Papers by Yuanhao Sun

2 papers
VisPCO: Visual Token Pruning Configuration Optimization via Budget-Aware Pareto-Frontier Learning for Vision-Language Models (2026.acl-long)

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Challenge: Existing methods for visual token pruning rely on predefined configurations without determining whether they achieve optimal performance.
Approach: They propose a framework that formulates visual token pruning as a Pareto configuration optimization problem to automatically identify optimal configurations.
Outcome: The proposed framework approximates the empirical Pareto frontier obtained through grid search and generalizes well across pruning methods and VLM architectures.
CogBench: Benchmarking Cognitive Alignment of Large Language Models in Educational Question Answering (2026.findings-acl)

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Challenge: Large language models (LLMs) possess strong capabilities in language understanding and generation, as well as remarkable problem-solving abilities.
Approach: They propose a benchmark to assess the cognitive alignment capabilities of large language models in educational QA.
Outcome: The proposed evaluation benchmark assesses the cognitive alignment capabilities of large language models in educational QA.

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