mlsanityData to 14 Oct 2026

CuriosAI Submission to the CASTLE Challenge at EgoVis 2026

arXiv 2605.27800 ↗First posted 27 May 2026cs.CVcited by 1

Not on the map. Why?

Abstract (arXiv)

CASTLE 2026 asks 185 multiple-choice questions over 600+ hours of synchronized multi-view egocentric video. We explore two approaches on top of a shared multimodal preprocessing layer, including per-person timelines, speaker-resolved transcripts, and multi-VLM caption ensembles. Approach A, SVA: Search-Verify-Answer, is a three-stage pipeline that hierarchically narrows to a primary window, verifies sub-windows with a VLM under four anti-confabulation rules, and fuses evidence with an LLM judge under an evidence-priority hierarchy. Approach B, TMKG: Temporal-Multimodal-Knowledge-Graph, is the contrast: it builds a temporal multimodal knowledge graph, locates a primary cell via graph search, and produces the final answer with a single grounded VLM. SVA reaches a leaderboard accuracy of 0.50 and is our final challenge submission; TMKG reaches 0.35.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 12 of its 17 references that are in the map. First posted on arXiv 27 May 2026.

Builds on

12 of 17 references.

References · 12

  1. 2022Robust Speech Recognition via Large-Scale Weak Supervisioncited by 4,057
  2. 2025Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilitiescited by 3,796
  3. 2025Qwen3-VL Technical Reportcited by 2,793
  4. 2025InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Modelscited by 1,834
  5. 2022Text Embeddings by Weakly-Supervised Contrastive Pre-trainingcited by 1,253
  6. 2025SAM 3: Segment Anything with Conceptscited by 906
  7. 2025Qwen3-Omni Technical Reportcited by 497
  8. 2023WhisperX: Time-Accurate Speech Transcription of Long-Form Audiocited by 326
  9. 2019Omni-Scale Feature Learning for Person Re-Identificationcited by 295
  10. 2023Powerset multi-class cross entropy loss for neural speaker diarizationcited by 111
  11. 2022Wespeaker: A Research and Production oriented Speaker Embedding Learning Toolkitcited by 97
  12. 2025The CASTLE 2024 Dataset: Advancing the Art of Multimodal Understandingcited by 16

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 1.

1 paper.

Similar, not cited

Close in wording, no citation either way

  1. 2026CASTLE2026 Team WDL Technical Report
  2. 2025EgoCross: Benchmarking Multimodal Large Language Models for Cross-Domain Egocentric Video Question Answering
  3. 2025Advancing Egocentric Video Question Answering with Multimodal Large Language Models
  4. 2025Omnia de EgoTempo: Benchmarking Temporal Understanding of Multi-Modal LLMs in Egocentric Videos
  5. 2024MM-Ego: Towards Building Egocentric Multimodal LLMs for Video QA
  6. 2026The Right Inference Strategy Is All You Need: Nearly Training-Free Domain-Wise Inference for EgoCross Challenge
  7. 20263rd Place at CVPR 2026 CASTLE Challenge: Agentic Multi-View Long-Context Video Understanding via Hierarchical Knowledge Graph Retrieval
  8. 2026Optimizing Multimodal LLMs for Egocentric Video Understanding: A Solution for the HD-EPIC VQA Challenge