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WE INTRODUCE VOYAGER, THE FIRST LLM-POWERED EMBODIED LIFELONG LEARNING AGENT IN MINECRAFT THAT CONTINUOUSLY EXPLORES THE WORLD, ACQUIRES DIVERSE SKILLS, AND MAKES NOVEL DISCOVERIES WITHOUT HUMAN INTERVENTION.

SEMANTIC PARSING

WE PRESENT C-EVAL, THE FIRST COMPREHENSIVE CHINESE EVALUATION SUITE DESIGNED TO ASSESS ADVANCED KNOWLEDGE AND REASONING ABILITIES OF FOUNDATION MODELS IN A CHINESE CONTEXT.

THE PROPOSED FC-CLIP, BENEFITS FROM THE FOLLOWING OBSERVATIONS: THE FROZEN CLIP BACKBONE MAINTAINS THE ABILITY OF OPEN-VOCABULARY CLASSIFICATION AND CAN ALSO SERVE AS A STRONG MASK GENERATOR, AND THE CONVOLUTIONAL CLIP GENERALIZES WELL TO A LARGER INPUT RESOLUTION THAN THE ONE USED DURING CONTRASTIVE IMAGE-TEXT PRETRAINING.

MULTIMODAL LARGE LANGUAGE MODEL (MLLM) RECENTLY HAS BEEN A NEW RISING RESEARCH HOTSPOT, WHICH USES POWERFUL LARGE LANGUAGE MODELS (LLMS) AS A BRAIN TO PERFORM MULTIMODAL TASKS.

THIS TUTORIAL NOTE SUMMARIZES THE PRESENTATION ON ``LARGE MULTIMODAL MODELS: TOWARDS BUILDING AND SURPASSING MULTIMODAL GPT-4'', A PART OF CVPR 2023 TUTORIAL ON ``RECENT ADVANCES IN VISION FOUNDATION MODELS''.

LARGE LANGUAGE MODEL (LLM) BASED GENERATIVE AI SYSTEMS HAVE SEEN SIGNIFICANT PROGRESS IN RECENT YEARS.

THIS EVOLUTION REQUIRES A COMBINATION OF BOTH TRADITIONAL METHODS (SUCH AS TERM-BASED SPARSE RETRIEVAL METHODS WITH RAPID RESPONSE) AND MODERN NEURAL ARCHITECTURES (SUCH AS LANGUAGE MODELS WITH POWERFUL LANGUAGE UNDERSTANDING CAPACITY).

WE DEMONSTRATE FAN ON A REAL-WORLD ROBOTIC SYSTEM (A MICRO AERIAL VEHICLE) AND REPORT ITS ABILITY TO SEAMLESSLY FOLLOW THE OBJECTS OF INTEREST IN A REAL-TIME CONTROL LOOP.

IN THIS WORK, WE INTRODUCE AUDIOSEP, A FOUNDATION MODEL FOR OPEN-DOMAIN AUDIO SOURCE SEPARATION WITH NATURAL LANGUAGE QUERIES.