arXiv subjects

Shingo Yokoi

Publications and source records attributed to Shingo Yokoi.

4 recordsLinked to original sources

arXiv2025

Hierarchical Reasoning with Vision-Language Models for Incident Reports from Dashcam Videos

Recent advances in end-to-end (E2E) autonomous driving have been enabled by training on diverse large-scale driving datasets, yet autonomous driving models still struggle in out-of-distribution (OOD) scenarios. The COOOL benchmark targets this gap by encouraging hazard understanding beyond closed taxonomies, and the 2COOOL challenge extends it to generating human-interpretable incident reports. We present a hierarchical reasoning framework for incident report generation from dashcam videos that integrates frame-level captioning, incident frame detection, and fine-grained reasoning within vision-language models (VLMs). We further improve factual accuracy and readability through model ensembling and a Blind A/B Scoring selection protocol. On the official 2COOOL open leaderboard, our method ranks 2nd among 29 teams and achieves the best CIDEr-D score, producing accurate and coherent incident narratives. These results indicate that hierarchical reasoning with VLMs is a promising direction for accident analysis and for broader understanding of safety-critical traffic events. The implementation and code are available at https://github.com/riron1206/kaggle-2COOOL-2nd-Place-Solution.

cs.CV↗

arXiv2025

Learning to detect continuous gravitational waves: an open data-analysis competition

We report results of a public data-analysis challenge, hosted on the open data-science platform Kaggle, to detect simulated continuous gravitational-wave signals (CWs). These are weak signals from rapidly spinning neutron stars that remain undetected despite extensive searches. The competition dataset consisted of a population of CW signals using both simulated and real LIGO detector data matching the conditions of actual CW searches. The competition attracted more than 1,000 participants to develop realistic CW search algorithms. We describe the top 10 approaches and discuss their applicability as a pre-processing step compared to standard CW-search approaches. For the competition's dataset, we find that top approaches can reduce the computing cost by 1 to 3 orders of magnitude at a false-dismissal probability comparable to standard CW searches. Additionally, the competition drove the development of new GPU-accelerated detection pipelines, which facilitated their adoption in other areas of gravitational-wave data analysis. We release the associated dataset, which constitutes the first open standardized benchmark for CW detection, to enable reproducible method comparisons and to encourage further developments toward the first detection of these elusive signals.

gr-qc↗

arXiv2022

5th Place Solution to Kaggle Google Universal Image Embedding Competition

In this paper, we present our solution, which placed 5th in the kaggle Google Universal Image Embedding Competition in 2022. We use the ViT-H visual encoder of CLIP from the openclip repository as a backbone and train a head model composed of BatchNormalization and Linear layers using ArcFace. The dataset used was a subset of products10K, GLDv2, GPR1200, and Food101. And applying TTA for part of images also improves the score. With this method, we achieve a score of 0.684 on the public and 0.688 on the private leaderboard. Our code is available. https://github.com/riron1206/kaggle-Google-Universal-Image-Embedding-Competition-5th-Place-Solution

cs.CV↗

arXiv2017

Where are the Low-Mass Population III Stars ?

We study the number and the distribution of low mass Pop III stars in the Milky Way. In our numerical model, hierarchical formation of dark matter minihalos and Milky Way sized halos are followed by a high resolution cosmological simulation. We model the Pop III formation in H2 cooling minihalos without metal under UV radiation of the Lyman-Werner bands. Assuming a Kroupa IMF from 0.15 to 1.0 Msun for low mass Pop III stars, as a working hypothesis, we try to constrain the theoretical models in reverse by current and future observations. We find that the survivors tend to concentrate on the center of halo and subhalos. We also evaluate the observability of Pop III survivors in the Milky Way and dwarf galaxies, and constraints on the number of Pop III survivors per minihalo. The higher latitude fields require lower sample sizes because of the high number density of stars in the galactic disk, the required sample sizes are comparable in the high and middle latitude fields by photometrically selecting low metallicity stars with optimized narrow band filters, and the required number of dwarf galaxies to find one Pop III survivor is less than ten at <100 kpc for the tip of redgiant stars. Provided that available observations have not detected any survivors, the formation models of low mass Pop III stars with more than ten stars per minihalo are already excluded. Furthermore, we discuss the way to constrain the IMF of Pop III star at a high mass range of > 10 Msun.

astro-ph.GA↗