Nick Kashani Motlagh
Research archive

Papers and manuscript notes

A reading-friendly archive of peer-reviewed papers and current research notes on selective prediction, multimodal evidence, calibration, and recoverability in QA systems.

Status labels are explicit: current manuscript notes are separated from peer-reviewed work, and public PDFs/code/data are linked where available.

Current manuscript

Under review

Manuscript under review / 2026

Manuscript Note: Knowing When to Answer, Refine, or Abstain

Author list withheld during review

Uses paired direct and evidence-refined outcomes to evaluate answer, refine, or abstain policies for a fixed retrieval-augmented QA stack.

  • selective prediction
  • adaptive QA
  • retrieval-augmented generation
  • abstention
  • Compares direct and evidence-refined answers on 25,870 held-out questions, distinguishing preserved, repaired, harmed, and unrecovered outcomes.
  • Evaluates answer, refine, or abstain policies for a fixed model-retriever-corpus stack instead of treating draft confidence as a complete estimate of recoverability.

Peer-reviewed

Published papers

Machine Vision and Applications / 2025

First author

Naturally Constrained Reject Option Classification

N. Kashani Motlagh, J. Davis, T. Anderson, J. Gwinnup

Journal extension of the ISVC 2022 work, evaluating per-class binomial reject thresholds on synthetic, image, and text classification datasets.

  • vision
  • reject option
  • calibration
  • ImageNet
  • Extends the natural reject-region constraint across controlled synthetic data, benchmark image classification, and text classification.
  • Reports transfer behavior on CINIC10 and long-tailed iNaturalist19 alongside explicit selective-accuracy, reject-accuracy, and coverage tradeoffs.
Paper arXiv Code
Related code and data

learning-idk

WMT 2024 / 2024

First author

Assessing the Role of Imagery in Multimodal Machine Translation

N. Kashani Motlagh, J. Davis, J. Gwinnup, G. Erdmann, T. Anderson

Contrastive evaluation of WMT 2024 multimodal MT systems shows measurable dependence on paired visual context.

  • multimodal MT
  • vision-language models
  • evaluation
  • WMT
  • Introduced imagery-aware contrastive probes for testing whether model scores change under mismatched visual context.
  • Evaluated three English-to-French multimodal model families, plus gated variants, under matched and mismatched visual context.
Paper
Related code and data

calibration

ISVC 2022 / 2022

First author Springer Best Paper Award

Learning When to Say "I Don't Know"

N. Kashani Motlagh, J. Davis, T. Anderson, J. Gwinnup

Per-class reject thresholds estimated from validation statistics without requiring a rejection cost, target accuracy, or target coverage.

  • vision
  • reject option
  • selective accuracy
  • ImageNet
  • Springer Best Paper Award at ISVC 2022; later extended in the MVA 2025 journal version.
  • At the ImageNet δ=.75 operating point, B-CDF improved select accuracy by 0.4 percentage points and coverage by 1.3 points versus an uncalibrated global 0.5 threshold.
Paper arXiv Code
Related code and data

learning-idk

ICCV 2021 Workshop on LUAI / 2021

First author

A Framework for Semi-automatic Collection of Temporal Satellite Imagery for Analysis of Dynamic Regions

N. Kashani Motlagh, A. Radhakrishnan, J. Davis, R. Ilin

OpenStreetMap-guided imagery collection and labeling tools for building temporal satellite datasets for dynamic-region analysis.

  • remote sensing
  • data collection
  • labeling pipelines
  • change detection
  • Combined OpenStreetMap extraction, polygon filtering, and temporal imagery download scripts in a public Python workflow.
  • Released the collection code and a sample construction-site satellite-imagery dataset under the repository's GPL license.
Paper Code
Related code and data

construction-site-satellite-imagery-collection