Papers by Keyang Xuan

2 papers
TinyScientist: An Interactive, Extensible, and Controllable Framework for Building Research Agents (2025.emnlp-demos)

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Challenge: Existing research systems often design and use agentic workflows to perform research tasks such as ideation, scientific coding, review writing, and tree-based search.
Approach: They propose an open-source codebase, an interactive web demonstration, and a PyPI Python package to make state-of-the-art auto-research pipelines broadly accessible to every researcher and developer.
Outcome: The proposed framework adapts easily to new tools and supports iterative growth.
TAMP: Token-Adaptive Layerwise Pruning in Multimodal Large Language Models (2025.findings-acl)

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Challenge: Existing pruning methods fail to account for unique token attributes across layers and modalities inherent to MLLMs.
Approach: They propose a pruning framework that takes into account unique token attributes across layers and modalities inherent to MLLMs.
Outcome: The proposed pruning framework outperforms existing pruning techniques on two state-of-the-art MLLMs.

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