Papers by Jay Wu

2 papers
RSVP: Reasoning Segmentation via Visual Prompting and Multi-modal Chain-of-Thought (2025.acl-long)

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Challenge: Recent advances in multi-modal learning have enhanced MLLMs' ability to reason about visual content.
Approach: They propose a framework that unifies multi-step multimodal reasoning with grounded visual understanding.
Outcome: The proposed framework surpasses state-of-the-art methods by +6.5 gIoU and +9.2 cIou on ReasonSeg and achieves 49.7 mAP on SegInW under zero-shot settings.
AudioChatLlama: Towards General-Purpose Speech Abilities for LLMs (2024.naacl-long)

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Challenge: a new model for speech processing and reasoning uses curated data instead of text.
Approach: They extend the instruction-tuned Llama-2 model with end-to-end speech processing and reasoning abilities without using any carefully curated paired data.
Outcome: The proposed model outperforms or outperfects existing models on synthesized and recorded speech QA tests.

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