2 citations · 2 across the 3 of their papers we have counts for
4 papers
When to Rethink: Learning Multi-Perspective Self-Verification for Vision-Language Models
Ziquan Zhu, Hanruo Zhu, Si-Yuan Lu +10
Vision-language models (VLMs) have achieved strong performance in multimodal reasoning, yet they remain prone to generating plausible but incorrect answers. Self-verification offer…
Stacked from One: Multi-Scale Self-Injection for Context Window Extension
Wei Han, Pan Zhou, Soujanya Poria +1
The limited context window of contemporary large language models (LLMs) remains a primary bottleneck for their broader application across diverse domains. Although continual pre-tr…
Retrieval Augmented End-to-End Spoken Dialog Models
Mingqiu Wang, Izhak Shafran, Hagen Soltau +4
We recently developed SLM, a joint speech and language model, which fuses a pretrained foundational speech model and a large language model (LLM), while preserving the in-context l…
RoboVQA: Multimodal Long-Horizon Reasoning for Robotics
Pierre Sermanet, Tianli Ding, Jeffrey Zhao +18
We present a scalable, bottom-up and intrinsically diverse data collection scheme that can be used for high-level reasoning with long and medium horizons and that has 2.2x higher t…