Papers by Yoonji Kim

2 papers
Diagnosing Spatial Consistency across Perspectives and Viewpoints in Large Vision-Language Models (2026.acl-long)

Copied to clipboard

Challenge: Existing models assess spatial capabilities from a static, single-view and egocentric perspective, failing to capture the dynamic nature of real-world spatial cognition.
Approach: They propose a benchmark to diagnose spatial reasoning capabilities using a 360 field of view.
Outcome: The proposed benchmark evaluates allocentric and egocentric reasoning capabilities from multiple perspectives in high-quality 3D environments.
Plug-in and Fine-tuning: Bridging the Gap between Small Language Models and Large Language Models (2025.acl-long)

Copied to clipboard

Challenge: Large language models (LLMs) are renowned for their extensive linguistic knowledge and strong generalization capabilities, but their high computational demands make them unsuitable for resource-constrained environments.
Approach: They propose a framework that integrates a single frozen layer from an LLM into a SLM and fine-tunes the combined model for specific tasks.
Outcome: The proposed framework improves performance across a range of natural language processing tasks, including both natural language understanding and generation.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations