This paper cites an unresolved cited work.

Eliminating Hallucination-Induced Errors in LLM Code Generation with Functional Clustering Unresolved cited work

Reference 19

Resolution
malformed identifier
no resolver link, observed 2026-08-15T20:56:36.023534Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:56:36.023534Z digest=sha256:da2fa28660123aad3562f505f9ffc05374c06715bcea03716977211d6debd78f

Observation a110b054-5ca4-4f96-9d6f-e4e7039785e8 · outbound

This paper cites CodeHalu: Investigating Code Hallucinations in LLMs via Execution-based Verification.

Eliminating Hallucination-Induced Errors in LLM Code Generation with Functional Clustering CodeHalu: Investigating Code Hallucinations in LLMs via Execution-based Verification

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-15T20:56:36.027222Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:56:36.027222Z digest=sha256:7f2291c53e4fdfa2ec26dbf655885ab407746382b6c4ae3e7e6926fa9cef7e71

Observation 6a2dcf32-4820-4ce5-a664-1e197ee64ed3 · outbound

This paper cites A Comprehensive Survey of Hallucination Mitigation Techniques in Large Language Models.

Eliminating Hallucination-Induced Errors in LLM Code Generation with Functional Clustering A Comprehensive Survey of Hallucination Mitigation Techniques in Large Language Models

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-15T20:56:36.030935Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:56:36.030935Z digest=sha256:6bb58861c740c5d28904fcdbf7e44eb2bc275b29d064aa3488fc7badf08c0957

Observation b15242db-5c6e-41e1-b5cb-d49d17bae170 · outbound

This paper cites Llm perfor- mance assessment in computer science graduate entrance exams.

Eliminating Hallucination-Induced Errors in LLM Code Generation with Functional Clustering Llm perfor- mance assessment in computer science graduate entrance exams

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-15T20:56:36.034811Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:56:36.034811Z digest=sha256:788b344c1baf750dd8bd75b6cb9df7564e20431875581b1abb40d9903257cb55

Observation cc91b9b8-7e47-407d-955b-2d201c7cdda9 · outbound

This paper cites Can LLMs Express Their Uncertainty? An Empirical Evaluation of Confidence Elicitation in LLMs.

Eliminating Hallucination-Induced Errors in LLM Code Generation with Functional Clustering Can LLMs Express Their Uncertainty? An Empirical Evaluation of Confidence Elicitation in LLMs

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-15T20:56:36.037381Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:56:36.037381Z digest=sha256:0487056e18db67b50e5ada9c392397a440b25b85f15a5f51268609e35f8c8826

Observation af0f3b83-99a5-4799-8bd5-1c05523a718e · outbound

This paper cites Mitigating LLM Hallucinations via Conformal Abstention.

Eliminating Hallucination-Induced Errors in LLM Code Generation with Functional Clustering Mitigating LLM Hallucinations via Conformal Abstention

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-15T20:56:36.040456Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:56:36.040456Z digest=sha256:0757c4fb2e91df4d9e1f4d6eaa97e68cf011a02c02303186c605a32e9337b750

Observation cacc16af-496c-4296-8c9f-7faa68f42645 · outbound

This paper cites Benchmarking LLMs via Uncertainty Quantification.

Eliminating Hallucination-Induced Errors in LLM Code Generation with Functional Clustering Benchmarking LLMs via Uncertainty Quantification

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-15T20:56:36.043524Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:56:36.043524Z digest=sha256:604c91199dc4b5ac5365b41a48a502b06938539958f4d42db37b525a36b2981e

Observation 4b82cfb8-3dc3-4625-8a40-2b5877b1b911 · outbound

This paper cites A Survey of Large Language Models.

Eliminating Hallucination-Induced Errors in LLM Code Generation with Functional Clustering A Survey of Large Language Models

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-15T20:56:36.046570Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:56:36.046570Z digest=sha256:4db3caafeb66cf9565464368cc8b2279393e655cccaf8a621600de7744984d91

Observation dc1f39d6-07f1-4763-82ec-bd93c09a9328 · outbound

This paper cites an unresolved cited work.

Eliminating Hallucination-Induced Errors in LLM Code Generation with Functional Clustering Unresolved cited work

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-15T20:56:35.990105Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:56:35.990105Z digest=sha256:b98299e9dbd3e5231ad20b06d3748b56f8ead5e396a088421de88adf027799b8

Pith citing papers

Observation cbc18774-863a-4c44-868b-10128397a22d · inbound

Ensemble-Based Uncertainty Estimation for Code Correctness Estimation cites this paper.

Ensemble-Based Uncertainty Estimation for Code Correctness Estimation Eliminating Hallucination-Induced Errors in LLM Code Generation with Functional Clustering

Reference 35

Resolution
verified exact
arxiv_id, observed 2026-05-14T22:53:14.101816Z

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=pdf_text observed=2026-05-14T22:52:58.524934Z digest=sha256:03135030eac81a7dbba42718a607b1bbdfe0feac5c4d57214e1a832d410b3644

Observation 11f700b5-386e-4373-8d2e-cb35008784d0 · inbound

Underspecification does not imply Incoherence: The Risks of Semantic Collapse in Coding Models cites this paper.

Underspecification does not imply Incoherence: The Risks of Semantic Collapse in Coding Models Eliminating Hallucination-Induced Errors in LLM Code Generation with Functional Clustering

Reference 23

Resolution
verified exact
arxiv_id, observed 2026-07-03T09:07:46.997095Z

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=pdf_text observed=2026-07-03T09:01:48.501745Z digest=sha256:d2cff4b2a96b7f3889ed4ff4b3662b14336ba7dce20619b8ee9c7819c04f58d0