Categories: FAANG

MARRS: Multimodal Reference Resolution System

*= All authors listed contributed equally to this work
Successfully handling context is essential for any dialog understanding task. This context maybe be conversational (relying on previous user queries or system responses), visual (relying on what the user sees, for example, on their screen), or background (based on signals such as a ringing alarm or playing music). In this work, we present an overview of MARRS, or Multimodal Reference Resolution System, an on-device framework within a Natural Language Understanding system, responsible for handling conversational, visual and background…
AI Generated Robotic Content

Recent Posts

If dean ran into Harry Potter

submitted by /u/Sad_Coach_1433 [link] [comments]

11 hours ago

Why AI Doesn’t Need Your Content — And What It Actually Needs Instead

Ask most people what makes content valuable to AI right now, and you’ll get some…

11 hours ago

STARFlow2: Bridging Language Models and Normalizing Flows for Unified Multimodal Generation

Unified multimodal models that understand, reason over, and generate interleaved text–image sequences remain structurally fragmented:…

11 hours ago

Agentic observability with Amazon OpenSearch Service MCP Apps

Observability agents are fast. They query alerts, correlate logs with traces, and produce a root…

11 hours ago

Now introducing Gemini Enterprise for Legal

Few professions are as exacting as the practice of law. A team reviewing a contract…

11 hours ago

‘Darth Vader’ Wants You to Know He Definitely Supports Flock Surveillance

Anthony Ralphs was frustrated by the San Diego City Council's support for Flock. He decided…

12 hours ago