1 citations · 1 across the 8 of their papers we have counts for
9 papers
ESPIRE: A Diagnostic Benchmark for Embodied Spatial Reasoning of Vision-Language Models
Yanpeng Zhao, Wentao Ding, Hongtao Li +2
A recent trend in vision-language models (VLMs) has been to enhance their spatial cognition for embodied domains. Despite progress, existing evaluations have been limited both in p…
The AI Hippocampus: How Far are We From Human Memory?
Zixia Jia, Jiaqi Li, Yipeng Kang +12
Memory plays a foundational role in augmenting the reasoning, adaptability, and contextual fidelity of modern Large Language Models and Multi-Modal LLMs. As these models transition…
Native Parallel Reasoner: Reasoning in Parallelism via Self-Distilled Reinforcement Learning
Tong Wu, Yang Liu, Jun Bai +6
We introduce Native Parallel Reasoner (NPR), a teacher-free framework that enables Large Language Models (LLMs) to self-evolve genuine parallel reasoning capabilities. NPR transfor…
v-HUB: A Benchmark for Video Humor Understanding from Vision and Sound
Zhengpeng Shi, Yanpeng Zhao, Jianqun Zhou +6
AI models capable of comprehending humor hold real-world promise -- for example, enhancing engagement in human-machine interactions. To gauge and diagnose the capacity of multimoda…
Seek in the Dark: Reasoning via Test-Time Instance-Level Policy Gradient in Latent Space
Hengli Li, Chenxi Li, Tong Wu +8
Reasoning ability, a core component of human intelligence, continues to pose a significant challenge for Large Language Models (LLMs) in the pursuit of AGI. Although model performa…
OmniMMI: A Comprehensive Multi-modal Interaction Benchmark in Streaming Video Contexts
Yuxuan Wang, Yueqian Wang, Bo Chen +3
The rapid advancement of multi-modal language models (MLLMs) like GPT-4o has propelled the development of Omni language models, designed to process and proactively respond to conti…
TokenSwift: Lossless Acceleration of Ultra Long Sequence Generation
Tong Wu, Junzhe Shen, Zixia Jia +2
Generating ultra-long sequences with large language models (LLMs) has become increasingly crucial but remains a highly time-intensive task, particularly for sequences up to 100K to…
VideoLLaMB: Long Streaming Video Understanding with Recurrent Memory Bridges
Yuxuan Wang, Yiqi Song, Cihang Xie +2
Recent advancements in large-scale video-language models have shown significant potential for real-time planning and detailed interactions. However, their high computational demand…
An Efficient Recipe for Long Context Extension via Middle-Focused Positional Encoding
Tong Wu, Yanpeng Zhao, Zilong Zheng
Recently, many methods have been developed to extend the context length of pre-trained large language models (LLMs), but they often require fine-tuning at the target length ($\gg4K…