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Paper Citation Record · LEDGER

Critique Before Thinking: Mitigating Hallucination through Rationale-Augmented Instruction Tuning

As of 18 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2505.07172.

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

pith.paper-citation-record.v1
2505.07172 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:27:46.851405Z

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

34 of 34 outbound references displayed

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  • verified fuzzy9
  • unresolved25
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9fd54759-7ce8-4184-98da-d7629290776c · outbound

This paper cites GPT-4 Technical Report.

Critique Before Thinking: Mitigating Hallucination through Rationale-Augmented Instruction Tuning GPT-4 Technical Report

Reference 1

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Observation 27cdbec4-a68b-4fa5-857d-02c436324b66 · outbound

This paper cites An aug- mented benchmark dataset for geometric question answer- ing through dual parallel text encoding.

Critique Before Thinking: Mitigating Hallucination through Rationale-Augmented Instruction Tuning An aug- mented benchmark dataset for geometric question answer- ing through dual parallel text encoding

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation b6988cb4-f314-4fff-8646-94d84dd1f831 · outbound

This paper cites MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models.

Critique Before Thinking: Mitigating Hallucination through Rationale-Augmented Instruction Tuning MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models

Reference 6

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Observation d1736190-46f0-4deb-8834-9528afd77d14 · outbound

This paper cites Hallusion- bench: an advanced diagnostic suite for entangled lan- guage hallucination and visual illusion in large vision- language models.

Critique Before Thinking: Mitigating Hallucination through Rationale-Augmented Instruction Tuning Hallusion- bench: an advanced diagnostic suite for entangled lan- guage hallucination and visual illusion in large vision- language models

Reference 7

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 31562297-079d-4678-95cc-cfcd95e064ef · outbound

This paper cites Detecting and preventing hallucinations in large vi- sion language models.

Critique Before Thinking: Mitigating Hallucination through Rationale-Augmented Instruction Tuning Detecting and preventing hallucinations in large vi- sion language models

Reference 8

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 70b4cade-a984-407d-9778-2e2a5fefd56c · outbound

This paper cites Mini- monkey: Multi-scale adaptive cropping for multimodal large language models.

Critique Before Thinking: Mitigating Hallucination through Rationale-Augmented Instruction Tuning Mini- monkey: Multi-scale adaptive cropping for multimodal large language models

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 5b5161ec-6da1-48a1-9098-3d07e218fec0 · outbound

This paper cites Gqa: A new dataset for real-world visual reasoning and compositional question answering.

Critique Before Thinking: Mitigating Hallucination through Rationale-Augmented Instruction Tuning Gqa: A new dataset for real-world visual reasoning and compositional question answering

Reference 10

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:27:46.715302Z digest=sha256:7873140fc08dc6abf70fca2ce018d180ddd8e55837603fb6bf527c798a2b577c

Observation 9912df95-fa7d-4cd1-8237-f3540f2e2256 · outbound

This paper cites FaithScore: Fine-grained Evaluations of Hallucinations in Large Vision-Language Models.

Critique Before Thinking: Mitigating Hallucination through Rationale-Augmented Instruction Tuning FaithScore: Fine-grained Evaluations of Hallucinations in Large Vision-Language Models

Reference 12

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Observation 38447abb-dafc-4725-bf88-ac03df8c351c · outbound

This paper cites Dvqa: Understanding data visu- alizations via question answering.

Critique Before Thinking: Mitigating Hallucination through Rationale-Augmented Instruction Tuning Dvqa: Understanding data visu- alizations via question answering

Reference 13

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Observation 0d5e1a3a-0fbc-426c-9157-ea51b0250689 · outbound

This paper cites OCRBench: On the Hidden Mystery of OCR in Large Multimodal Models.

Critique Before Thinking: Mitigating Hallucination through Rationale-Augmented Instruction Tuning OCRBench: On the Hidden Mystery of OCR in Large Multimodal Models

Reference 16

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Observation c53dfa6f-f1bc-4e35-a4fa-0ca950eda072 · outbound

This paper cites A Survey on Hallucination in Large Vision-Language Models.

Critique Before Thinking: Mitigating Hallucination through Rationale-Augmented Instruction Tuning A Survey on Hallucination in Large Vision-Language Models

Reference 17

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Observation 8b05ee9a-b59a-477e-9b3a-4ab9fff1456c · outbound

This paper cites MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts.

Critique Before Thinking: Mitigating Hallucination through Rationale-Augmented Instruction Tuning MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts

Reference 18

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Observation 85e6e759-fd60-4b52-a965-8a768fc04730 · outbound

This paper cites DeepSeek-VL: Towards Real-World Vision-Language Understanding.

Critique Before Thinking: Mitigating Hallucination through Rationale-Augmented Instruction Tuning DeepSeek-VL: Towards Real-World Vision-Language Understanding

Reference 19

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Observation 4ba307b6-5686-440f-aed4-2a168b80d893 · outbound

This paper cites ChartQA: A Benchmark for Question Answering about Charts with Visual and Logical Reasoning.

Critique Before Thinking: Mitigating Hallucination through Rationale-Augmented Instruction Tuning ChartQA: A Benchmark for Question Answering about Charts with Visual and Logical Reasoning

Reference 20

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Observation f4c04d88-5ac5-4d3e-8bd2-8da1658cb079 · outbound

This paper cites Direct preference optimization: Your lan- guage model is secretly a reward model.Advances in Neu- ral Information Processing Systems,.

Critique Before Thinking: Mitigating Hallucination through Rationale-Augmented Instruction Tuning Direct preference optimization: Your lan- guage model is secretly a reward model.Advances in Neu- ral Information Processing Systems,

Reference 23

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verified fuzzy
raw_fallback, observed 2026-08-15T22:27:47.474454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 66b9e284-1381-446a-b8b9-11702fa188b2 · outbound

This paper cites Object Hallucination in Image Captioning.

Critique Before Thinking: Mitigating Hallucination through Rationale-Augmented Instruction Tuning Object Hallucination in Image Captioning

Reference 24

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Unavailable: canonical work link unavailable.

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Observation c073446d-8c83-4ff1-90dd-f8da68240937 · outbound

This paper cites Aligning Large Multimodal Models with Factually Augmented RLHF.

Critique Before Thinking: Mitigating Hallucination through Rationale-Augmented Instruction Tuning Aligning Large Multimodal Models with Factually Augmented RLHF

Reference 25

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Observation 15b8692c-86bd-4c19-99f3-3a560cfd4d61 · outbound

This paper cites Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context.

Critique Before Thinking: Mitigating Hallucination through Rationale-Augmented Instruction Tuning Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Reference 26

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Observation 04a819bd-1fc3-4b4d-8bc9-74b786916413 · outbound

This paper cites To See is to Believe: Prompting GPT-4V for Better Visual Instruction Tuning.

Critique Before Thinking: Mitigating Hallucination through Rationale-Augmented Instruction Tuning To See is to Believe: Prompting GPT-4V for Better Visual Instruction Tuning

Reference 27

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Observation 06660f99-caad-4a4e-8439-9b8a8c233e6d · outbound

This paper cites Chain-of-thought prompting elicits rea- soning in large language models.

Critique Before Thinking: Mitigating Hallucination through Rationale-Augmented Instruction Tuning Chain-of-thought prompting elicits rea- soning in large language models

Reference 28

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 70f0db1d-abfd-4ab3-85b5-af9fa280d71d · outbound

This paper cites Mmbench: Bench- marking end-to-end multi-modal dnns and understand- ing their hardware-software implications.

Critique Before Thinking: Mitigating Hallucination through Rationale-Augmented Instruction Tuning Mmbench: Bench- marking end-to-end multi-modal dnns and understand- ing their hardware-software implications

Reference 29

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verified fuzzy
raw_fallback, observed 2026-08-15T22:27:47.436813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 2a3c446b-4e2b-44b2-acb2-7a7da8797cad · outbound

This paper cites MiniCPM-V: A GPT-4V Level MLLM on Your Phone.

Critique Before Thinking: Mitigating Hallucination through Rationale-Augmented Instruction Tuning MiniCPM-V: A GPT-4V Level MLLM on Your Phone

Reference 30

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Observation db4cae1a-0071-432c-89b5-94dac04030b4 · outbound

This paper cites Rlaif-v: Aligning mllms through open-source ai feedback for super gpt-4v trustworthiness.

Critique Before Thinking: Mitigating Hallucination through Rationale-Augmented Instruction Tuning Rlaif-v: Aligning mllms through open-source ai feedback for super gpt-4v trustworthiness

Reference 31

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Observation 6672fabb-b8d8-48ec-a06b-4417526a09da · outbound

This paper cites Beyond Hallucinations: Enhancing LVLMs through Hallucination-Aware Direct Preference Optimization.

Critique Before Thinking: Mitigating Hallucination through Rationale-Augmented Instruction Tuning Beyond Hallucinations: Enhancing LVLMs through Hallucination-Aware Direct Preference Optimization

Reference 32

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Observation ca2a7a46-ec63-47a4-87d2-5eecfa0ca14f · outbound

This paper cites Aligning Modalities in Vision Large Language Models via Preference Fine-tuning.

Critique Before Thinking: Mitigating Hallucination through Rationale-Augmented Instruction Tuning Aligning Modalities in Vision Large Language Models via Preference Fine-tuning

Reference 33

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Observation d0318aae-a62b-40f9-937e-fbe86d4c32d1 · outbound

This paper cites MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models.

Critique Before Thinking: Mitigating Hallucination through Rationale-Augmented Instruction Tuning MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models

Reference 34

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Observation e3cac5e3-d88c-43d1-9689-816ae801b3d5 · outbound

This paper cites Evaluating Object Hallucination in Large Vision-Language Models.

Critique Before Thinking: Mitigating Hallucination through Rationale-Augmented Instruction Tuning Evaluating Object Hallucination in Large Vision-Language Models

Reference 2016

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Observation d2d4d349-1d99-4edc-97d5-1e02dc2fe1fb · outbound

This paper cites A diagram is worth a dozen images.

Critique Before Thinking: Mitigating Hallucination through Rationale-Augmented Instruction Tuning A diagram is worth a dozen images

Reference 2018

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verified fuzzy
raw_fallback, observed 2026-08-15T22:27:47.510017Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation ff9843c9-18ee-4392-8516-9d20daec99df · outbound

This paper cites Forward-backward reasoning in large language models for mathematical verification.

Critique Before Thinking: Mitigating Hallucination through Rationale-Augmented Instruction Tuning Forward-backward reasoning in large language models for mathematical verification

Reference 2019

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verified fuzzy
raw_fallback, observed 2026-08-15T22:27:47.537433Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T22:27:46.720802Z digest=sha256:b0760fc8177d8b37a30d0e68d5eb16f2914e4ba8cbcf04162d42796dbc6311ca

Observation 1ea0968a-a9dd-4f58-ab96-e5cee72bc881 · outbound

This paper cites Reasoning with Language Model Prompting: A Survey.

Critique Before Thinking: Mitigating Hallucination through Rationale-Augmented Instruction Tuning Reasoning with Language Model Prompting: A Survey

Reference 2021

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Observation c8449a9f-7f21-4f16-bfdc-a0406a25ef04 · outbound

This paper cites Docvqa: A dataset for vqa on document images.

Critique Before Thinking: Mitigating Hallucination through Rationale-Augmented Instruction Tuning Docvqa: A dataset for vqa on document images

Reference 2022

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Unavailable: canonical work link unavailable.

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Observation 6cfa227b-b5ea-4a44-a49b-1b53a006f098 · outbound

This paper cites Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond.

Critique Before Thinking: Mitigating Hallucination through Rationale-Augmented Instruction Tuning Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 2023

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Unavailable: canonical work link unavailable.

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Observation 5e445ef5-cebc-415c-8b16-ffbaeba06ca3 · outbound

This paper cites Sharegpt4v: Improving large multi-modal models with better captions.

Critique Before Thinking: Mitigating Hallucination through Rationale-Augmented Instruction Tuning Sharegpt4v: Improving large multi-modal models with better captions

Reference 2024

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Unavailable: canonical work link unavailable.

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Observation 67a319a8-f9b6-46f9-ba0e-96c49ed867cc · outbound

This paper cites Active Prompting with Chain-of-Thought for Large Language Models.

Critique Before Thinking: Mitigating Hallucination through Rationale-Augmented Instruction Tuning Active Prompting with Chain-of-Thought for Large Language Models

Reference 2025

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Unavailable: canonical work link unavailable.

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Pith citing papers

No inbound Pith citation observations are available.