「multimodal」の検索結果
32 件Video understanding is being rapidly transformed by multimodal large language models (MLLMs), as research move
Despite advances in 3D scene understanding, existing 3D Large Multimodal Models operate in offline settings, r
Training vision-language web agents with multi-step RL is compute-intensive, with two dominant forms of ineffi
Latent visual reasoning (LVR) inserts supervised latent tokens between perception and answer generation in vis
While Vision-Language Models (VLMs) have shown strong visual reasoning capabilities, their spatial reasoning a
Despite the rapid progress of Vision-Language Models (VLMs), the field lacks benchmarks that rigorously diagno
In real-world applications, models are expected to perform reliably across diverse settings. Yet, many existin
Developing unified video generation and editing models capable of interpreting interleaved multimodal inputs i
Multimodal Large Language Models (MLLMs) excel at 2D semantic understanding but lack intrinsic 3D awareness, r
Large language models are increasingly used to simulate social media users and infer how individuals may respo
Benchmarks are fundamental for evaluating and advancing LLMs and MLLMs by providing standardized and explicit
Vision language models (VLMs) excel at many tasks but still struggle with spatial reasoning when critical info
Processing video in vision-language models is expensive: each frame occupies hundreds of tokens, and inference
Learning representations of CAD models is a largely open problem. While 3D representation learning has flouris
Lane-level maps are critical infrastructure for autonomous driving and lane-level navigation, yet constructing
3D vision has rapidly evolved, driven by increasingly diverse data representations, learning paradigms, and mo
Selection is a core operation in interactive image editing. To be practical, a user should be able to specify
In robotics systems, vast amounts of visual data are easily captured at high resolution using low-cost, low-po
Multimodal agents in robotics, AR, and autonomous driving must reason about places and layouts from continuous
Wide-baseline matching (WBM) requires integrating geometric understanding, viewpoint changes, fine-grained per
Graph Language Models (GLMs) have become a promising direction for adapting Large Language Models (LLMs) to gr
Existing autonomous driving datasets have enabled major progress, but fall short in sensor fidelity, map compl
Video is temporally redundant: adjacent frames usually share most objects, background, and layout. Yet existin
We introduce Cosmos 3, a family of omnimodal world models designed to jointly process and generate language, i
Abundant procedural knowledge on the Web holds great potential for helping agents solve long-horizon tasks. Ho
Multimodal Large Language Models (MLLMs) have demonstrated significant achievements in general visual question
Humans can effortlessly perceive spatial layouts, form cognitive representations, reason about spatial relatio
While current multimodal models are proficient at open-ended visual editing, executing precise single-answer e
AI coding agents are increasingly used for scientific work, but their end-to-end autonomous research capabilit
Music recommendation systems typically treat songs as opaque tokens, relying on collaborative interaction hist
We present Stable-Layers, a reinforcement learning framework that eliminates the need for paired supervision b
Vision-Language Models (VLMs) are increasingly deployed in embodied environments, where they need produce nume