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Paper Citation Record · LEDGER

Mitigating Large Language Model Hallucination with Faithful Finetuning

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2406.11267.

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

pith.paper-citation-record.v1
2406.11267 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 12 of 12 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 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:41:35.299699Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T17:28:44.635985Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • 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 a3af8d04-62d3-4be0-b553-0a72efb441f8 · inbound

TruthFlow: Truthful LLM Generation via Representation Flow Correction cites this paper.

TruthFlow: Truthful LLM Generation via Representation Flow Correction Mitigating Large Language Model Hallucination with Faithful Finetuning

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-08T22:23:27.819703Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T22:23:27.819703Z digest=sha256:7d31c7d81765f2cfe94605cb3d69ba05715af61f589c9950c741d1ce681fe498

Observation 5098cfae-e73a-4342-93af-15739d74458a · inbound

LowRA: Accurate and Efficient LoRA Fine-Tuning of LLMs under 2 Bits cites this paper.

LowRA: Accurate and Efficient LoRA Fine-Tuning of LLMs under 2 Bits Mitigating Large Language Model Hallucination with Faithful Finetuning

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-08T10:26:45.439858Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T10:26:45.439858Z digest=sha256:68ab915ee4119195d1db616833ed21373effb022cdd15d0acea17c1368ff29e0

Observation 132745b5-7e99-4b31-bd3c-e73db7852ee0 · inbound

Learning Auxiliary Tasks Improves Reference-Free Hallucination Detection in Open-Domain Long-Form Generation cites this paper.

Learning Auxiliary Tasks Improves Reference-Free Hallucination Detection in Open-Domain Long-Form Generation Mitigating Large Language Model Hallucination with Faithful Finetuning

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-15T20:41:35.299699Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:41:35.299699Z digest=sha256:66496964d047552f4bce57da33d0108ce7dc94446907c52aed8f8d5889ad0acf

Observation 9e429d65-2cda-4f55-81f7-07a132fccac6 · inbound

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation cites this paper.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Mitigating Large Language Model Hallucination with Faithful Finetuning

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-07T14:48:02.849746Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:48:02.849746Z digest=sha256:ace5e6a42f023f44048c6fe1cc3d5e5926eb6f0101203cc6c4eb1198bb272785

Observation 8f524dae-8464-4392-ad7b-8baaee3e852b · inbound

From Extraction to Synthesis: Entangled Heuristics for Agent-Augmented Strategic Reasoning cites this paper.

From Extraction to Synthesis: Entangled Heuristics for Agent-Augmented Strategic Reasoning Mitigating Large Language Model Hallucination with Faithful Finetuning

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-06T16:24:05.715721Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:24:05.715721Z digest=sha256:87bce3353451eb0d695f9df0d734d293c2c43ce850f13103d8fd189df2bf34fb

Observation 2235ca12-16ac-492d-9b26-185d58d9cab0 · inbound

Exploring Causal Effect of Social Bias on Faithfulness Hallucinations in Large Language Models cites this paper.

Exploring Causal Effect of Social Bias on Faithfulness Hallucinations in Large Language Models Mitigating Large Language Model Hallucination with Faithful Finetuning

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-05T21:58:54.445386Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T21:58:54.445386Z digest=sha256:d0e3f527eb8a4f43cdd9b5a9482715927e6445e144bde249f1e40daefede1d46

Observation bb13f093-408d-45a7-a7f6-c0764a8f60d5 · inbound

HAVE: Head-Adaptive Gating and ValuE Calibration for Hallucination Mitigation in Large Language Models cites this paper.

HAVE: Head-Adaptive Gating and ValuE Calibration for Hallucination Mitigation in Large Language Models Mitigating Large Language Model Hallucination with Faithful Finetuning

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-15T16:19:39.683986Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:19:39.683986Z digest=sha256:064dc99b9f96439ed39a84e42a5ba400daca0b3f33b0f272f695297f596397ae

Observation de4ddc77-5da3-4554-8cd2-83c132b47af5 · inbound

Learning from AVA: Early Lessons from a Curated and Trustworthy Generative AI for Policy and Development Research cites this paper.

Learning from AVA: Early Lessons from a Curated and Trustworthy Generative AI for Policy and Development Research Mitigating Large Language Model Hallucination with Faithful Finetuning

Reference 40

Resolution
verified exact
arxiv_id, observed 2026-05-10T12:10:22.927760Z

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=2026-05-10T04:38:00.482850Z digest=sha256:156ef206c77dcd48bd1ddc542d3700fb29345a371a1d454a70d0aedc0e5a4b79

Observation da7a8fee-6ddd-4625-89c9-ec350d4eaa90 · inbound

HalluScore: Large Language Model Hallucination Question Answering Benchmark cites this paper.

HalluScore: Large Language Model Hallucination Question Answering Benchmark Mitigating Large Language Model Hallucination with Faithful Finetuning

Reference 38

Resolution
verified exact
arxiv_id, observed 2026-05-19T20:32:45.431359Z

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=2026-05-19T20:31:20.017866Z digest=sha256:c16d5c94d3ac4c852b0543a1ce17e2d5597dcc5215c42f9ceb330a852840dbd7

Observation ca0661dd-8506-4b68-8dd5-3d49b357b416 · inbound

BALTO: Balanced Token-Level Policy Optimization for Hallucination Mitigation cites this paper.

BALTO: Balanced Token-Level Policy Optimization for Hallucination Mitigation Mitigating Large Language Model Hallucination with Faithful Finetuning

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-07-03T17:28:44.637465Z

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=2026-06-27T04:07:26.224919Z digest=sha256:07568d2c9d0803e0c5e9946a4d738b4b6bb3d5d7f9afd5da9822c7971a241334

Observation 02e4857f-ff6f-4fa8-b8ca-3319a49e7236 · inbound

Knowledge Injection Exists in MoE? Exploring Expert-Aware Contrast Decoding in MoE for Mitigating LLMs'Hallucinations cites this paper.

Knowledge Injection Exists in MoE? Exploring Expert-Aware Contrast Decoding in MoE for Mitigating LLMs'Hallucinations Mitigating Large Language Model Hallucination with Faithful Finetuning

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-02T14:37:31.212348Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T14:37:31.212348Z digest=sha256:a3e2ddb18492f146ceb09d3548774b6bcd2a4e447a59645e167a0a06e09435b5

Observation e91a0aab-05c8-43c3-a9fc-406a76696097 · inbound

Decomposed Entailment for Factuality Checking and Hallucination Detection cites this paper.

Decomposed Entailment for Factuality Checking and Hallucination Detection Mitigating Large Language Model Hallucination with Faithful Finetuning

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-07T22:53:05.153034Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T22:53:05.153034Z digest=sha256:8500bd32341583ba4d693cd602b4ce8e78aaef3b1414802cd4549ce66d8076e4