Papers by Allison Koenecke
SPHERE: Unveiling Spatial Blind Spots in Vision-Language Models Through Hierarchical Evaluation (2025.acl-long)
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Wenyu Zhang, Wei En Ng, Lixin Ma, Yuwen Wang, Junqi Zhao, Allison Koenecke, Boyang Li, Wanglu Wanglu
| Challenge: | Current vision-language models lack multi-dimensional spatial reasoning capabilities for human-like understanding and applications. |
| Approach: | They propose a hierarchical evaluation framework that probes models across increasing levels of complexity and integrates spatial, visual, and logical understanding. |
| Outcome: | The proposed framework probes models across increasing levels of complexity, from basic skills to multi-skill integration and high-level reasoning that combines spatial, visual, and logical understanding. |
Analyzing Dialectical Biases in LLMs for Knowledge and Reasoning Benchmarks (2025.findings-emnlp)
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| Challenge: | Previous work has shown degraded performance of large language models for under-represented English dialects. |
| Approach: | They analyze the effects of typifying “standard” American English language questions as non-”standard” dialectal variants on multiple choice questions. |
| Outcome: | The results show that typifying “standard” American English language questions as non-”standard” dialectal variants can reduce performance 20% . |