Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 27 inbound Pith citation observations for arXiv:2405.05904.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-08T19:12:42.238886Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-06-30T00:04:06.739008Z
0 of 0 outbound references displayed
External citation measurements
No source-named external measurement is stored.
No outbound reference observations are available for this paper version.
Observation 11edd4ec-9ab3-445c-8016-451d6a5d66e9 · inbound
A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions Does Fine-Tuning LLMs on New Knowledge Encourage Hallucinations?
Reference 101
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.
Observation 11d12a21-ca32-4651-94b9-44a7c7ed2135 · inbound
OntoTune: Ontology-Driven Self-training for Aligning Large Language Models Does Fine-Tuning LLMs on New Knowledge Encourage Hallucinations?
Reference 16
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 73e71acc-819f-45bd-b72c-44fa5b27caea · inbound
Refine Knowledge of Large Language Models via Adaptive Contrastive Learning Does Fine-Tuning LLMs on New Knowledge Encourage Hallucinations?
Reference 12
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 71483c38-9e7a-49ef-8260-ff5294e1f711 · inbound
The Hallucination Tax of Reinforcement Finetuning Does Fine-Tuning LLMs on New Knowledge Encourage Hallucinations?
Reference 10
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 413b14db-df5e-45d4-a4ae-da33be469d06 · inbound
SLearnLLM: A Self-Learning Framework for Efficient Domain-Specific Adaptation of Large Language Models Does Fine-Tuning LLMs on New Knowledge Encourage Hallucinations?
Reference 7
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation dfaabf00-13a2-4708-8f88-4c91022a859d · inbound
Towards Objective Fine-tuning: How LLMs' Prior Knowledge Causes Potential Poor Calibration? Does Fine-Tuning LLMs on New Knowledge Encourage Hallucinations?
Reference 10
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bcc44dfd-c6e4-4bb4-8e60-94e71ee4ef50 · inbound
Position: Agent Should Invoke External Tools ONLY When Epistemically Necessary Does Fine-Tuning LLMs on New Knowledge Encourage Hallucinations?
Reference 53
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.
Observation aafb8524-eb26-4d8a-a1bc-bc867eb3b7aa · inbound
Quantifying Cross-Modality Memorization in Vision-Language Models Does Fine-Tuning LLMs on New Knowledge Encourage Hallucinations?
Reference 4
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8c8bc5bf-1122-47d1-b6a2-b9a15cace4ba · inbound
When to Trust Context: Self-Reflective Debates for Context Reliability Does Fine-Tuning LLMs on New Knowledge Encourage Hallucinations?
Reference 10
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 83b38b11-3731-4d6f-94f3-6636205811ec · inbound
Reliable Reasoning Path: Distilling Effective Guidance for LLM Reasoning with Knowledge Graphs Does Fine-Tuning LLMs on New Knowledge Encourage Hallucinations?
Reference 21
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f23add95-5d40-4dde-b29e-bcf673da8cce · inbound
ClimateChat: Designing Data and Methods for Instruction Tuning LLMs to Answer Climate Change Queries Does Fine-Tuning LLMs on New Knowledge Encourage Hallucinations?
Reference 11
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 908f5f85-53c8-4784-9d84-7d67d006b716 · inbound
AggTruth: Contextual Hallucination Detection using Aggregated Attention Scores in LLMs Does Fine-Tuning LLMs on New Knowledge Encourage Hallucinations?
Reference 5
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2a74068f-f281-4a93-961a-df4e148d89a8 · inbound
Loki's Dance of Illusions: A Comprehensive Survey of Hallucination in Large Language Models Does Fine-Tuning LLMs on New Knowledge Encourage Hallucinations?
Reference 147
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3aedc88a-fa19-4ab2-b62c-047eda7b95d9 · inbound
Bridging Vision and Language: Optimal Transport-Driven Radiology Report Generation via LLMs Does Fine-Tuning LLMs on New Knowledge Encourage Hallucinations?
Reference 13
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0b0ef7e6-53de-4928-96f3-a47a72fbb1b0 · inbound
Reconstructing Biological Pathways by Applying Selective Incremental Learning to (Very) Small Language Models Does Fine-Tuning LLMs on New Knowledge Encourage Hallucinations?
Reference 6
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1d155af6-aae1-48b6-9396-f3180a5213da · inbound
Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Does Fine-Tuning LLMs on New Knowledge Encourage Hallucinations?
Reference 21
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3947515b-4eb2-4fa4-8bc6-ed08f8e3234a · inbound
Building Task Bots with Self-learning for Enhanced Adaptability, Extensibility, and Factuality Does Fine-Tuning LLMs on New Knowledge Encourage Hallucinations?
Reference 45
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0145a9c8-6083-4740-b07a-1ba22821f32c · inbound
Understanding New-Knowledge-Induced Factual Hallucinations in LLMs: Analysis and Interpretation Does Fine-Tuning LLMs on New Knowledge Encourage Hallucinations?
Reference 7
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.
Observation f682ed51-9f73-4f3d-9de4-b9518bb15eae · inbound
Reinforcement Learning Improves Traversal of Parametric Knowledge in LLMs Does Fine-Tuning LLMs on New Knowledge Encourage Hallucinations?
Reference 14
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d63afa9b-4eab-430e-bab4-2ef14eb787b0 · inbound
REFLEX: Self-Refining Explainable Fact-Checking via Verdict-Anchored Style Control Does Fine-Tuning LLMs on New Knowledge Encourage Hallucinations?
Reference 10
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.
Observation ed37aacd-9820-4521-a48e-ef24cbaf73a8 · inbound
REFLEX: Self-Refining Explainable Fact-Checking via Verdict-Anchored Style Control Does Fine-Tuning LLMs on New Knowledge Encourage Hallucinations?
Reference 10
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 89ffba67-33aa-496f-8f79-f2366f96023f · inbound
Why Fine-Tuning Encourages Hallucinations and How to Fix It Does Fine-Tuning LLMs on New Knowledge Encourage Hallucinations?
Reference 2
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.
Observation bc4c3590-c941-4da8-9c08-b9214bef1a07 · inbound
EHRAG: Bridging Semantic Gaps in Lightweight GraphRAG via Hybrid Hypergraph Construction and Retrieval Does Fine-Tuning LLMs on New Knowledge Encourage Hallucinations?
Reference 18
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.
Observation fe2f34f6-4722-466c-8c3d-239259f23235 · inbound
Semantic Layers for Reliable LLM-Powered Data Analytics: A Paired Benchmark of Accuracy and Hallucination Across Three Frontier Models Does Fine-Tuning LLMs on New Knowledge Encourage Hallucinations?
Reference 2
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.
Observation f0954bd3-2f6a-4fda-af6a-82016c2bd46d · inbound
Cultivating Machine Intelligence: The OMEGA Shift from Top-Down Optimization to Autopoietic Cognitive Ecologies Does Fine-Tuning LLMs on New Knowledge Encourage Hallucinations?
Reference 9
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.
Observation 3d639c06-ea19-406b-ab58-46d4f8d0c07f · inbound
Reliability Scales Inversely: Hallucinations Snowball Faster in Bigger Language Models Does Fine-Tuning LLMs on New Knowledge Encourage Hallucinations?
Reference 61
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 81dccf5c-4ffe-4aa8-b452-766737e1b393 · inbound
Data Quality over Capacity: Internalizing Documents into LoRA Adapters for Closed-Book QA Does Fine-Tuning LLMs on New Knowledge Encourage Hallucinations?
Reference 5
Source-reported events for the cited work
Unavailable: canonical work link unavailable.