Papers by Honglu Zhou
Contra4: Evaluating Contrastive Cross-Modal Reasoning in Audio, Video, Image, and 3D (2025.emnlp-main)
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Artemis Panagopoulou, Le Xue, Honglu Zhou, Silvio Savarese, Ran Xu, Caiming Xiong, Chris Callison-Burch, Mark Yatskar, Juan Carlos Niebles
| Challenge: | a recent study shows that multimodal models can reason across multiple modalities . a limited number of models are able to reason across a variety of inputs . |
| Approach: | They propose a dataset for contrastive cross-modal reasoning across four modalities . they use human annotations and a mixture-of-models round-trip-consistency filter . |
| Outcome: | a new model evaluates models on multiple modalities to determine which one best answers a natural language prompt . the model must select the one that best satisfies the query and then fine-tune it . state-of-the-art models still achieve only 56% accuracy overall and 42% in four-modal settings . |