Signals 4 · free daily AI digest

YANAMI: A Large-Scale Multimodal Dataset and Benchmark for Multiturn Stateful Interaction

Paper recorded by Signals 4 on 2026-11-03 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-11-03 on arXiv · recorded by Signals 4 on 2026-11-04

Category: cs.CV · 计算机视觉 · first seen 2026-11-04

Abstract

Unified Multimodal Models (UMMs) integrate visual understanding, generation, and editing within a single unified framework. However, existing unified multimodal datasets and benchmarks remain dominated by single-turn tasks. Even in recent multi-turn datasets, many turns can be solved independently without tracking information across turns. Consequently, they provide limited supervision and evaluat

Read on arXiv →

#7 most recent of 710 cs.CV papers we have recorded · ↑ newer: Anchored Rank-Adversarial Fine-Tuning Pretrained Visual Place Recognit · ↓ older: Möbius: A Unified Motion-Language Model Bridging Understanding and Gen
Cite this page: YANAMI: A Large-Scale Multimodal Dataset and Benchmark for Multiturn Stateful Interaction: the #7 most recent of 710 cs.CV papers we have recorded (as of 2026-11-03). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/yanami-a-large-scale-multimodal-dataset-and-benchmark-for-multiturn-stateful-int.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
Related: More cs.CV papers · arXiv signals · All papers · Today in AI
Get 4 AI signals a day by email — free.
Subscribe free → See all plans →
Get 4 AI signals a day by email — free
All models · All repos · By company · Daily editions