Papers by Lewei Yao
DetGPT: Detect What You Need via Reasoning (2023.emnlp-main)
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Renjie Pi, Jiahui Gao, Shizhe Diao, Rui Pan, Hanze Dong, Jipeng Zhang, Lewei Yao, Jianhua Han, Hang Xu, Lingpeng Kong, Tong Zhang
| Challenge: | Recent advances in the field of computer vision have enabled more effective and sophisticated interactions between humans and machines. |
| Approach: | They propose a reasoning-based object detection paradigm that leverages state-of-the-art multi-modal models and open-vocabulary object detectors to perform reasoning within the context of the user’s instructions and the visual scene. |
| Outcome: | The proposed method enables users to interact with the system using natural language instructions, allowing for a higher level of interactivity. |
AEQ-Bench: Measuring Empathy of Omni-Modal Large Models (2026.findings-acl)
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| Challenge: | Existing benchmarks focus on cognitive abilities, such as knowledge retrieval, complex reasoning, and instruction following, largely overlooking empathy evaluation. |
| Approach: | They propose to benchmark two core empathetic capabilities of omnimodal large models (OLMs) generating empatries by comprehending affective cues from multi-modal inputs and judging empathy of audio responses without relying on text transcription. |
| Outcome: | The proposed benchmark outperforms existing models with audio output capabilities but is unreliable for evaluating fine-grained paralinguistic expressiveness. |