Skip to content

SRFE: Measuring Chain-of-Thought Faithfulness with Independent Stepwise Visual Probes

Sep 2026 · Applied and Computational Engineering · 0 citations
Multimodal Machine Learning Applications

Abstract

Using stepwise probe as an external reference or Chain-of-Thought (CoT) to evaluate visual-language model (VLM) analysis ability is common, but the faithfulness of PASS/FAIL verdicts in VLM produced by explicit CoT and independent SRFE probe needs further work to figure out. Prior works on CoT faithfulness are mainly about large language model (LLM) and internal interpretability signals, with limited VLM, Vision Prompt Distillation (VPD), structured verdict settings and behavioral probes. This paper focuses on evaluating Stepwise Reasoning Faithfulness Evaluation (SRFE), a five-step protocol (object->color->size->relation->composition) with prompt-defined order, and CoT faithfulness after distillation, trying to align them using probe Supervised Fine-Tuning (SFT) to reduce two different methods to a single faithfulness evaluating method. To get features of SRFE, the paper compares the independent and conditional probe version and find weak chain effect in model then order ablation experiment find SRFE is order invariance. After VPD distillation on Qwen2-VL, teacher and student have a high agreement (97.6% stepwise, 88% exact bits), supporting SRFE probe is procedure faithfulness but not internal reasoning faithfulness. To find Chain-of-thought procedure faithfulness, the paper uses VLM to generate explicit CoT then separate the answer and compare each one under SRFE to get the similarity, finds that baseline CoT-SRFE probe partial misalignment. To improve alignment, SRFE probe supervised SFT on CoT is implemented, but finds a trade-off between independent probe agreement, chain consistency, and say-do &do-say.

Read PDF

Similar papers

#computer vision Open access Jun 2016

Software Development in Startup Companies: The Greenfield Startup Model

The results are packaged in the Greenfield Startup Model (GSM), which explains the priority of startups to release the product as quickly as possible, and the need to shorten time-to-market, by speeding up the development through low-precision engineering activities.

Carmine Giardino, Nicolò Paternoster, M. Unterkalmsteiner et al. · 178 citations · ⚡14
#computer vision Open access Oct 2016

Software Startups - A Research Agenda

Software startup companies develop innovative, software-intensive products within limited timeframes and with few resources, searching for sustainable and scalable business models.

M. Unterkalmsteiner, P. Abrahamsson, Xiaofeng Wang et al. · 157 citations · ⚡17
#machine learning Review Open access Oct 2016

“Failures” to be celebrated: an analysis of major pivots of software startups

This study conducts a case survey study based on the secondary data of the major pivots happened in 49 software startups, and demonstrates that customer need pivot is the most common among all pivot types.

Sohaib Shahid Bajwa, Xiaofeng Wang, Anh Nguyen-Duc et al. · 127 citations · ⚡15
#computer vision Review Open access May 2015

A survey study on major technical barriers affecting the decision to adopt cloud services

The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.

Nattakarn Phaphoom, Xiaofeng Wang, S. Samuel et al. · 111 citations · ⚡8
#computer vision Conference Open access Dec 2013

Affordable and Energy-Efficient Cloud Computing Clusters: The Bolzano Raspberry Pi Cloud Cluster Experiment

The ongoing work building a Raspberry Pi cluster consisting of 300 nodes is presented, with potential use cases being an inexpensive and green test bed for cloud computing research and a robust and mobile data center for operating in adverse environments.

P. Abrahamsson, S. Helmer, Nattakarn Phaphoom et al. · 110 citations · ⚡7
#computer vision Book Open access Mar 2017

On the Unhappiness of Software Developers

The results indicate that software developers are a slightly happy population, but the need for limiting the unhappiness of developers remains, and 219 factors representing causes of unhappiness while developing software are identified.

D. Graziotin, Fabian Fagerholm, Xiaofeng Wang et al. · 84 citations · ⚡6

Related blog posts

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.