Signals 4 · free daily AI digest

PANORAMA: Panoptic Grounded Captioning via Mask Proposal Selection

Paper recorded by Signals 4 on 2026-09-16 in cs.CL. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-16 on arXiv · recorded by Signals 4 on 2026-09-17

Category: cs.CL · 自然语言处理 · first seen 2026-09-17

Abstract

Intelligent systems that act in the world require image understanding that is both comprehensive and spatially grounded. Current vision-language models (VLMs) can generate fluent and detailed image captions, but reliably associating them with image pixels remains challenging. Existing methods that combine dense captioning with pixel-level grounding often produce either incomplete descriptions or i

Read on arXiv →

#13 most recent of 186 cs.CL papers we have recorded · ↑ newer: Language-model groups overstate consensus when replaying human deliber · ↓ older: ScienceIDE: Turning World's Scientific Codebase into Agent Learnable E
Cite this page: PANORAMA: Panoptic Grounded Captioning via Mask Proposal Selection: the #13 most recent of 186 cs.CL papers we have recorded (as of 2026-09-16). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/panorama-panoptic-grounded-captioning-via-mask-proposal-selection.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
Related: More cs.CL 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